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Review Cite This: Chem. Rev. 2017, 117, 12641-12704

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Biointerface Structural Effects on the Properties and Applications of Bioinspired Peptide-Based Nanomaterials Tiffany R. Walsh*,† and Marc R. Knecht*,‡ †

Institute for Frontier Materials, Deakin University, Geelong, Victoria 3216, Australia Department of Chemistry, University of Miami, 1301 Memorial Drive, Coral Gables, Florida 33146, United States

‡

ABSTRACT: Peptide sequences are known to recognize and bind different nanomaterial surfaces, which has resulted in the screening and identification of hundreds of peptides with the ability to bind to a wide range of metallic, metal oxide, mineral, and polymer substrates. These biomolecules are able to bind to materials with relatively high affinity, resulting in the generation of a complex biointerface between the biotic and abiotic components. While the number of material-binding sequences is large, at present, quantitative materials-binding characterization of these peptides has been accomplished only for a relatively small number of sequences. Moreover, it is currently very challenging to determine the molecular-level structure(s) of these peptides in the materials adsorbed state. Despite this lack of data related to the structure and function of this remarkable biointerface, several of these peptide sequences have found extensive use in creating functional nanostructured materials for assembly, catalysis, energy, and medicine, all of which are dependent on the structure of the individual peptides and collective biointerface at the material surface. In this Review, we provide a comprehensive overview of these applications and illustrate how the versatility of this peptide-mediated approach for the growth, organization, and activation of nanomaterials could be more widely expanded via the elucidation of biointerfacial structure/property relationships. Future directions and grand challenges to realize these goals are highlighted for both experimental characterization and molecular-simulation strategies.

CONTENTS 1. Introduction 2. Bioinspired Nanotechnology 2.1. Identification of Materials-Binding Peptides via Biocombinatoric Screening 2.2. Chemical Synthesis of Nanomaterials Using Peptides 2.3. Experimental Approaches for Characterizing Nanoparticle Biointerfaces 2.4. Advances in Computational Approaches to Examine Nanoparticle Biointerfaces 2.5. Thermodynamic Basis of Peptide/Nanoparticle Interactions 3. Nanoparticle Assembly 3.1. Peptide Amphiphile-Driven Nanoparticle Assembly 3.2. Multidomain Peptide-Driven Assembly 3.3. Peptide-Modified Bolaamphiphilic Nanotubes for Nanoparticle Assembly 3.4. Viral-Capsid-Designed Material Assembly Using Materials-Binding Peptides 3.5. Challenges and Future Opportunities in Nanoparticle Assembly 4. Peptide-Based Materials for Energy 4.1. Energy-Storage Materials 4.2. Energy-Harvesting Materials 4.3. Energy-Conversion Materials

© 2017 American Chemical Society

4.4. Challenges and Future Opportunities in Energy Materials 5. Catalysis 5.1. Peptide-Capped Nanoparticle Catalysis 5.2. Self-assembling Peptide Templates for Catalytic Materials 5.3. Virus-Based Nanoparticle Catalysis 5.4. Challenges and Future Opportunities in Nanoparticle Catalysis 6. Biomedical Technologies 6.1. Peptide-Based Surface Coatings for Implant Materials 6.2. Materials for Regenerative Medicine 6.3. Peptide-Materials Recognition for Medical Imaging and Therapies 6.4. Challenges and Future Opportunities in Biomedical Technologies 7. Summary and Outlook Author Information Corresponding Authors ORCID Notes Biographies Acknowledgments

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Special Issue: Bioinspired and Biomimetic Materials Received: March 10, 2017 Published: August 29, 2017 12641

DOI: 10.1021/acs.chemrev.7b00139 Chem. Rev. 2017, 117, 12641−12704

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2. BIOINSPIRED NANOTECHNOLOGY

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2.1. Identification of Materials-Binding Peptides via Biocombinatoric Screening

In many cases, biology employs peptides, proteins, and other biomolecules to generate and activate functional materials.4−9 This can arise from complete proteins (e.g., as found in the Japanese pearl oyster Pinctada f ucata)10 or by peptides generated in vivo via protein cleavage and/or post-translational modification (e.g., silaffins of diatoms).4,5 By extracting these biomolecules from their inorganic components, peptides with affinity for these biologically relevant material compositions are known (i.e., SiO2, CaCO3, etc.); however, biocombinatorial methods have been exploited over the past two decades to identify new peptides with affinity for target structures that are not typically observed in nature, including both inorganic and organic/polymeric compositions.11−29 In general, two approaches are typically employed: phage display or cell-surface display. For both systems, the genetic code of the organism (either a bacteriophage for phage display or a bacterial cell for cell-surface display) is specifically modified to present randomized peptide sequences along the surface of the cell or viral capsid. Only a single sequence is repeated many times along the cell/capsid surface where different peptide sequences can be displayed on different cells or viruses. From this approach, large peptide libraries (109 and greater) can be developed that can be readily replicated through biological approaches.30,31 Both methods can be exploited to identify peptides with affinity for specific inorganic material compositions; however, phage display tends to be employed more often over cell-surface display approaches. As such, a brief discussion of this approach and its application for the identification of inorganic materials-binding peptides is included. Phage-display isolation of materials-binding peptides is traditionally studied using commercially available libraries developed using the M13 bacteriophage (Figure 1).13,17,23−25

1. INTRODUCTION There are many exquisite examples of biologically derived nanomaterials, where nature fabricates such structures for three key reasons: (1) protection against predation, (2) bioremediation, and (3) structural support. While such materials are fascinating, the typical chemical composition of these structures has little application in current technologies. For instance, mollusks generate a complex nacre structure in a brick and mortar arrangement where CaCO3 platelets are arranged in a biomolecule matrix, with this composite providing substantially increased fracture strength and fracture toughness compared to geological monolithic CaCO3;1 however, such materials do not possess inherent properties that facilitate their adaptation for technological advancement. While such nanomaterials may not find immediate use in nonbiomedical technological applications, the mechanisms and synthetic approaches employed in biological systems to fabricate such structures could be adapted for the generation of new, nonbiologically relevant materials for a diverse array of applications including optics/plasmonics, catalysis, biological and chemical sensors, energy harvesting and storage, etc. Such bioinspiration provides pathways to the sustainable and environmentally friendly production of complex inorganic nanomaterials, potentially on large scales, where the properties can be directly tuned by both the synthesis conditions and the biological molecules used to generate the final structures. Most biomimetic approaches for materials production and application rely on the use of biomacromolecules such as peptides to bind to the growing surface of the inorganic structure in solution. In this arrangement, an inorganic core is generated that is passivated by the biological component, thus resulting in a unique biotic/abiotic biointerface from which numerous properties can be integrated into the system. As we will show, these biomolecules can be highly specific for the targeted material, thus selectively binding to only a single inorganic composition in a mixture of materials dispersed in solution. In many instances, these peptides adsorb to growing structures via a series of noncovalent interactions where these interactions between the two components of the biointerface can be directly manipulated. This binding event of the biomolecule to the nanoparticle surface provides key opportunities to control both the final overall morphology of the material and the resultant properties that arise from that specific structure. Very recent results2,3 have demonstrated that the sequence employed cannot only bind to the growing material but also alter metal atom deposition on the material surface, leading to disordered metallic surface structures that deviate from the anticipated crystal structure, as discussed below. Such capabilities provide a powerful opportunity to control material properties at levels that cannot be readily achieved with conventional nonbiological approaches. Herein, we review how biointerfacial structures of bioinspired nanomaterials can be directly manipulated to control the structure/ function relationship for a variety of applications, focusing on materials-binding peptides that are typically isolated via biocombinatorial selection methods. This includes a discussion of the background of bioinspired nanotechnology and how peptides with materials affinity are experimentally and computationally characterized.

Figure 1. Structure of the M13 filamentous bacteriophage capsid.

The M13 bacteriophage is a nonpathogenic virus that readily infects bacterial cells for replication.30 As shown in Figure 1, the M13 bacteriophage is composed of ∼2700 copies of the pVIII major coat protein along the long axis of the viral capsid.30 While this region remains constant, the pIII region of the capsid presents ∼5 copies of a different peptide, where this sequence can be randomized via molecular biological approaches. Typically, septamer and dodecamer peptides are presented at this region from which binding to inorganic surfaces can be processed. By using this approach, different 12642


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bacteriophages that present different peptide sequences at the pIII variable region can be produced from which the peptide library can be generated, with typically 109 different peptides in the library.30 There are two key points that arise from such bioselection approaches. First, by having dodecamer peptides with 12 residues varied over the 20 canonical amino acids, the diversity of functional group compositions (hydrophobic, hydrophilic, aromatic, and positively and negatively charged) and arrangement within the sequence is enormous, allowing for rapid fine-tuning of the interactions of the peptides with the inorganic surface. This is important as recent studies have demonstrated that localized changes in these bioorganic structures can have dramatic implications over both the peptide affinity and the nanoparticle surface structure,32−37 which can be very difficult to achieve using traditional organic ligands. Second, the phage-display process is inherently biased against the incorporation of cysteine residues into the variable peptide domains. This is important because cysteines, with a free thiol group, would nonspecifically adsorb to many metallic and metal sulfide surfaces, thus preventing the isolation of peptides with specific affinity for particular inorganic compositions. Once developed, the phage libraries can be used to identify peptides with affinity for target surfaces through a process commonly referred to as biopanning (Figure 2).17,24,30 Briefly,

Using biocombinatorial selection techniques such as phage and cell-surface display, peptides with affinity for a variety of different compositions have been identified, including metals,15,38 such as Au,27,39−42 Ag,24,25,29 Pt,28,43−45 and Pd;26,46 metal oxides,16,18,23,47−53 including TiO2,20,22,54 Cu2O,55 GeO2,21 and ZnO;55,56 and metal sulfides such as CdS and ZnS.15,57,58 Note that, in some cases, peptides that are isolated may have affinity for multiple different compositions. Peptides with affinity for more complex, multicomponent compositions of materials have also been isolated. For instance, Belcher and co-workers have isolated sequences with affinity for L10 phase FePt and CoPt, both of which are sought-after compositions of materials for their intrinsic magnetic properties.15,38 For most inorganic materials, polycrystalline surfaces are typically used of the target composition during the phage-isolation process, where this surface must be extensively purified to remove any contaminants such as adventitious carbon to ensure that peptides with affinity for the target only are identified. To increase the degree of selectivity for the final peptides, single-crystalline target surfaces have been exploited to isolate peptides with both facet and compositional selectivity.43,44 In one specific study,44 Huang and colleagues used shaped Pt materials, cubes and octahedra, that displayed only (100) or (111) facets, respectively, as the target inorganic surface. In this approach, only Pt of specifically controlled crystallographic orientations was presented to solution, thus ensuring that the peptides isolated would bind to that specific surface. Using this method, the T7 (TLTTLTN) and S7 (SSFPQPN) peptides were identified with affinity for the Pt (100) and (111) surfaces, respectively, where they could be used to generate Pt nanocubes (T7) and tetrahedra (S7) in solution using singlecrystal Pt nanoparticle seeds.44 In a separate study, Forbes et al. were also able to isolate Pt(100) binding peptides using a similar approach with Pt nanocubes as the target for biopanning.43 Subsequent work using the T7 and S7 peptides demonstrated the ability to advance the shape control of the final nanoparticles to different morphologies.59−61 This was achieved by using single twinned nanoparticle seeds instead of single-crystal seeds. Using the twinned seeds resulted in the production of right bipyramid and [111]-bipyramid shaped nanoparticles using the T7 and S7 peptides as capping agents, respectively.

Figure 2. Phage-display biopanning process for the isolation of materials-binding peptides using metal solids as targets.

2.2. Chemical Synthesis of Nanomaterials Using Peptides

Using the peptides identified via biocombinatorial selection techniques, a great variety of different inorganic nanomaterials have been generated, typically in aqueous solution at room temperature.2,24−27,32,38,42,44,45,61−70 For most, but not all, of these inorganic nanostructures, the peptides cap the growing nanoparticle on the surface, arresting particle growth, stabilizing the particle in colloidal suspension, and generating the biointerface. Alternative mechanisms for peptide-controlled growth of inorganic oxide materials have also been proposed, e.g., by modulation of the stability of intermediate phases via control of the local concentration of ions available for complexation.71 For metallic materials such as Au and Pd, very simple reduction-based methods are traditionally used.26,32,64 In this regard, the materials-binding peptides are incubated with the metal ions in solution for specific time periods, followed by reduction using an exogenous reductant. In this situation, the reductant reduces the metal ions to zerovalent metal atoms. This leads to nanoparticle nucleation and growth, which is arrested when the peptides adsorb to the

the phage library is incubated with the target material, which allows for binding of the viruses to the inorganic surface. The solid material is separated from the solution and washed with detergent from which nonbinding phages are removed. Next, the bound phages are released from the surface of the material through changes to the solution conditions, typically through changes in the pH. The released phages are then incubated with bacteria, leading to amplification of these viruses. This process constitutes a single round of biopanning, leading to a narrowing of the peptide library. Subsequent rounds of biopanning are then processed from which the stringency of the washing step is increased to remove weakly and nonspecifically bound viruses from the inorganic material. This process is employed for ∼3−5 biopanning cycles from which the DNA of the remaining phage clones are sequenced to determine the peptide sequences with affinity for the target surface.17,24,30 Viruses with the strongest affinity may not be released from the target surface. In this case, their capsid can be ruptured directly on the inorganic material to collect the DNA to determine peptide sequences.24 12643


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trations between 1.0 and 4.0 μg/mL, where adsorption of the peptide to the Au surface was monitored via changes in the resonating frequency of the quartz (Figure 3). Due to the time

growing metallic surface in solution. In this case, the peptides bind through the collective interactions of the amino acid residues, which forms the biotic/abiotic interface that is responsible for colloidal stability. Interestingly, a recent study by Briggs et al. demonstrated that the reductant strength has substantial effects on the final structure of Au peptide-capped materials.63 To this end, as the strength of the reductant decreased, the overall size of the nanoparticle increased. Such effects likely arise from changes in the rate of nucleation and reduction, all of which are determined via the reduction rate, thus leading to dramatic changes in particle morphology. Other approaches can be used to fabricate inorganic materials not composed of zerovalent metals. For instance, the biomolecular-driven fabrication of metal sulfide structures such as ZnS and CdS follows a two-step process.13,15,58 Using ZnS as an example, Zn2+ ions are commixed with the peptide for selected time points, allowing for complexation between the two components to occur. Subsequently, Na2S is introduced, driving ZnS quantum dot formation and growth, which is again arrested via binding of the biomolecule to the particle surface. Analogous approaches can be used for other metal sulfides, where the cation is replaced with an appropriate precursor. Finally, a variety of metal oxide structures have been generated using peptides;4,5,20,21,23,36,37,54,56,72−74 however, these syntheses may result in encapsulation of the peptide within the growing structure or rely on controlled oxidation of zerovalent metal materials to generate the specific metal oxide.

Figure 3. Typical QCM data for peptides binding to inorganic materials. Changes in the frequency of the QCM sensor as a function of time are observed based on 3R-GBP1 peptide adsorption at selected concentrations. An inverted plot is presented for more intuitive data analysis. Reprinted with permission from ref 40. Copyright 2006 American Chemical Society.

that it takes for the peptide solution to flow from the stock to the sensor, no adsorption at short time periods is anticipated. Once the peptide solution reaches the sensor, changes in frequency will occur. Each data set was subsequently fit using a Langmuir isotherm to extract individual kobs values for each peptide concentration. This isotherm is ideal for such methods as it assumes monolayer coverage, which is a reasonable assumption based on the lack of dissipation energy for many of these peptide binding experiments. Note that not all QCM systems are able to quantify the dissipation energy of the adsorbed peptide layer. Plots of the kobs values as a function of peptide concentration can subsequently be fit linearly where the slope and y-intercept of the best-fit line represent the ka and kd values of peptide binding, respectively.40 Using this approach for the 3R-GBP1 peptide, a ka value of 3.49 × 103 M−1 s−1 was determined, while a kd of 3.12 × 10−4 s−1 was observed.40 These values can be then used to determine the equilibrium constant (Keq) and free energy of binding (ΔG) via standard thermodynamic equations, resulting in values of 1.12 × 107 M−1 and −9.68 kcal/mol (−40.5 kJ/mol), respectively.40 This QCM approach has additionally been exploited to identify compositional selectivity of the peptides for the target surface.77,89 To this end, Tamerler et al. employed the 3RGBP1 peptide and processed its affinity for both Au and Pt QCM sensor surfaces.89 As indicated above, GBP1 was identified for Au binding;12 thus, its affinity for Au should be greater than that for Pt. From this analysis, a greater ΔG value of −9.68 ± 0.28 kcal/mol (−40.5 ± 1.2 kJ/mol) was observed when studying the peptide affinity for Au, as compared to the value calculated for binding to Pt (−8.27 ± 0.17 kcal/mol; −34.6 ± 0.7 kJ/mol).89 Interestingly, only a small difference in affinity was noted between the two metals; however, both share similar face-centered cubic structures and lattice parameters, which may give rise to the similar degrees in affinity based on raw ΔG values. When the peptides were incubated with a surface patterned with separate regions of Au and Pt (Figure 4), the peptides preferentially absorbed onto the Au surface, based on fluorescence analysis of the interface post-peptide-binding. Such results indicate that, while the raw binding free energy

2.3. Experimental Approaches for Characterizing Nanoparticle Biointerfaces

The biointerface constructed at the nanoparticle surface is exceedingly complex to characterize; however, atomically resolved understanding of this critically important structural regime is imperative. While techniques such as UV−vis spectroscopy, transmission electron microscopy (TEM), selected area electron diffraction (SAED), and X-ray-based techniques have been exploited to study the inorganic core of these materials (refs 2, 24−27, 32−34, 38, 42, 44, 59, 62, 64, 65, 69, 70, and 75−83), methods that specifically acquire data concerning the peptide structure at the biointerface are rather limited; however, a variety of techniques have been exploited to characterize this regime. Because of the complexity of the system to be characterized (multiple different lengths of peptides adsorbed onto a 2−10 nm particle dispersed in aqueous solution), analysis of the binding event of the peptides to two-dimensional surfaces has been explored, most notably via quartz crystal microbalance (QCM) analysis,35,66,73,76,77,84−94 surface plasmon resonance (SPR) spectroscopy, 28,29,39,40,95−97 and atomic force microscopy (AFM).40,97−102 QCM specifically exploits the piezoelectric effect of quartz to measure the amount of matter adsorbed on the metal-coated sensor based on frequency changes.103 Using this information, binding thermodynamics can be extracted to quantify the affinity for the peptide to the target material surface, thus providing key information about the biointerfacial interactions. Sarikaya and colleagues were one of the first groups to exploit QCM methods to quantify peptide binding to inorganic materials.40 In this landmark study, the 3R-GBP1 peptide, which was three tandem repeats of the GBP1 peptide (MHGKTQATSGTIQS) previously isolated with affinity for Au via cell-surface display,12 was employed. The peptide was flowed over the Au-coated QCM sensor at various concen12644


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Figure 4. Demonstration of materials-selective binding. (a) Scheme employed to confirm binding of the 3R-GPB1 peptide to Au regions over Pt and SiO2 domains. In this regard, biotinylated peptide (Bio-GBP1) was incubated with the patterned surface. Subsequent binding of streptavidin-coated quantum dots (SAQD) to the immobilized Bio-GBP1 allowed for fluorescent imaging of the peptide location on the surface. (b, d) Images of the surface; (c, e) fluorescence analysis, confirming the location of the peptide on the Au regions. Reprinted with permission from ref 89. Copyright 2006 John Wiley & Sons.

affinity to Au and Ag QCM sensor surfaces, demonstrating only minor differences between the selected peptides and the two metals. That said, the largest difference in affinity was noted for the AuBP1 and AgBP1 peptides on Au (−37.6 ± 0.9 versus −31.6 ± 0.2 kJ/mol). This demonstrates that a degree of selective interactions for the peptides on a Au surface is possible. While this difference appears to be small, the resulting variations in the degree of fractional coverage (θ) between these two peptides can be quite large. The θ value is quantified using the equation θ = C/(C + Keq−1), where C is the peptide solution concentration and Keq is the equilibrium constant of peptide−surface binding.40 When comparing mixtures of the AuBP1 and AgBP1 peptide for binding to the metal surface, the θ value for each peptide is a function of the peptide concentrations and their equilibrium constants for metal binding. Figure 5a presents a plot of the surface coverage of the AuBP1 and AgBP1 at selected mixture concentrations on Au, which is based on the QCM-measured equilibrium constant for the peptides on the inorganic surface.77 Interestingly, at equal peptide concentrations, the surface coverage depends strictly on the two equilibrium constants, giving rise to an 11.2fold enhancement of the AuBP1 over the AgBP1 on Au in a mixture of the two sequences. Figure 5b displays the analysis of binding on a Ag surface for the same peptides where only a

may be similar, small differences in these values give rise to large degrees of actual materials specificity. Additional QCM-based selectivity analyses of peptide affinity have generally agreed with the results of Tamerler et al.89 For instance, Knecht and co-workers77 have compared four peptides that were isolated with affinity for either Au40 (AuBP1, WAGAKRLVLRRE; AuBP2, WALRRSIRRQSY) or Ag 29 (AgBP1, TGIFKSARAMRN; AgBP2, EQLGVRKELRGV). Table 1 lists the ΔG values for these peptides’ Table 1. QCM-Determined ΔG Values for Indicated Peptides Binding to Au and Ag Surfaces peptide

sequence

pIa

material

AuBP1

WAGAKRLVLRRE

11.7

AuBP2

WALRRSIRRQSY

12.0

AgBP1

TGIFKSARAMRN

12.0

AgBP2

EQLGVRKELRGV

8.9

Au Ag Au Ag Au Ag Au Ag

ΔGb,c,d (kJ/mol) −37.6 −35.3 −36.4 −36.7 −31.6 −35.9 −35.3 −36.2

± ± ± ± ± ± ± ±

0.9 0.8 0.3 0.8 0.2 1.0 1.2 1.0

a

Calculated using http://web.expasy.org/compute_pi/. bTop values, Au binding; bottom values, Ag binding. cValues for Au from ref 85. d Values for Ag from ref 77.

Figure 5. Surface-coverage analysis for mixtures of the AuBP1 and AgBP1 peptides on (a) Au and (b) Ag. The dash-dot line represents the coverage at equal peptide concentrations. Reprinted with permission from ref 77. Copyright 2014 American Chemical Society. 12645


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negligible difference between ΔG values was determined by QCM (−35.3 ± 0.8 kJ/mol for AuBP1 versus −35.9 ± 1.0 kJ/ mol for AgBP1), demonstrating no substantial differences in the peptide coverage on the metal surface. Additional studies have exploited QCM to elucidate basic thermodynamic parameters for the binding of peptides to Au surfaces (see section 2.5 below for additional discussion). For instance, Walsh and colleagues exploited a peptide library of 12 known materials-binding peptides to identify these thermodynamic parameters for peptide affinity for Au.85 This library (Table 2) contained a majority of peptides identified with Au

sequence has a great effect on the affinity of the biomolecule for the inorganic material. A complementary technique to QCM employed to characterize the biointerfacial structure of nanoparticles is SPR.28,29,39,40,95−97 SPR uses the changes in the surface plasmon resonance of Au in response to an analyte (in this case a peptide) binding at the metal surface.104 It is highly sensitive, thus providing additional information on the affinity of the peptides for the metal. In this approach, the biomolecules are again flowed over the SPR sensor surface, which is typically Au due to its inherent plasmon resonance. From peptide adsorption, changes to the optical properties of the Au surface can be monitored to quantify the degree of peptide adsorption.104 Sarikaya and co-workers have extensively employed the SPR approach to quantify not only peptide binding but also the effects of the peptide molecular structure on its affinity. Additionally, this team was able to adapt the SPR approach to materials other than Au, such at Pt and SiO2,28,95 thus expanding its capability to multiple different compositions of inorganic materials. SPR is typically focused on adsorption of molecules to the Au surface. In initial work by Sarikaya and colleagues,40 the team compared the SPR binding analysis of the 3R-GPB1 peptide to the results observed (and discussed above) for the same biomolecule on Au via QCM. Interestingly, while QCM demonstrated an exponential binding curve, SPR displayed biexponential Langmuir binding behavior, which was originally attributed to the polycrystalline structure of the SPR surface; however, AFM analysis of this binding event later suggested an alternative process based on peptide adsorption differences as a function of surface coverage.100 From the biexponential fit of the data, two different binding free energies (ΔG values) for the peptide at the different binding domains can be extracted (−8.797 and −7.765 kcal/mol; −36.8 and −32.5 kJ/mol, respectively).40 Of note, the variations in affinity appear to arise from differences in the rate of peptide adsorption (ka), which is 20-fold higher for the first binding event over the second. The rates of peptide desorption (kd) are quite similar; thus, the ka values drive the changes in the overall affinity of the different binding events. It is worth noting that the SPR and QCM ΔG values are generally similar (−8.797 versus −9.68 kcal/mol, respectively).40 SPR has additionally been used to demonstrate differences in peptide adsorption to Au based on the molecular structure. For this, Hnilova et al. studied both linear and cyclic-constrained versions of the AuBP1 and AuBP2 peptides.39 The main difference between the linear and cyclic peptides was that the cyclic structure had two cysteines appended to the peptide: one at the N-terminus and one at the C-terminus. These cysteines were allowed to react to form disulfide bonds, resulting in the cyclic motif. The four peptides (two sequences either linear or constrained) were subsequently analyzed for Au binding via SPR analysis. For the linear AuBP1 and AuBP2 peptides, ΔG values of −8.9 ± 0.2 and −8.7 ± 0.1 kcal/mol (−37.2 ± 0.8 and −36.4 ± 0.4 kJ/mol, respectively) were determined,39 consistent with separate results obtained via QCM;85 however, when the cyclic peptides were studied, ΔG values were determined as −8.7 ± 0.1 kcal/mol (−36.4 ± 0.4 kJ/mol) for the cyclic AuBP1 species and −9.7 ± 0.2 kcal/mol (−40.6 ± 0.8 kJ/mol) for the cyclic AuBP2 peptide.39 While no significant difference was noted for the AuBP1 peptide between the linear and cyclic forms, there was a substantial change between the two configurations for the AuBP2 peptide, all of

Table 2. Peptide Library Analyzed by QCM for Binding Affinity to Aua

a

peptide

sequence

AuBP1 GBP1 B1 AuBP2 Midas2 AgBP2 Z2 QBP1 A3 AgBP1 Z1 Pd4

WAGAKRLVLRRE MHGKTQATSGTIQS LKAHLPPSRLPS WALRRSIRRQSY TGTSVLIATPYV EQLGVRKELRGV RMRMKMK PPPWLPYMPPWS AYSSGAPPMPPF TGIFKSARAMRN KHKHWHW TSNAVHPTLRHL

ΔG (kJ/mol) −37.6 −37.6 −36.6 −36.4 −35.7 −35.3 −35.0 −35.0 −31.8 −31.6 −31.3 −30.3

± ± ± ± ± ± ± ± ± ± ± ±

0.9 1.0 1.2 0.3 1.2 1.2 0.6 1.1 0.3 0.2 0.1 0.2

θ (%) 97.64 97.70 96.85 95.91 95.75 94.57 92.49 93.61 82.83 79.83 81.41 70.20

± ± ± ± ± ± ± ± ± ± ± ±

0.82 0.80 1.47 0.45 2.00 2.51 1.07 2.53 1.26 1.56 4.54 0.49

Data in this table comes from ref 85.

affinity; however, additional sequences isolated with affinity for other inorganic materials were also studied. From the QCM analysis of binding, all of the peptides ranged over a very small window of affinity (from −30.3 to −37.6 kJ/mol).85 Interestingly, no correlations between stronger affinity for Au and the biocombinatorial selection target were identified, suggesting that the degree of selectivity to be achieved via phage or cell-surface display was not as great as anticipated. Very recent results from Hughes et al. have expanded on this library analysis, focusing on point mutations of individual amino acids within a peptide sequence.35 In this regard, known anchor residues (defined as those residues with the most persistent contact with the target surface as identified via computational modelingsee section 2.4) were selectively replaced with alanines to diminish binding at that local site. This initial mutation analysis was completed using the Pd4 peptide (TSNAVHPTLRHL) originally isolated with affinity for Pd;26 however, studies have demonstrated that it also has the ability to bind Au with substantial affinity and stabilize Au nanoparticles in solution.63,64,85 For the Pd4, the two histidine residues at the 6 and 11 positions were identified as the anchors.85 As such, three mutant peptides that replaced histidine for alanine either at the 6 or 11 position, or both, were generated. Two additional mutants that scrambled the sequence or clustered the two histidines at the N-terminus were also prepared. On the basis of the QCM binding analysis of these five peptides, noticeable differences in affinity were identified, ranging from −27.2 ± 0.2 kJ/mol for the weakest peptide (H6A mutant of Pd4) to −35.5 ± 0.2 kJ/mol for the strongest binder (clustering the histidines at the N-terminus of Pd4).35 This is compared to the parent Pd4 affinity for Au (−31.4 ± 0.1 kJ/mol),85 demonstrating that the peptide 12646


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ensemble of these two molecules, both when free in solution and when adsorbed at the interface. Sarikaya and colleagues also have been able to adapt SPR beyond Au toward the binding of peptides to different inorganic surfaces.28,95 To achieve this, the Au SPR sensor surface is coated in a thin layer of a secondary material such as Pt metal or SiO2. This layer is typically incorporated with nanoscale thicknesses such that the plasmonic properties of the underlying Au sensor remain sensitive to the peptide binding at the secondary material surface. Such a technique was first introduced in 2007 by Seker et al. to use SPR to probe the binding of Pt-specific peptides to Pt metal.28 In this specific situation, a 2 nm thick layer of Pt was directly coated onto the Au surface, as quantified by QCM. Once the sensor was prepared, the binding of the PtBP1 peptide (PTSTGQA) was processed with the peptide in both linear and cyclic forms. As for the AuBP1 and AuBP2 peptides discussed above, the cyclic from of the PtBP1 peptide was generated through the formation of a disulfide bond from two cysteines incorporated into the peptide sequence at both termini. Remarkably, when these two different conformations of the same peptide were studied for Pt binding via the modified SPR approach, a biexponential binding event was observed by the linear form, similar to the linear 3R-GBP1 peptide; however, the cyclic form of the PtBP1 peptide demonstrated only a single binding event. From this SPR analysis, ΔG values of −7.16 ± 0.14 and −6.22 ± 0.14 kcal/mol (−30.0 ± 0.6 and −26.0 ± 0.6 kJ/mol, respectively) were calculated for the two different binding events of the linear PtBP1 peptide; however, a greatly increased free energy of binding was noted for the cyclic form with a value of −8.97 ± 0.13 kcal/mol (−37.5 ± 0.5 kJ/mol).28 Such effects were similar to those observed for the linear versus cyclic forms of the AuBP2 peptide, where enhanced affinity was noted for the constrained loop peptide; however, no difference in binding was noted for the linear and cyclic forms of the AuBP1 sequence.39 These results demonstrate that the overall molecular structure of the biomolecule plays an important role in the binding affinity for the inorganic surface. While QCM and SPR provide information concerning the amount of peptide adsorbed at the inorganic surface, they cannot image the structure or patterning of the biomolecules along the newly formed biointerface. To access such information, AFM methods are available that can provide actual imaging and size-based analyses of the biointerfacial structure generated at the Au surface;98−102 however, it is important to note that differences in the observed peptide/ biointerface structure on the two-dimensional surface as compared to three-dimensional, quasi-spherical nanoparticles is likely. So et al. studied the binding of the 3R-GPB1 peptide to atomically flat Au (111) using ex situ noncontact mode AFM.100 In this regard, they analyzed the Au surface before, during, and after peptide adsorption at selected time points and concentrations to image the peptide layer structure that was formed. Figure 6A presents the images of the interfaces that were achieved after 1200 s of peptide adsorption at 3R-GBP1 concentrations ranging from 0 to 2320 nM. As can be seen from these images, clear changes in the surface peptide morphology were evident as a function of the biomolecule concentration, where the degree of surface coverage increased at higher peptide concentrations.100 Using this AFM approach, the degree of surface coverage (θ) can be calculated (Figure 6B), which was comparable to the observations achieved from SPR analysis of the same peptide on the Au surface.40 This

which was determined by SPR binding analysis. This indicates that such structural effects can dictate the binding affinity of the biomolecule where SPR is an appropriate experimental approach to elucidate such differences. While SPR and QCM can provide complementary analysis of the binding of peptides to the metal surface, QCM is more sensitive to the system temperature due to changes in the vibrations as a function of temperature. As a result, SPR tends to be more accommodating to changes in temperature where thermal fluctuations at the surface do not substantially increase the noise in the final data. As such, Seker et al. were able to use SPR analysis of peptide binding at temperatures between 10 and 55 °C to extract additional thermodynamic parameters including enthalpy (ΔH) and entropy (ΔS) values using the van’t Hoff equation.97 The researchers used two different biomolecules to study this process: the GBP1 peptide and the triple tandem repeat 3R-GBP1. For clarity, we remark here that the original authors referred to these peptides as l-GBP1 and 3lGBP1, respectively. However, to harmonize this nomenclature with more recent studies, herein we refer to these peptides as GBP1 and 3R-GBP1. For both peptides, calculation of equilibrium constants (Keq) at both low and fast adsorption regimes was processed at various temperatures, from which the thermodynamic parameters were extracted. Of note, for the single GBP1 peptide, the ΔH values were negative; however, the entropy values (ΔS) were all positive (Table 3).97 When Table 3. Thermodynamic Parameters for the Binding of GBP1 and 3R-GPB1 on Aua,b parameters

l-GBP1

ΔH1 (kcal/mol) ΔH2 (kcal/mol) ΔS1 (cal/mol·K) ΔS2 (cal/mol·K)

−5.09 ± 0.25 −1.84 ± 0.53 +10.90 ± 1.30 +19.60 ± 2.20

3l-GBP1 −22.1 −13.4 −43.4 −16.6

± ± ± ±

3.0 1.5 8.5 4.6

a

Note that the table headings carry the original labels used in ref 97, where l-GBP1 and 3l-GBP1 correspond with GBP1 and 3R-GBP1, respectively. bData for this table comes from ref 97.

considering the 3R-GBP1 peptide (Table 3), the enthalpy values were negative and greater in magnitude compared to the single GBP1 peptide, but uniquely, the ΔS values were also negative. These results, which were fully accessed using SPR, indicated that the peptide-adsorption processes for these two biomolecules were both exothermic; however, the differences observed for the entropy term arise from other effects such as water desorption during peptide binding to the metallic surface and the fact that peptide conformational changes are a more significant factor for the larger 3R-GBP1 over the single repeat GBP1. To elaborate, this might suggest that 3R-GBP1 may be able to access a relatively greater number of conformations in the unbound state relative to GBP1, which might lead to a relatively greater loss of entropy upon adsorption. This, in partnership with the release of surface-bound water molecules during the adsorption process (which usually contributes to an increase in ΔSads), might explain the loss of entropy for 3RGBP1 relative to GBP1. However, at present, these molecularscale reasons are not known; this example serves to illustrate how challenging it can be to interpret differences in these measured thermodynamic quantities for different peptides (in this case of differing chain lengths) without recourse to additional detailed information regarding the conformational 12647


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Figure 7. Scheme proposed by So et al. for the two-stage adsorption of the 3R-GBP1 peptide on Au as imaged by AFM. Reprinted with permission from ref 100. Copyright 2009 John Wiley & Sons.

is a well-known sequence with affinity for Au and Ag that was identified via phage display.25,42 The distinction between this work and the AFM studies above of the 3R-GBP1 binding is that the A3 peptide is substantially shorter in length (12 versus 42 amino acids). In this study, the authors achieved AFM images of the Au surface after adsorption of different solution concentrations of peptides and at selected time points during the adsorption study.102 Similar surface features were observed as with the 3R-GBP1; however, it was noted that the different interactions in the system (i.e., peptide−Au, peptide−peptide, and peptide−solvent) can have extremely important effects on the structure of the biointerface that is generated. Additionally, this study observed that defects in the Au surface also substantially altered the structure of the biointerface, which is not surprising as these high-energy sites are likely to have varying degrees of interaction with the biomolecules.102 While all of the above techniques (QCM, SPR, and AFM) provide exceedingly important information on the peptide surface structures when adsorbed onto their target material, they generally require the use of a two-dimensional surface that is quite different than the three-dimensional interface generated along nanoparticles dispersed in solution. Moreover, to date, the AFM characterization reported for these peptide/materials interfaces has been performed ex situ, using dried samples. This means the resulting adsorbed peptide stuctures may be a product of the drying process. Going forward, in situ AFM studies in this area would be a promising future development for the characterization of these interfaces. Unfortunately, the number of experimental techniques that are available to probe this highly complex system remains quite limited, with a good emphasis on circular dichroism (CD) spectroscopy.32−34,64,66,76,87,105 CD is a straightforward method to characterize the structure of biomolecules using standard approaches106 that can be used to compare differences in peptide conformations when bound to nanoparticles. As an example, Coppage et al. studied the structure of the Pd4 peptide (TSNAVHPTLRHL) and selected mutant sequences bound to Pd nanoparticle surfaces (Figure 8).34 The Pd nanoparticles were generated using standard approaches where Pd2+ ions were reduced by NaBH4 in the presence of the indicated peptides. For the CD analysis, all of the samples were

Figure 6. AFM analysis of 3R-GBP1 binding as a function of peptide concentration. (A) AFM image of the surface after 1200 s of adsorption at the indicated concentration; (B) degree of surface coverage (θ) as a function of peptide concentration, comparing the coverage as measured by AFM and SPR. Reprinted with permission from ref 100. Copyright 2009 John Wiley & Sons.

suggests that the peptide follows simple Langmuir adsorption profiles to the inorganic substrate. When the binding of the 3R-GBP1 peptide was followed at a single concentration as a function of time, a unique, twodomain adsorption event was observed via changes in the structure of the developed biointerface.100 Interestingly, this resulted in a biexponential Langmuir fit of the surface adsorption plot as a function of time, fitting quite well with the SPR results discussed above.40 In this regard, the researchers proposed a unique two-stage process that gave rise to the final biointerface structure (Figure 7).100 In the first regime, individual peptides would adsorb to the Au surface; however, they are highly mobile. This mobility allows for them to aggregate on the Au surface to form a branched network. Once this occurs, the second regime in the adsorption process is reached where subsequent individual peptides that adsorb to the Au do so at the open spaces that remain. This is what is suggested to give rise to the biexponential fit of the data from the two different adsorption processes occurring at the Au surface, all of which was supported by both SPR and AFM imaging results.40,100 Note that further research using this system demonstrated that changes to the biointerfacial structure can be achieved via the method by which the surface was washed after peptide adsorption;99 the force of the water stream used to remove free peptide can cause changes to both the underlying Au structure and, in turn, the peptide layer. In a separate work by Singamaneni and co-workers, AFM approaches were used to study the adsorption of the A3 peptide to a Au (111) surface.102 The A3 peptide (AYSSGAPPMPPF) 12648


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Figure 8. Comparison of CD spectra before and after peptide adsorption. (a) Analysis for the parent Pd4 peptide (TSNAVHPTLRHL) before (black) and after (red) nanoparticle binding. Similar analyses were conducted for the (b) A6 (TSNAVAPTLRHL), (c) A11 (TSNAVHPTLRAL), and (d) A6,11 (TSNAVAPTLRAL) peptides. (e, f) Comparison between the different peptide structures as a function of sequence both (e) free in solution and (f) bound to the Pd nanoparticle surface. Reprinted with permission from ref 34. Copyright 2010 John Wiley & Sons.

diluted to where the peptide concentration was 16 μM.34 When comparing the free peptide in solution to the biomolecule capped on the particle surface, significant structural differences were noted. This was not surprising as the structure of the biomolecule is likely to be substantially perturbed to ensure metal surface binding as compared to the free molecule in solution. Furthermore, CD spectroscopy was able to elucidate structural differences between the Pd4 and mutant sequences when bound to the nanoparticle surface.34 This included singlepoint mutations for histidine to alanine that changed the binding at localized regions within the peptide sequence for the nanoparticle. This is a highly powerful technique that can be used readily to characterize structural differences in the biointerface morphology. One important area where CD spectroscopy has played a major role is in the area of photoswitchable peptides adsorbed onto nanoparticle surfaces.66,87 Recent studies have shown that the incorporation of photoswitches into peptide sequences can cause dramatic changes in the biointerface structure on nanoparticles. This was studied using the AuBP1 peptide where an azobenzene moiety was incorporated at either the Nor C-terminus via thiol−maleimide coupling at incorporated cysteine residues. When the peptide was adsorbed onto either Au or Ag nanoparticles, computational modeling indicated that

the azobenzene was in direct contact with the metal.66,87 Upon photoswitching of this moiety from the trans to cis conformation via light, the backbone structure of the biomolecule changes, thus changing the overall biointerface morphology. Switching the azobenzene back to the trans isomer causes the peptide, and the overall biointerface, to restructure back to the original configuration. To experimentally demonstrate this effect, CD spectroscopy was instrumental; the spectra of the azobenzene-modified peptide free in solution and bound to the Au and Ag nanoparticle surface were clearly different, based on the ellipticity of the peak at 198 nm. Additionally, discernible differences in the spectra before and after the photoswitching event were observed, confirming changes in the biointerface structure.66,87 One interesting observation made by Naik and co-workers is that the introduction of chiral peptides to Au nanoparticles results in the generation of a CD signal at around the same position as the plasmon band of the inorganic material (Figure 9).105 They observed this both for the helical E5 peptide (CGGEVSALEKEVSALEKEVSALEKEVSALEKEVSALEK) that was covalently bound to a Au nanoparticle through the thiol of a cysteine residue at the N-terminus and for the FlgA3 peptide (DYKDDDDKPAYSSGAPPMPPF) that lies flat on the Au particle surface through multidentate interactions of the 12649


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with the electrons of the metallic nanoparticle.105 When the plasmon resonance is excited, the surface electrons of the nanoparticle collectively oscillate, potentially allowing them to interact with the chiral peptides. This was suggested to give rise to the peak in the CD spectrum. Additionally, at lower wavelengths of the CD spectrum, changes in the peptide structure were observed between the bound and unbound peptides, especially for FlgA3 (Figure 9),105 thus further demonstrating the use of this technique to characterize nanoparticle biointerfaces. Beyond CD spectroscopy, only a handful of additional experimental approaches have been applied to provide important information concerning the biointerfacial structure for nanoparticles capped with materials directing peptides. For instance, two groups have exploited nuclear magnetic resonance (NMR) methods to characterize the structure of materials directing peptides both bound to an inorganic surface and free in solution.107,108 These studies focus on the binding of peptides to SiO2 and TiO2 surfaces only, thus presenting fantastic opportunities to probe additional biointerfaces. NMR characterization of nanoparticles is exceedingly difficult due to the size of the materials leading to significant anisotropy. Such methods have been applied to characterize the ligands of alkanethiol-capped Au nanoparticles;109−112 however, the alkanethiols were bound to the particle through a thiol group, and thus the alkyl chains extended away from the surface. While NMR is able to spectroscopically observe signals for the groups at points extended away from the nanoparticle, the thiol and other groups that are near to the material cannot readily be observed. For peptide-capped materials, the bioligands lay flat on the surface; thus, observation of NMR signals from such ligands is challenging. In the first work, Mirau et al. employed nuclear Overhauser effect spectroscopy (NOESY) and saturation-transfer difference (STD) NMR to characterize peptides bound to SiO2 and TiO2 nanoparticles.108 To obtain the data, the researchers exploited the inherent on/off equilibrium of the biomolecules for the nanoparticle surface, thus allowing for the spectroscopic observation of the peptides and their orientations on the material. Figure 10 presents the NMR-obtained structure of the TBP6 peptide (RKLPDA) bound to a SiO2 nanoparticle surface, which is described as the C-shaped structure based on the peptide morphology.108 The fast on/off equilibrium facilitated observation of NMR signal from which the overall

Figure 9. Optical characterization of FlgA3-capped Au nanoparticles. (A) UV−vis absorbance of the peptide and peptide-capped nanoparticles displaying the plasmon band at ∼520 nm. (B, C) CD analysis of the materials over the UV−visible range (B) and the UV range only (C). Reprinted with permission from ref 105. Copyright 2011 American Chemical Society.

residues of the sequence. Such a peak at the plasmon resonance was suggested to arise from the interaction of the chiral peptide

Figure 10. (a) NMR-derived structure of the TBP6 peptide when bound to a SiO2 nanoparticle. (b) Same structure from a different perspective. Reprinted with permission from ref 108. Copyright 2011 American Chemical Society. 12650


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rational manipulation of the peptide/nanoparticle interface to enable the realization of functional, new bioinspired materials. As explained earlier, the clear connections between a peptide sequence and its propensity to noncovalently adsorb to a solid surface remain unresolved. What is clear, as particularly evident from homopeptide studies116,117 and from experimental binding studies on tandem repeat peptide sequences,95 is that the interfacial binding strength of a given sequence is not an additive sum of the binding strengths of the individual residues. In other words, despite decades of intensive research, currently it is simply not possible to a priori reverse-engineer a peptide sequence that possesses a predictable binding affinity to a given target material. The ultimate goal arising from the combination of both experimental and molecular modeling data in this context is the use of informatics to mine such combined data sets and reveal these connections. That said, it does not necessarily follow that the a priori prediction of peptide− materials binding affinity will automatically lead to the ability to predict the f unctionality of these biointerfacial materials; the resolution of this remains an additional future grand challenge. Structural details of the peptide/nanoparticle biointerface are therefore a critical component of any evaluation of the abiotic/ biotic interface, not only for the purposes of contributing to a data set for subsequent harvesting by informatics but also to inform the development of nonintuitive metrics with which such informatics approaches can be used to eventually evaluate, score, and predict peptide−materials binding propensities. Current experimental evidence indicates that many peptides that have been biocombinatorially selected to bind to inorganic materials are intrinsically disordered in their molecular structure.118 Intrinsically disordered peptides (IDPs) are thought to not be characterized by a single conformation, or even perhaps by a single class of conformations; the structural traits of these IDPs are better described by an ensemble of conformations. This results in a complex energy landscape119 for these systems120 (see Figure 11 for an example) that cannot be adequately explored using simple approaches such as static geometry optimizations of a fixed number of possible structures or molecular simulations that are based on a limited number of initial configurations, even if that “limited number” is substantial. As illustrated in Figure 11, an IDP (in this case, the IDP is not even in a surface adsorbed state) can support a highly complex landscape with hundreds of distinct groups of structures, some of which are separated by very high energetic barriers. Clearly, this scenario demands a targeted simulation strategy and presents specific challenges for molecularsimulation approaches in terms of capturing and characterizing this complex conformational ensemble. This task of recovering the ensemble of conformations is commonly referred to as conformational sampling. It is an enormous challenge for molecular simulation to even approximately recover this conformational ensemble, while being a pivotal component for elucidating the structure/property relationships that are the ultimate goal of this research field. This challenge in conformational sampling cannot currently be convincingly addressed by merely extending the duration of the simulation (at least, not until simulations can practicably run to at least seconds in actual duration) or even by considering tens of different initial conformations of the biomolecule (a typical strategy mostly employed in early simulations in this field, vide infra). Latour121,122 has described two tutorial-style technical overviews of commonly used approaches to advanced conformational sampling in general.

peptide adsorbed structure could be determined. Interestingly, multiple peptides were studied using this approach when bound to either SiO2 or TiO2, where similar structures were observed for these biomolecules when adsorbed onto the particles. This suggests that specific structural motifs may be required to ensure peptide binding to the nanoparticle surface. In a separate work by Suzuki et al.,107 they also examined the binding of the TBP6 peptide to TiO2 using STD NMR. These results demonstrated that specific residues are in direct contact with the inorganic surface, further refining the structure of the biointerface. In this regard, the N-terminal arginine and lysine lay in direct contact with the TiO2, thus anchoring the biomolecule to the inorganic component.107 Such effects provided a slightly varied structure as compared to the Cshaped morphology of Mirau et al. but are important to help refine the NMR-based analysis of peptides at nanoparticle interfaces. The differences that were observed could arise based on the underlying charge of the oxide materials depending on their synthetic approach, which should be considered for most inorganic materials. When considering the structure of peptides bound to metallic nanoparticles, Gerdon et al. exploited simple 1H NMR spectroscopy to confirm that a peptide was adsorbed to the nanoparticle surface.113 In this experiment, the researchers used cysteine-bearing peptides to place exchange with tiopronin ligands on the surface of ligand-capped Au nanoparticles. Such a process was employed so that the peptide would be specifically displayed for detection assays; thus, such a system was quite different from the biointerfaces that are the focus of this Review. In this regard, the researchers integrated a looped peptide structure from the protective antigen of B. anthracis onto nanoparticle surfaces as a protein mimic.113 NMR spectroscopy was used to confirm the presence and potential orientation of the loop on the particle; however, advanced structural analysis was not reported. While the experimental techniques discussed above can be used to assess the structure and conformation of the biointerface on nanoparticle surfaces, more advanced and newer methods are required to provide further atomic insight into these critical regions. Additional techniques such as isothermal titration calorimetry (ITC),114 Fourier transform infrared (FTIR), Raman spectroscopy, etc. may provide important new information, especially at the level of peptide binding and biointerface formation, which will be critically important to advance our understanding of how such structures are generated. At present, our experimental understanding of the structure of such systems remains underdeveloped; however, when such studies are exploited in combination with computational modeling, highly refined biointerfacial structures could be resolved. 2.4. Advances in Computational Approaches to Examine Nanoparticle Biointerfaces

Molecular simulation approaches offer enormous promise in providing molecular-scale structural details of the aqueous abiotic/biotic interface that are currently not readily accessible via experimental characterization alone.115 Such computational approaches typically yield information that is challenging to directly compare with experimental evidence. However, these computational data can provide complementary insights that can work in close partnership with experimental efforts, to provide the comprehensive overview of the peptide−materials binding event that is ultimately needed as a basis for the 12651


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degree of conformational sampling that is possible. The question of which approach is best (ranging anywhere between these extremes) is one of context and relevance to the research questions at hand; one of the key factors in determining the quality and utility of any molecular-simulation study in this field is the degree to which these approximations are stated, understood, and used to inform a discerning and critical contextualization of the simulation findings. The abovementioned example of the detailed interatomic potential may not provide useful data because the conformational sampling might be restricted to such a degree that the output becomes meaningless in the context of the IDP energy landscape. On the other hand, the energy landscape corresponding with the example of the Go̅ model, which can be almost exhaustively mapped out, can lack physical details to such an extent that, again, the veracity and relevance of the simulation findings can be questionable. The earliest reported simulation of a biocombinatorially selected peptide adsorbed at its target interface was reported by Schulten and co-workers.124 In this landmark contribution, three experimentally identified 42-residue peptides, originally denoted by the authors as GBP1, GBP2, and GBP3, were modeled using all-atom molecular dynamics (MD) simulations. We note here that GBP1 is now commonly referred to as 3RGBP1. The peptides (principally 3R-GBP1) were modeled in the surface-adsorbed state in the presence of two different crystallographic orientations of the solid Au surface, Au(111) and Au(211), in the presence of liquid water (modeled explicitly, i.e., in molecular form). These simulations were truly impressive for their time (published in 2002), in terms of system size, level of detail, and simulation duration (5 ns), but would have required access to computing power that was beyond the means of many of the authors’ contemporaries. While not seeking to disparage this pioneering work, the caveats of the conformational sampling in particular are clear; the authors by necessity assumed an ordered initial adsorbed conformation, and the subsequent exploration of the energy landscape was minimal. Nevertheless, these outcomes suggested explanations for experimentally observed properties, namely, the facet-dependence in the adsorption of GBP1 at the aqueous Au(111) interface. However, these findings clearly depended on the choice of the initial conditions of the simulations. The challenges associated with applying a contemporary advanced simulation strategy to this system remain daunting, and it is telling that simulations of this facetdependent binding of the full length of 3R-GBP1 have not since been revisited by researchers in this field using more advanced simulation approaches. Following this contribution, several early modeling studies chiefly focused on modeling structure and binding at idealized interfaces between peptides and carbon nanotubes (CNTs), semiconductors, titania, and noble metals.125−135 Many of these early studies involved severe approximations such as geometry optimization only (where no MD simulation was used) or, on a related note, considerable undersampling of conformations; and/or use of very small peptides (such as dipeptides); and/or extremely simplified (or unverified) interatomic potentials; and/or neglect of liquid water in the structural model (i.e., use of implicit solvation approximations, namely, continuum models based on the attenuation of electrostatic interactions in a dielectric medium, such as the Generalized Born model; Ren et al.136 have provided a discussion of solvation models in general). While these early simulations were laudable for their

Figure 11. Potential energy disconnectivity graph constructed from the most populated structures obtained in replica exchange molecular dynamics (REMD) simulations at 280 K. The coloring of the branches corresponds to the α-helical percentage calculated for each minimum in the database, as defined in the key. Reprinted with permission from ref 120. Copyright 2015 Nature Publishing Group.

To elaborate, the necessary compromises that are inherent to modeling the biointerface can exert a strong influence over the relevance of the simulation findings in terms of elucidating structure/property relationships, and therefore, they warrant further comment. In molecular simulation there is always a compromise between the size of the system we wish to model (where “size” is a deliberately flexible term that could imply the total number of atoms, the spatial extent of the simulation cell, etc.), the level of veracity with which we seek to model this system (the level of detail regarding the interactions that capture the essential physics and chemistry of the system that is inherent to the research objectives of the simulations, herein referred to as the interatomic potential), and the thoroughness with which we seek to explore possible conformations of the biomolecules in these systems (the conformational sampling). All three of these caveats are closely interconnected, and the result of this tension means that modeling of the biointerface must always involve approximations. For example, in one extreme, one can compromise by modeling an overly simplified system (such as the Go̅ model123), which allows exhaustive conformational sampling for very long peptide sequences. Another extreme would be to use a highly detailed interatomic potential (for example, based on quantum mechanics) and a large system size, which will necessarily (and heavily) curtail the 12652


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Figure 12. (Left) Total water/Au(111) interface, taken from a representative snapshot from a FPMD trajectory. A charge slicer passing through the O atom and perpendicular to the surface is superimposed for clarity. (Right) Oxygen (red isosurface) and hydrogen (blue isosurface) spatial distribution function of water molecules within 2.6 Å from gold atoms at the surface (yellow spheres represent gold atoms at the surface). Adapted with permission from ref 149. Copyright 2011 American Chemical Society.

“DFT+D”-type approaches)145 and those aligned with the Rutgers−Chalmers van der Waals density functional (vdWDF).146 Refinements and improvements to both approaches are ongoing but are very promising in terms of performance, particularly for the vdW-DF functionals.147,148 However, even with these developments, the use of FP approaches cannot always guarantee that the interatomic potential of these interfaces can be appropriately recovered; more extensive testing and validation against experimental data are needed for building up a reliable database of molecule−surface interactions. Moreover, the substantial computational expense of this approach, coupled with the need to incorporate explicit solvation, limited earlier simulation studies to small system sizes and very short durations (∼100 ps or less). Some of the greatest value from these FP studies lies in the generation of benchmarks (particularly of interfacial structural data, including the solvation structure in the vicinity of the interface) against which more approximate interatomic potentials (herein referred to as force fields) may be compared.149 For example, Cicero et al.149 reported the use of FPMD simulations to predict the structuring of interfacial liquid water at the Au(111) interface (see Figure 12); in the absence of corresponding experimental data, such FPMD simulations provide a wealth of structural information, against which force-field approaches can be tested. Traditional all-atom force fields have been the predominant form of interatomic potential that has, to date, been used to describe the abiotic/ biotic interface, chiefly because these force fields can be computationally economical to use for large, complex system sizes, particularly when utilized in partnership with advanced conformational sampling strategies. Many of the force fields used in this area of research are allatom force fields. However, a considerable number of coarsegrained (where several atoms can be consolidated into a single, typically spherical, interaction site) simulation studies of the abiotic/biotic interface have been reported.128,134,150−157 Coarse-grained force fields enable the access of greater simulation length-scales and time-scales, but this reduction in computing demand comes with the sacrifice of atomistic details arising from the coarse-graining. Such coarse-grained approaches provide a simplified description of the biointerface that is computationally cheaper to realize compared with allatom force fields, which can be particularly advantageous when applied to the study of multipeptide adsorption154−157 or in making very broad estimates of thermodynamic quantities such as the heat capacity of the system.128,134,150,152,153 This means

era, the scientific conclusions drawn from these studies regarding the properties of these peptide/materials interfaces should be viewed in the context of these limiting approximations. Instead, these studies are perhaps more valuable for their developmental aspects, which in turn prompted critical future improvements in simulation approaches. One counterexample of an early study can be found in the work of Latour and co-workers, who applied a more rigorous and critical simulation approach, albeit to investigate the aqueous peptide/self-assembled monolayer (SAM) interface, not the peptide/materials interface directly.126 Their use of a molecular description of liquid water at the interface (as opposed to use of an implicit solvent model) was a particularly notable development. The unsuitability of implicit solvent models for these interfacial simulations was clearly articulated in subsequent studies,73,130,137 such that most contemporary simulations of these biointerfaces make use of explicit solvation models as a matter of routine. However, implicit solvation approximations and models are also evolving,138 although this progress has been solely targeted at predicting structures of biomolecules in solution and not in a surface-adsorbed state. The interfacial interatomic potential describes all of the interactions between all of the atoms in the system under consideration. The interatomic potential that is used in modeling studies is therefore a foundational component of any simulation of the abiotic/biotic interface, and neglect or misrepresentation of relevant interactions at this interface can diminish the utility of these simulation data, regardless of the degree of conformational sampling used. Therefore, simulation approaches based on electronic structure theory (herein referred to as first-principles MD (FPMD) simulationsnote we do not include static FP calculations in this definition) were initially a popular strategy, although we limit our overview to those studies that incorporated molecular liquid water in their models.139−144 FP approaches involve approximate solutions of the Schrödinger equation (we include density functional tight binding theory (DFTB) here) and take quantum electronic effects into account. However, the key interactions acting across these biointerfaces are typically weak, nonbonded interactions, and until recently, such FP approaches, particularly those based on density functional theory (DFT), suffered from limitations in the reliable description of precisely these types of interactions. Developments in the area of new functionals to address these limitations currently can be categorized in two groups: those applying an empirical posthoc correction (such as 12653


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that the key advantage of coarse-grained force fields lies in their ability to recover relatively simple structural information, particularly when applied to surface-adsorbed multipeptide overlayers. However, the prospect of identifying and using coarse-grained force fields to reliably capture the IDP-like conformational character of materials-binding peptides is unresolved and remains an ongoing challenge.158 Following on from this, questions remain regarding the structural veracity of the outcomes from coarse-grained multichain peptide− materials adsorption, chiefly because these outcomes are extremely challenging to verify from both an experimental and a modeling perspective. It is notoriously challenging to determine the detailed molecular-level structure of biomolecules when adsorbed at a solid interface; AFM measurements described in section 2.3 offer perhaps the best opportunity to directly compare coarse-grained predictions with experimental structures. However, as mentioned earlier, most of these experiments to date have been reported for ex situ scenarios where the substrate has been dried, which are likely not appropriate for comparison with the aqueous interface structures. While in situ AFM approaches are promising in this respect and are evolving,159 this strategy has yet to be successfully reported regarding the study of multichain peptide assembly and/or aggregation on solid surfaces under aqueous conditions. On the other hand, all-atom simulations could, in principle, provide a helpful point of comparison. Such simulations of multichain peptide−surface adsorption remain challenging in terms of implementing advanced conformational sampling, such that these too require substantive verification against experimentally generated findings. Another variation on all-atom traditional force fields that has supported a growth in usage involves the exploration of reactive all-atom force fields such as Reax-FF,160 for example, as applied to complex dynamic deprotonation phenomena at hydroxylated titania interfaces. 161,162 Such force fields are relatively immature, particularly when compared with the established (yet still evolving, vide infra) biomolecular force fields such as CHARMM163,164 and AMBER.165 Developments in reactive force fields offer an interesting strategy for addressing phenomena such as surface hydroxyl deprotonation, but these force fields also require further and substantial testing prior to assuming a wider adoption into mainstream molecularsimulation approaches. In summary, a key point is that the generation, validation, and refinement of force fields for the aqueous biointerface should be viewed as a continuous, ongoing process rather than a definitively completed activity, and partnership with advances in experimental techniques is a critical aspect of advancing these developments. To this end, as part of this validation and benchmarking process, several previous studies have quantified the binding strength (interaction energy or, preferably, the genuine adsorption free energy) of amino acids (or their analogues) adsorbed at aqueous materials interfaces, for substrates including Au, Ag, graphene, quartz, and various crystallographic orientations of TiO2.77,166−180 Most of these data were determined for planar flat substrates, although recently amino acid binding free energies have been reported for both Au180 and TiO2179 nanoparticles in solution. As explained earlier, the key questions of peptide/materials recognition cannot be addressed solely by a description of peptide−surface binding in terms of an additive sum of individual residue−surface interactions. This is due to the complex and nonintuitive interplay between the peptide sequence, the three-dimensional

structure(s) adopted by this peptide, and the binding and properties of the resultant biointerface. That fact notwithstanding, amino acid binding propensities provide useful information but not necessarily decisive and thoroughly conclusive input for elucidating, in part, the structure/property relationships of complex peptide/materials interfaces. In addition to their utility as a stepping-stone to improved force fields, these amino acid binding data also provide a benchmark against which sequence context effects can be interpreted. For example, amino acid binding data can be used to gauge the up or down modulation of a particular residue binding strength to the surface, due to, for example, the character of the flanking residues in the sequence.85 These context-based insights could aid the future inference of peptide-binding propensities, such as those that could be generated from informatics approaches, to ultimately reverse-engineer sequences with predictable properties. The ability to reasonably describe the interactions between the peptide and nanomaterials under aqueous conditions has evolved considerably in the past decade, and these developments have been foundational in fueling advances in our detailed understanding of the abiotic/biotic interface. Peptide/ Au interfaces have been a strong focus of these force-field developments. In 2008, Corni and co-workers pioneered the GolP force field to describe biomolecule adsorption at the Au(111) interface.181,182 The GolP model had several appealing features: it incorporated surface polarization effects in a computationally tractable manner and correctly ensured that atop adsorption sites were favored. However, in its original form, it was limited to description of the Au(111) surface only and could not capture dynamic Au surfaces (e.g., arising from mobile surface adatoms). In the same year, Heinz and coworkers published a generalized force field, CHARMMMETAL,183 for modeling the interactions of peptides with aqueous metal interfaces, including Au, Ag, Pd, and Pt, and it was subsequently incorporated into the INTERFACE force field.184 In its most widely used implementation applied to noble metal surfaces, this force field is based solely on LennardJones interfacial interactions. Therefore, the relatively simplified nature and implementation of the CHARMM-METAL force field also holds advantages, particularly when applied to dynamic, or disordered, metal interfaces. Walsh, Corni, and co-workers subsequently devised the GolP-CHARMM force field, which extended its applicability to an accurate, polarized description of the aqueous Au(111), Au(100)(1 × 1), and Au(100)(5 × 1) interfaces (Figure 13).185,186 In addition, the GolP-CHARMM parametrization strategy has since been analogously extended to the Ag(111), Ag(100), and graphene aqueous interfaces.187,188 In contrast to the GolP family of force fields, the simplified but versatile framework of CHARMM-METAL enables modeling of peptide adsorption on both flat metal surfaces and nanoparticle surfaces. However, this implies that all metal nanoparticle/ peptide simulations reported to date are limited by a central assumption, namely, that the simplified Lennard-Jones type representations assume that all sites on the nanoparticle surface bind adsorbates with the same strength (i.e., that all nanoparticle sites have the same Lennard-Jones well-depth parameter, ε). The basis of this assumption has been recently challenged by Hughes and Walsh,189 where first-principles calculations have suggested that vertex and edge atomic sites on noble-metal nanoparticles bind heteroatomic adsorbates more strongly, while hydrocarbons adsorbed best at the planar facets. This difference in binding preferences is anticipated to translate 12654


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We start with those studies based on standard MD approaches, the bulk of which comprise the earlier studies in this area. Despite improvements in the reliability of the interfacial force fields used in these studies, many (but certainly not all) of the simulation studies arising from these force fields dedicated to studying adsorption of non-naturally occurring (i.e., biocombinatorially selected or designed) materials-binding peptides still relied (and, in some instances, continue to rely) on relatively primitive conformational sampling strategies.72,75,117,137,173,197,205−224 This caveat places limitations on the interpretations of these simulations, particularly if seeking unbiased comparisons with experimental observations of biointerfacial properties. This is particularly problematic for elucidating unambiguous and/or definitive structure/property relationships of the biointerfaces from these studies, because the structures predicted from such relatively simple sampling approaches are likely not to be free from the influence of the simulation initial conditions (even if several different initial conditions were explored). Despite these caveats, these studies have provided enormous value; collectively they have revealed a number of key features of the biointerface that have shaped our current views in this research area, including the importance of interfacial solvent structuring to the peptide-binding event,137,168,225 the influence of the conformational ensemble (in some earlier studies this was somewhat misleadingly referred to as peptide “flexibility”,117,205,212 vide infra), and, of particular note, the first steps exploring composition-dependent and/or facet-dependent binding selectivity.213,214 These findings are of high value because they have provoked (and continue to prompt) further advances in this field. However, many of the more recent simulation studies of the peptide−materials biointerface involve the use of advanced conformational sampling.2,35,66,73,77,84−86,96,175,177,220,225−249 That said, we reiterate here that the use of advanced conformational sampling is a necessary, but not sufficient, factor in making physically reasonable predictions of abiotic/ biotic interfacial interactions; the influences of the interfacial force field and the structural model of the substrate can also exert a critical influence on the simulation outcomes. For example, Sahai and co-workers reported the use of advanced conformational sampling (using parallel tempering metadynamics) to predict the adsorption free energies and structures of the aqueous peptide/hydroxyapatite (HAP) interface.244 However, as indicated by the recent work of Heinz and coworkers,197 the simulations of Sahai and co-workers used a structural model for HAP that corresponds with extremely basic solution conditions (pH ≈ 14) that is not appropriate for comparison with experimental data obtained under more pHneutral conditions, regardless of the robustness of their conformational sampling strategy. Another illustrative example is the work of Grasso et al., who also applied advanced sampling to investigate peptide adsorption at magnetite interfaces.238 However, their substrate model was based on a simple general clay force field, which was unverified for application to iron oxide materials in general and, crucially, neglected key strongcorrelation electronic phenomena in magnetite. Unfortunately, the inclusion of these strongly correlated effects is essential to capturing unique molecule−surface interaction effects compared with nonferrimagnetic iron oxides (e.g., hematite) and is critical for a range of metal oxide materials, such as Cu2O and NiO. Regrettably, it is therefore unlikely that the outcomes from this study can be used to infer significant information regarding peptide adsorption on magnetite. Moreover, to date,

Figure 13. Au(100)(5 × 1) surface after relaxation using vdW-DF viewed (left) from above and (right) from the side. For the plan view (left), surface-layer Au atoms are depicted as largest and medium gold in color, second-layer Au atoms are dark gold and medium size, and the third layer of Au atoms are the smallest size and light gold in color. Adapted with permission from ref 185. Copyright 2013 American Chemical Society.

into aqueous conditions; this is expected to affect the degree of solvent structuring around the nanoparticle, which will also influence how peptides interact with nanoparticle surfaces in solution. However, further work is required to explore this situation in more depth, and the corresponding experimental data required to confirm or refute this assumption are currently not available. The limitations of this assumption are expected to be particularly acute for simulation studies based on faceted nanoparticles.180 Development of new models to capture these phenomena should be a future priority. The utility and relevance of findings from simulations of the biointerface progressed substantially with the publication of several all-atom interfacial force fields in the years since 2008, designed for modeling noncovalent interactions between biomolecules and different materials,137,181−188,190−198 which were also sufficiently computationally economical to use in partnership with a representation of explicit solvation. Of note is the fact that several choices are available for “designed” force fields for describing the aqueous peptide−materials interface for noble metals,181−183,185,186,188 titania,137,196,199 and silica.190,191,193,198 We emphasize the distinction between data obtained using these particular “designed” force fields, as opposed to those data derived from simulation studies that have made use of unverified interatomic potentials typically provided by default by turnkey commercial software packages. The latter situation will not be discussed here and should be viewed with caution. In contrast, designed interfacial force fields are usually harmonized with commonly used and relatively mature biomolecular interatomic potentials, e.g., the CHARMM family of force fields.163 Herein, in discussing previous peptide−materials simulation studies, we make the distinction between studies that did not make use of advanced conformational sampling (vide infra), defined here by the use of standard MD simulations, and those that have implemented genuine advanced sampling strategies using atomistic force fields, defined here by the use of, for example, steered MD, adaptive biasing force MD,200 paralleltempering MD (which is very similar, but more general, compared with replica-exchange MD),201and replica-exchangebased MD simulations.202 The latter two approaches have also been combined with metadynamics simulation approaches,203 particularly well-tempered metadynamics.204 12655


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Figure 14. Snapshots depicting the side view (top) and view from above (bottom) of AuBP1 adsorbed at the aqueous (a) Au(111), (b) Au(100)(1 × 1), and (c) Au(100)(5 × 1) interfaces. Atoms shown are gold in yellow, hydrogen in white, oxygen in red, nitrogen in blue, and carbon in cyan. Water molecules were omitted for clarity in the plan view images. Reprinted with permission from ref 248. Copyright 2015 Royal Society of Chemistry.

the generation of physically reasonable biointerface force fields for strongly correlated substrates such as magnetite, Cu2O, NiO, etc. remain as an unresolved challenge. The first advanced sampling strategies proposed for the biointerface were reported by Latour and co-workers and focused on the fundamental case of atomic ion adsorption at an aqueous SAM interface.227 This was consolidated shortly afterward with a landmark study226 that combined temperature-based replica exchange molecular dynamics (REMD) simulations with bias-exchange MD, to predict the adsorption properties of an nonapeptide (9-mer) host−guest peptide adsorbed at an aqueous polylactide crystal interface. This not only provided unprecedented structural insights into this peptide adsorbed at the interface but also enabled an estimate of the peptide-binding free energy, calculated via a probability ratio approach. The first REMD study of biocombinatorially selected materials-binding peptides220 focused on three silicabinding peptides, two strongly binding peptides and one weakly binding peptide, and identified conformational rigidity as a key factor in facilitating strong contact with quartz. This work was unique in the way it combined bioinformatics predictions52,217 of enriched binding motifs with the residue-surface contact analysis provided by the simulations. Advanced sampling strategies are helpful for determining the structure/function relationships of the peptide−materials interface, and these approaches can also provide value in aiding the evolution and improvement of the interfacial force fields used in these simulations. For example, Latour and co-workers made careful use of advanced sampling strategies and complementary experimental binding data to refine all-atom force fields, particularly for the silica interface.193 REMD simulations were also used to investigate the experimentally identified goldbinding peptides AuBP1 and AuBP2 adsorbed at the aqueous Au interface.96 These authors identified IDP-like traits of these peptides that were suggested to give rise to their strong affinity for the Au surface. As identified in these pioneering works summarized above, the rigorous and appropriate application of REMD (i.e., using a sufficient number of replicas over a wide-enough temperature

range) to a given aqueous biointerface was computationally expensive to implement, verging on the impracticable. The introduction of Hamiltonian-based replica-exchange approaches250−252 has transformed the practical viability of this strategy, enabling comprehensive sampling of the adsorbed peptide conformational ensemble. The replica exchange with solute tempering MD (REST-MD) approach was shown to be a powerful technique to predict the complex peptide conformational ensemble to a similar standard as REMD, but in a much more computationally economical manner,246 and can be even further enhanced via combination with metadynamics approaches to enable useful predictions of adsorption free energies (as opposed to the more limited “interaction energy” approaches, vide infra). Of particular note, Schneider and Colombi Ciacchi first combined REST with well-tempered metadynamics simulations to recover, compare, and explain adsorption free energy differences of a hexapeptide (originating from phage-display experiments) at both amorphous titania and silica interfaces.225 Recently, Wright et al. also demonstrated the power of this combined approach to predict the binding free energy of a gold-binding peptide (AuBP1) at several different aqueous facets of Au and recovered the experimentally determined binding free energy of this peptide adsorbed at the polycrystalline Au interface.248 The economic advantages of the REST-MD approach, and similar approaches such as those based on parallel tempering, have been pivotal to establishing clearer connections between structure and function for a range of interfaces, including Au,2,35,66,77,84−86,248 Ag,77,84,249 silica,225,236,237,246 graphene,177 and titania.73,225 REST-MD simulations using the GolP suite of force fields have been used to investigate the molecule-scale origins of peptide− materials selectivity, namely, the preferential adsorption of peptide sequences for one material over another.84,77 As mentioned earlier, alternative strategies for realizing enhanced conformational sampling are applicable to biointerfaces such as parallel-tempering MD simulations, steered MD simulations, and umbrella sampling. Advanced sampling simulations, specifically those that have also incorporated metadynamics approaches, have therefore been demonstrated 12656


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Figure 15. Three-dimensional iso-valued free energy surfaces (3D-FEH) as a function of collective variables showing the shape of the free energy landscape of the alanine dipeptide at the gold/water interface. The equivalent absolute minima at the opposite values of CV1 can be observed in dark blue; they are symmetric with respect to the mean value of CV1 (O). The local minima of the energy landscape in the vicinity of the surfaces are shown in blue−green. The isosurface at higher energies is shown in yellow. A series of “channels” connecting the equivalent free energy basins can be observed in the central region of the 3D-FEH. The intersections between channels and the x−y plane at the mean value of CV1 are highlighted in black. Reprinted with permission from ref 235. Copyright 2014 American Chemical Society.

Figure 16. (a) Trajectory-averaged fluctuations of the vertical surface−residue distance for a typical binding configuration (“Surface”). “Fixed water” indicates binding via a fixed water bilayer with the titania slab removed from the simulation cell. “Bulk water” shows the average fluctuations in a bulk solution (no surface present). “COM” indicates the fluctuation in the distance from the surface to the center of mass of the peptide. (b) Typical profiles of the surface−residue distance for a remodeling event. Reprinted with permission from ref 137. Copyright 2009 American Chemical Society.

binding, several earlier simulation studies sought explanations for the pioneering experimental data of Willett and coworkers,116 via the prediction of homopeptide binding at aqueous Au interfaces. However, in summarizing the findings from these homopeptide-simulation studies, this overview must be tempered by an appreciation of the limitations of these simulations, chiefly due to their structural models (which did not take relevant Au surface reconstructions into account), the inaccurate approaches used to calculate peptide−surface “interaction energies” (see article by Corni and co-workers96 for clear exposition on the origin of these inaccuracies), and, crucially, their extremely limited conformational sampling. An overarching theme of these earlier findings was the importance of so-called “peptide flexibility” in conferring strong peptide adsorption. However, earlier use of this term was unfortunately misleading; “peptide flexibility”117,205 in these earlier studies actually referred to what are now known as IDP structural traits, i.e., structural disorder. Therefore, in these studies a “flexible” peptide was chiefly defined by the absence of welldefined secondary structure (e.g., an α-helix). In other words, this definition could not encompass an IDP peptide that was

to provide reliable estimates of the peptide−materials adsorption free energy, but only in the instances where reliable interfacial force fields have been used in partnership with these techniques. However, the true power of these approaches does not lie merely in the recovery of the binding free energy per se but rather in the accompanying structural analysis from these simulations that provides a direct link between the conformational traits of the peptide in the adsorbed state and the adsorption free energy. For example, Wright et al.248 reported the structural differences in a Au-binding sequence, AuBP1, at three different facets of the aqueous Au interface (see Figure 14) and used their structural data to explain these differences via their binding free energy estimations obtained from REST +metadynamics simulations. Technical advances aside, herein we summarize the scientific progress that has been made in elucidating structure function relationships of the peptide−materials interface for a range of exemplar substrates. For instance, the aqueous peptide/Au interface is arguably one of the most intensively studied by molecular simulation, due to its importance in a wide range of disciplines.253 In addition to revisiting 3R-GBP1 peptide 12657


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both lacking in secondary structure and conformationally rigid. Not surprisingly, this “flexibility” hypothesis was found to not be universally applicable.117 In later years, the development of advanced conformational sampling approaches that could better identify structural disorder led to the expansion and clarification of our understanding of how both entropic and enthalpic factors can influence peptide-binding affinities (see section 2.5). The importance of targeted conformational sampling strategies for peptides adsorbed at the aqueous Au interface was underscored by the work of Bellucci and Corni,235 who showed that even a simple dipeptide can result in a complex adsorption free energy landscape, as illustrated in Figure 15. The aqueous peptide/TiO 2 interface has also been intensively investigated using molecular simulation, particularly for adsorption at the rutile (110) surface plane. The availability of high-quality experimental data regarding the interfacial solvent structuring at the rutile TiO2 (110) interface was pivotal to helping simulations elucidate a central concept in explaining peptide/surface binding, namely, that the peptide may also recognize the spatial and orientational ordering of the solvent in the near-interface region,137,225 in addition to recognizing the lateral arrangement of surface atoms in the material itself. For example, Skelton et al. 137 probed this by performing simulations of the peptide adsorbed to an aqueous TiO2 (110) interface, where the first two solvation layers were held fixed in space, and compared these data with the case where all atoms were free to move. The degree of peptide stability (illustrated in Figure 16) between simulations with both “frozen” and “free” water layers was comparable, underscoring the significance of the interaction of the peptide with interfacial solvent structure rather than with the titania surface per se. Several reports have documented the calculation of peptide adsorption free energy at aqueous titania interfaces,73,225 finding good agreement with experimental data (including those reported for the single-crystal (110) interface), involving QCM measurements73 and AFM force spectroscopy.254,255 The influence of different interfacial coadsorbed cations in solution, such as Ca2+, have been investigated in detail for short tripeptides in the work of Skelton and co-workers,206−208 indicating that divalent ions can play a critical role in bridging the favorable interactions between acidic residue side chains (Asp and Glu) with the titania surface. The influence of surface planes other than the widely studied (110) surface and their impact on peptide adsorption were also reported by Friedrichs et al.,216 who studied adsorption of two Ti-binding dodecapeptides identified from phage-display experiments.256 However, we note that neither of these two sets of studies made use of advanced conformational sampling in their simulations. While the use of flat, planar interfaces has been a central theme of many previously reported modeling studies of materials-binding peptides, several contributions have focused on peptide adsorption to nonidealized surfaces, including steps, grooves, and notches on flat surfaces,209,216,257 and, crucially, the aqueous nanoparticle interface.2,62,211,214,218,219,223,224 These studies also include the investigation of how peptide adsorption is affected by interfacial curvature.218,219 Notably, some of the more recent studies of peptide/nanomaterial interactions involved the consideration of more than one peptide chain adsorbed at the aqueous nanoparticle interface.2,62,223 Recently, multichain simulations have been reported to explore peptide-coverage effects on peptide−materials adsorption for revealing and elucidating structure/property

relationships of catalytically active nanoparticles in aqueous media, comprising Pt and Pd62,214,223 and Au.2 Of particular note is the recent work of Bedford et al.,2 where advanced conformational sampling (REST-MD simulation) was used to predict the structural ensemble for a range of Au nanoparticleadsorbed multipeptide overlayers under aqueous conditions. This is the first known instance of advanced sampling simulations applied to multipeptide adsorption at an aqueous nanoparticle interface. This structural ensemble was consequently used to explain variations in catalytic activity of these nanoparticles, as well as the comprehensive overview of the traits of an ideal peptide sequence to realize enhanced catalytic properties. By comparison, multiadsorbate simulation studies of amino acids have figured less prominently; these have been used to explore hypotheses of amino-acid-mediated nanoparticle assembly (using standard MD simulations of multiamino acid adsorption at flat interfaces).258 In summary, while the advances made in this particular area of multiadsorbate binding at nanomaterial biointerfaces are promising, considerable further progress on elucidating structure/property relationships is required for the future. The generation of new force fields designed specifically for nanoparticle substrate environments and the implementation of advanced sampling strategies are both essential for realizing these advances. Extension to the modeling of biointerfaces that incorporate nonpeptide elements opens new directions for predicting structure/function relationships that extend beyond catalysis. For example, Briggs et al.84 reported modeling (including advanced conformational sampling) of a bifunctional molecule, denoted as a PARE (peptide assembling and responsive element), containing a Ag-binding domain at one end, a Aubinding domain at the opposite end, and an azobenzenecontaining linker positioned between these two domains. These authors used the PARE to grow and organize Au and Ag nanoparticles in solution, as discussed later. Metadynamics simulations and REST simulations predicted that the azobenzene linker adsorbed strongly at the aqueous metallic interfaces and, along with data from standard MD simulations of the PARE-mediated nanoparticle dimer in solution, suggested reasons for the metastability of PARE-mediated assemblies of Ag and Au nanoparticles. Incorporation of azo moieties into peptides was also studied by Slocik et al.234 Optical properties and surface-binding properties of these hybrids were investigated for an azobenzene-containing peptide adsorbed at the aqueous Au interface and included modeling studies using steered MD to determine the binding strength of these hybrids at the Au surface. These promising developments indicate an emerging new research direction, with bright prospects for predicting the structure and properties of other hybrids between peptides and functional elements from nonpeptide molecules (such as DNA/RNA, lipids, carbohydrates) and molecular switches. In summary, the area of molecular simulation of peptide− materials interfaces has shown substantial growth, particularly over the past decade. The insights and explanations yielded to date have provided much-needed guidance, principally in the interpretation of experimental data. Simulations of interfaces incorporating noble metals, titania, silica, and graphene are the most developed to date. For other substrates and materials beyond this, the development of new force fields is required. Going further, the development of force fields that are specifically designed for nanoparticle interfaces are also essential. More ambitiously, expansion of the current successes 12658


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in modeling peptide/nanoparticle interfaces to functional oxide materials, including strongly correlated oxides, and oxides of complex, energy-relevant multimetal materials, such as and FeNi or FeCo, is a highly aspirational but key target for future efforts. Another avenue that remains relatively unexplored is the modeling of peptide interactions with conducting polymer materials,259 such as those based on poly(3,4-ethylenedioxythiophene) (PEDOT), relevant to applications in bionics and nerve regeneration. One of the key obstacles in realizing this goal is the construction of physically reasonable structural models of this complex substrate. Simulations of multifunctional/multidomain peptides, including bifunctional peptides and hybrid peptide/nonpeptide molecules, are in a stage of relative infancy and should assume a stronger focus from the molecular simulation community in the future. The evidence for this need is clear; sections 4 and 6 provided herein articulate the strong demand for high-quality simulations of bifunctional peptides as relevant to both energy materials and biomedical applications. Finally, future advancements that combine informatics52,260,261 approaches with molecular simulation outcomes and experimental data comprise another essential direction, which promises the means to escalate beyond pure elucidation and move toward realizing truly predictive capabilities. Progress in this area is currently impeded by sparse data sets, chiefly those which combine experimental and modeling data, indicating that closer integration of experimental and molecular simulation findings, obtained for a broader set of substrate materials than those currently available, will be an essential foundation for enlarging these data sets. For example, the Au substrate is the most advanced in terms of the number of matched data points between high-quality experimentally determined binding affinities (e.g., from QCM or SPR measurements) and outcomes from advanced MD simulations (e.g., from REST-MD simulations), with almost 20 peptide sequences currently meeting this data-matching criterion.35,85,86 Regarding other substrates, only Ag and titania are associated with similarly matched data sets of comparable quality, but with a relatively smaller number of peptide sequences (two each for titania73 and Ag77). A combined experiment/modeling/informatics approach may ultimately provide the fundamental basis for reverse-engineering peptide sequences for the on-demand creation of functional biointerfacial materials.

affinity is thought to be largely due to strong enthalpic contacts, mediated by anchor residues (residues that show a high degree of residue−surface contact in the surface-adsorbed peptide). Alternatively, a strong peptide−surface binding affinity can also arise from conformational entropy considerations, where the peptide can bind with high affinity to the surface by assuming many different surface-adsorbed conformational states. In this instance, the residues may not necessarily have strong contact with the surface. The authors denoted such peptides as “entropic binders”. In summary, this study highlighted that a strong peptide−surface binding affinity can be achieved via conformational entropic contributions, in addition to the more widely perceived enthalpic mode, resulting in strong engagement with the surface via anchor residues alone. This analysis of the peptide conformational contribution to peptide−surface binding was quantified using the discrete entropy as a metric in subsequent studies, such that entropic binders are associated with a high discrete entropy score. Recently, this analysis was used to identify peptide sequences that have a high propensity to act as poor surface-capping agents for Au nanoparticle dispersions in solution, as indicated by a high discrete entropy score.35 Enthalpic binder analysis has also been used to reveal links between peptide structure and properties. As reported by Bedford et al.,2 the catalytic activity of peptide-capped Au nanoparticles was found to be directly related to the number of strong anchor residues. Sequences characterized as enthalpic binders, i.e., those with a high number of anchor residues, exhibited high activation energies for a prototypical surface-catalyzed reaction (reduction of 4nitrophenol). However, very recent evidence suggests an upper limit to this benefit: too high a contribution in terms of conformational entropy was indicated in a subsequent study35 to be detrimental to nanoparticle stability in aqueous media and was used to identify and explain cases where a given peptide sequence may not be capable of acting as a dispersing agent for Au nanoparticles in solution. In summary, the classification of peptide sequences as enthalpic or entropic binders has helped to bridge the connection between structure and function at the abiotic/biotic interface. Nonetheless, this framework should be considered as an evolving concept, awaiting further refinement as prompted by future experimental advances.

3. NANOPARTICLE ASSEMBLY The ability to drive the assembly of nanoparticles in three dimensions over extended length scales is required to advance applications in catalysis, optics, plasmonics, energy harvesting and storage, etc. While different approaches have been explored,69,70,76,91,262−277 peptide- and virus capsid-driven approaches exploiting materials-directing peptides have demonstrated unique success for the controlled orientation of inorganic materials. Additional methods, which are not discussed here, exploit the complementarity of DNA strands to control the intricate positioning of nanoparticles in threedimensional arrays273−275,277,278 and surface-templated methods.91,271,272 Peptide- and protein-driven approaches provide complementary methods to achieve unique structures that may be difficult to access via different approaches. Many of these methods rely on both the interactions between the inorganic material and biomolecule (i.e., the biointerface) and peptide− peptide interactions (both on a single-particle surface and between two separate particles) to generate the overall assembly of inorganic materials.

2.5. Thermodynamic Basis of Peptide/Nanoparticle Interactions

Recently, it has been possible to harness both experimental advances and progress in advanced molecular-simulation approaches to produce a wide overview of the structure and binding of materials-binding peptides adsorbed at the aqueous Au interface.85 This analysis, as discussed earlier, considered 12 different peptide sequences, of which many had been either biocombinatorially selected or designed to recognize the Au surfaces. This set of peptides also included sequences that were selected for binding to substrates other than Au, such as quartz and Ag. The binding free energies inferred from QCM experiments together with the structural analysis derived from the advanced molecular simulations jointly provided a comparison of peptide binding on an equal footing. This data set enabled the authors to propose a framework for connecting structural characteristics of the adsorbed peptide with the binding affinity of the sequences. In this framework, enthalpic binders are classified as peptide sequences where binding 12659


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Figure 17. Au nanoparticle double helices generated with the C12-A3 conjugate in an aqueous HEPES buffer solution. Reprinted with permission from ref 83. Copyright 2008 American Chemical Society.

Figure 18. (a, b) Tomographic analysis of the Au nanoparticle double helices produced by the C12-A3 conjugate. (c) Scheme of the assembly process. Reprinted with permission from ref 83. Copyright 2008 American Chemical Society.

3.1. Peptide Amphiphile-Driven Nanoparticle Assembly

nesulfonic acid (HEPES) buffer, the formation of left-handed helical fibers was observed, which was confirmed by staining TEM and AFM imaging.83 These unique biomimetic fibers were quite narrow with a diameter of 6.1 ± 0.6 nm; however, they could extend over substantial lengths of >4 μm. This amphiphilic structure used the hydrophobic interactions of the C12 chain at the core of the helix to maintain the assembled conformation. In this arrangement, this displayed the A3 peptide to solution, thus presenting opportunities to guide nanoparticle assembly via the binding of the peptide to Au materials, forming the biointerface. When the C12-A3 conjugate molecule was commixed with HAuCl4 in HEPES buffer, the formation of helically assembled Au nanoparticles was evident.83 No additional reductant was required as both the tyrosine of the peptide and the HEPES

Researchers have exploited the ability of peptides to recognize and bind inorganic nanoparticles to drive their assembly in solution. One specific elegant method,81,83,279−288 developed by Rosi and co-workers, has focused on the use of peptide amphiphiles to advance this approach. In this regard, the researchers employed the A3 peptide, identified by Naik and colleagues25,42 with the ability to bind both Au and Ag, to control the assembly process. In the original study, the Nterminus of the peptide was modified with dodecanoic acid (C12) to generate the C12-A3 amphiphilic peptide.83 Note that the authors refer to this as C12-PEPAu in the original work. The C12 chain was added with the anticipation that it would drive biomolecular assembly in water. When the C12-A3 peptide was dissolved in an aqueous 4-(2-hydroxyethyl)-1-piperazineetha12660


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buffer itself are known to drive the reduction of Au3+ to Au0 for nanoparticle formation.289−291 Figure 17 presents TEM images of the Au nanoparticle double helices, which were rapidly formed in solution.83 The Au nanoparticles were nearly monodisperse with an average particle size of 8.2 ± 1.0 nm. Electron tomographic analysis of the helical materials was also conducted, from which image reconstruction was used to generate the tomogram of the 3D structure (Figure 18).83 Of note, when comparing helix formation in the presence and absence of Au3+, enhanced helix formation was observed with the metal ions in solution, suggesting that the assembly process was enhanced by the Au3+. Additional modifications to the aliphatic tail (i.e., using a C14 chain instead of a C12 or preparation of dendritic-like biomolecules) have recently been demonstrated that result in fine control over the structure of the final assembly of materials.280,283 For peptide helix formation, Rosi and co-workers modified the N-terminus of the biomolecule with a hydrophobic C12 chain; however, the A3 peptide presents a hydrophobic phenylalanine (Phe) residue at the C-terminus that could also alter the global helix structure. To identify such effects, Zhang et al. modified the C12-A3 biomolecule at the peptide domain in four specific ways: (1) removing the terminal Phe, (2) maintaining the Phe (parent sequence), (3) adding an additional Phe residue, and (4) adding two additional Phe residues.282 This would efficiently probe the effect of Cterminal hydrophobicity on helix formation. While removal of the terminal Phe residue (condition 1) did not prevent biomolecular assembly, it did require longer times and resulted in the formation of a fiber instead of a helix; however, when either one or two additional Phe residues were incorporated (conditions 3 and 4), thicker and branched Au nanoparticle assemblies (conditions 3) and bundling of multiple nanoparticle assemblies (condition 4) were observed.282 As such, regardless of the peptide modification, the binding of the A3 peptide to the Au surface remained sufficiently strong enough to lead to assembly and biointerface formation; however, these results do demonstrate that the materials-binding peptide also plays a significant role in assembly formation and structural determination. While this approach provides exquisite control over the formation of 3D helical linear assemblies, additional solution processing can be used to control the size, conformation, and interparticle spacing of the Au materials along the helical construct.81,279 For instance, the number and density of Au nanoparticles integrated onto the helical template increased as the reaction time increased from 30 min to several months.81 In fact, at the longest time studied (i.e., months), the helical template was completely coated in Au materials to form a continuous 1D metallic structure. To control nanoparticle size and interparticle spacing, citrate and adenosine triphosphate (ATP) were added to the assembly solution.81 The researchers chose these two molecules as they are known to adsorb onto Au nanoparticle surfaces and were anticipated to be stronger binders than HEPES. Note that HEPES is likely adsorbed onto the Au nanoparticles at regions not directly interacting with the A3 peptide at the biointerface. Interestingly, these two negatively charged molecules significantly changed both the particle size and the interparticle spacing (Figure 19). For instance, when the helical nanoparticle assemblies were generated without citrate or ATP, nanoparticles of 8.1 ± 1.0 nm were generated with a spacing of 6.1 ± 0.4 nm between two particles on opposing sides of the double helix. When citrate

Figure 19. TEM analysis of the Au nanoparticle double helices formed using the C12-A3 peptide conjugate using standard methods in the presence of (a) citrate, (b) HEPES only, and (c) ATP. Reprinted with permission from ref 81. Copyright 2010 American Chemical Society.

was added to the reaction mixture, the particle size decreased to 6.2 ± 0.8 nm, while the interparticle distance increased to 10.7 ± 1.1 nm. Interestingly, when ATP was employed during helical-based assembly, the particle size also decreased as compared to the standard synthesis (5.4 ± 0.8 nm); however, the interparticle spacing across two helices remained roughly the same at 5.9 ± 0.5 nm.81 This suggests that both the particle size and the interhelical distances can be directly controlled by solution-processing conditions where additional factors beyond the secondary reagent charge play an important role in controlling such dimensional features. While solution conditions can be used to tune nanoparticle assembly using the C12-A3 helix, the actual organically modified biomolecule can also be used to modify the assembly morphology. To this end, Hwang et al. replaced the C12 chain with a biphenyl molecule to generate BP-A3 (biphenyl conjugated to the A3 peptide).279 Biphenyl was specifically selected to aid in peptide assembly via π-stacking interactions. Unfortunately, this compound did not self-assemble in solution; thus, the researchers incorporated an additional AYSS motif into the N-terminal region of the peptide to generate the BP-AYSS-A3 molecule. The additional AYSS region was reasoned to facilitate biomolecule assembly as it was previously suggested to aid in peptide assembly using the C12A3.83 Using the BP-AYSS-A3 molecule, rapid assembly was evident to produce nonhelical nanofibers in solution. These fibers were subsequently employed to template the assembly of Au nanoparticles in solution due to the exposed A3 binding domain at the fiber surface. Using the BP-AYSS-A3 fiber, a twostep process was required for Au nanoparticle assembly (i.e., nanofiber formation first, followed by Au nanoparticle incorporation),279 which contrasted with the C12-A3 assembly where helix formation was facilitate by nanoparticle production. Using the BP-AYSS-A3 fibers, linear nanoparticle assembly was observed; however, the localized order of the individual particles on the biointerface was not as well ordered as observed using the C12-A3 helices. Interestingly, when the fibers were examined after 6 days, multiple fiber bundles were observed,279 suggesting even larger Au nanoparticle superstructures may be possible using the BP-AYSS-A3 template. 12661


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that are consistent with their double-helical counterparts.280 Single-helical assemblies were generated using a template that conjugated two A3 peptides to a single C18 carbon chain. This results in a divalent peptide species, which was shown to form double-helical Au nanoparticle assemblies;283 however, oxidation of the thioether side chain of the methionine residue to a sulfoxide resulted in the formation of single-helix Au nanoparticle assemblies.280 Such results confirm that peptide-based assemblies provide unique handles to achieve difficult-to-access optical capabilities. To drive the assembly of the A3 peptide into double helices, a C12 chain was required. To explore the effects of the aliphatic chain, Song et al. generated multiple peptide conjugates with various chain lengths of C6, C8, and C10.287 While the C10-A3 conjugate generated 1D Au nanoparticle assemblies under the standard synthetic conditions, those with smaller chains typically produced individual nanoparticles or small aggregates of Au particles. This demonstrated that the chain length was critically important in controlling the final assembled structures. While the C6-A3 conjugate did not generate assembled materials, the researchers incorporated two additional alanine (Ala) residues between the C6 aliphatic chain and the peptide to induce biomolecular assembly.287 The two Ala residues provided additional hydrophobicity within the biological domain, which did indeed aid in peptide-assembly formation. Using the C6-AA-A3 peptide, the formation of spherical biomolecular assemblies occurred in water, resulting in structures with an overall dimension of 136.5 ± 2.5 nm.287 Interestingly, when the same process was done in HEPES buffer that is typically used for Au reduction in the assembly studies, no spherical superstructures were formed. The C6-AA-A3 conjugate was subsequently employed to controllably assemble Au nanoparticles via binding of the solvent-exposed A3 to the Au via biointerface formation.287 For this, the peptide was incubated with HAuCl4 in HEPES buffer for 24 h, which resulted in nanoparticle formation. Upon imaging of the materials using TEM, the formation of spherical Au nanoparticle superstructures was evident (Figure 22).287 On the basis of the images, it was clear that the superstructure was hollow, composed of the biomolecular template at the interior with the Au nanoparticles on the exterior. Such effects were confirmed by tomography analysis (Figure 22). The Au

These one-dimensional assemblies provide a unique platform for organizing optically important materials, Au nanoparticles, in specific arrangements that could present unique chiroptical properties. Such effects were originally studied by Song et al. using both right- and left-handed nanoparticle helices.281 While the left-handed double helices are formed with the standard C12-A3 motif prepared using L-amino acids (C12-L-A3), switching of the chirality of the peptide using D-amino acids resulted in right-handed double helices (C12-D-A3). Nearly identical double-helical nanoparticle assemblies were generated using the C12-D-A3 construct as compared to the C12-L-A3 (Figure 20), thus allowing for easy comparison of the

Figure 20. Comparison of left- and right-handed helices formed with the (a−c) C12-L-A3 and (d−f) C12-D-A3 bioconjugates, respectively. Scale bars: (a, d) 200 nm (b, e) and 20 nm. Reprinted with permission from ref 281. Copyright 2013 American Chemical Society.

chiroptical properties of the two different arrangements. Experimental CD analysis of the two materials (Figure 21) demonstrated mirrored chiroptical properties that matched theoretical predictions.281 More recent results using nanoparticle single helices (generated using a modified A3 selfassembling template) also demonstrated chiroptical properties

Figure 21. (a) Experimental and (b) theoretical CD analysis of the left- and right-handed helices. For both parts, the red plot represents the righthanded helix, while the blue plot represents the left-handed helix. Reprinted with permission from ref 281. Copyright 2013 American Chemical Society. 12662


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3.2. Multidomain Peptide-Driven Assembly

Using the amphiphilic peptides above, assembly was achieved due to the hydrophobic/hydrophilic domains working in concert with the binding of the inorganic material. In a separate method, researchers have explored the use of multidomain materials-binding peptides to drive inorganic material assembly,19,67,84,292 paying particular attention to the use of multiple biointerfaces to achieve assembly. In this regard, one domain is exploited to bind one material, while the second domain binds to a second material of a different composition. Note that, by combining multiple materials-binding peptides into a single sequence, altered target affinity of the individual domains may occur. As such, it is important to quantify the affinity of the overall chimeric construct to identify any effects on binding affinity. This approach provides the unique capability of driving material assembly of multiple different compositions of inorganic structures simultaneously that can be challenging to achieve using ligands that are not specific to individual material composition. The use of bifunctional peptides was demonstrated by Naik and colleagues for the generation of regiospecifically assembled Au nanoparticles on graphene.67 In this regard, the researchers used two specific peptides: a graphite-binding peptide (GBP: EPLQLKM)19 and a carbon-nanotube-binding peptide (CBP: HSSYWYAFNNKT),292 both of which were previously identified using biocombinatorial selection methods for the indicated material. In this instance, the authors of the original work used the name GBP to refer to graphite-binding peptides, which should not be confused with the gold-binding GBP peptides discussed earlier. On the basis of AFM imaging (Figure 23), the GBP sequence preferentially binds to the edges

Figure 22. Imaging of the spherical Au nanoparticle superstructures generated using C6-AA-A3. (a, b) TEM images; (c, d) tomographic reconstruction analysis. (c) Scale bar = 20 nm. Reprinted with permission from ref 287. Copyright 2010 American Chemical Society.

nanoparticles in the assembly were rather monodisperse with a size of 8.3 ± 0.2 nm, while the overall dimension of the assembled structure was 51.6 ± 0.8 nm.287 These different dimensions can be directly manipulated by changing the structure of the peptide conjugate (through the use of a biphenyl group instead of a C6 chain and the number of alanine residues added) or though judicious selection of reaction conditions.284,286 Furthermore, the composition of the inorganic shell can also be changed by varying the peptide employed and its material affinity.288 For instance, the formation of CoPt spherical nanoparticle assemblies was accomplished using the Co1−P10 peptide identified by Naik and co-workers with affinity for Co and CoPt.24 Using this peptide, an exogenous reductant was required to generate the materials as HEPES was not reactive; however, spherical nanoparticle superstructures were again generated based on the preferred assembly of the bioconjugate peptides that were magnetic.288 Such results demonstrate the broad versatility of this method that can be applied to numerous material compositions. Due to the hollow structure of the spherical Au nanoparticle assemblies, it is possible to load the interior with additional molecules for potential delivery.285 These molecules are likely constrained within the assembly at the organic core due to the nanoparticles situated at the materials-binding peptide interface, thus sequestering them for eventual release. To probe this effect, doxorubicin (DOX) was commixed with the solution during Au spherical superstructure assembly, which resulted in DOX encapsulation.285 The amount loaded was quantified and subsequently probed for release. To release the compound, the DOX-loaded Au nanoparticle superstructures were mixed in solution with proteinase K, which cleaves peptide amide bonds. In the presence of the protease, decomposition of the peptides in the superstructure occurs, thus breaking apart the assembly and leading to DOX release.285 It was observed that the drug had multiple release stages, which was likely due to the rate of enzymatic reactivity for peptide degradation. The drug was eventually rapidly released where substantial degrees of release can be achieved within 10 h.285

Figure 23. Analysis of peptide binding to graphene. (A) GBP binding analysis where preferential edge adsorption is observed. (B) CBP binding to graphene, where the formation of a biointerface on the graphene plane is observed. Note that distinctive pore formation is noted for this sample. (C) Assembly analysis for the Au nanoparticle adsorbing at graphene edges using the GBP-A3 multidomain peptide. Graphene edges are highlighted in red for clarity. (D) Preferential binding analysis of the Au nanoparticles in part (C). Reprinted with permission from ref 67. Copyright 2011 American Chemical Society. 12663


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Biomolecular-driven assembly via the PARE was processed wherein Au or Ag nanoparticles were first fabricated in the presence of the PARE in either the cis or trans conformation.84 This was subsequently followed by the production of the second nanoparticle of the opposite composition in the presence of the first nanoparticle, where the azobenzene moiety remained in the same conformation. This was processed at selected peptide/Au/Ag ratios that ranged from 1:1:1 to 1:4:4. Note that the Au/Ag ratio was set at 1:1; however, the peptide/metal ratio varied from 1:4. Using this approach, the formation of small aggregated structures was evident at lower peptide/metal ratios where mass aggregation was apparent at higher ratios (Figure 24).84 In general, only a small number of

of graphene; however, the CBP peptide prefers to adsorb along the central plane of graphene.67 This level of regioselective interactions is quite unique and difficult to achieve for conventional organic ligands without exploiting selective incorporation of defects into the graphene surface. Computational modeling demonstrated that the GBP sequence preferred edge binding based on the negatively charged glutamic acid residues interacting with the positively charged graphene edges that are terminated with hydrogen. Conversely for the CBP that presents numerous residues with aromatic side chains (i.e., tyrosine, tryptophan, and phenylalanine), these residues prefer to form π−π interactions with the plane of the graphene, leading to biointerface formation.67 On the basis of the regiospecific binding of the GBP peptide, a multidomain sequence was generated that linked it together with the Au binding A3 sequence.67 In this regard, the GBP peptide was appended to have a four glycine spacer region followed by the A3 sequence, all of which was incorporated at the C-terminus of the GBP. This new biomolecule was termed the GBP-A3 to denote the binding domains of the sequence. To direct graphene/Au nanoparticle assembly, Au nanoparticles were fabricated employing the GBP-A3 sequence using standard methods.67 In this regard, the A3 region was anticipated to interact with the Au, thus exposing the GBP domain to solution for graphene binding. When the peptidecapped Au nanoparticles were exposed to graphene, the materials preferentially assembled at the graphene edges, as shown in Figure 23C.67 Such capabilities were accessible based on the multidomain peptide sequence that controlled the binding event via the formation of multiple biointerfaces. Kim et al. have expanded the use of biointerfaces and carbon materials to form hybrid assemblies.68 For this, they were able to assemble Au nanoparticles onto carbon nanotubes via multiple points of interactions. In this regard, DNA-coated carbon nanotubes were mixed with Pt2+ ions, allowing for the metal ions to complex with the oligonucleotides on the nanotube surface. To this solution, Au nanoparticles capped with the multidomain FlgA3 peptide (DYKDDDDK-A3) were added to allow for assembly based on biointerfacial interactions. In this regard, the lysine residues on the nanoparticle surface can bind to the Pt2+ ions adsorbed onto the carbon nanotubes, cross-linking the particles to the tubes.68 This leads to extensive nanoparticle assembly, all of which was achieved via biointerfacial interactions. In a separate analysis, multidomain peptides were exploited for the assembly of Au and Ag nanoparticles.84 For this process, Briggs et al. employed two peptides with affinity for the two noble metals: AuBP139 and AgBP1,29 respectively. On the basis of QCM analyses, the AuBP1 should preferentially bind to Au over the AgBP1; thus, selective formation of multimaterial assemblies could be achieved.77,85 The synthesis of the multidomain peptide followed a simple approach where cysteine residues were incorporated at the C-terminus for the AgBP1 and the N-terminus for the AuBP1. These species were subsequently coupled to two maleimides on an azobenzene spacer unit to generate the overall biomolecule (AgBP1azobenzene-AuBP1), which was denoted as a PARE (peptide assembling and responsive element).84 In this structure, no thiol groups are available for interactions with the metal surface as they are all covalently coupled to the spacer molecule. This hybrid biomolecule was considered to be responsive to optical stimulation due to the ability of the azobenzene moiety to controllably photoswitch.

Figure 24. PARE-based Au and Ag nanoparticle-assembly analysis. The isomerization state of the PARE and the order of nanoparticle production are indicated on the left, while the peptide/Au/Ag ratio is indicated on the top that ranged from 1:1:1 to 1:4:4. Reprinted with permission from ref 84. Copyright 2016 Royal Society of Chemistry.

assemblies were observed via TEM in the presence of a great number of free nanoparticles in the system. On the basis of energy-dispersive X-ray spectroscopy (EDS) mapping analysis, the organized materials were composed of both Au and Ag nanoparticles. Conversely, small-angle X-ray scattering (SAXS) analysis of the materials in solution demonstrated minimal to no assembly, which contrasted with the TEM images that showed some degree of nanoparticle organization in the dried state.84 This suggests that sample-drying and solvent-evaporation processes are required to drive the organization of nanoparticles using the multidomain peptide where modification of the PARE unit is likely required to enhance its use for nanoparticle assembly via biointerface formation. 3.3. Peptide-Modified Bolaamphiphilic Nanotubes for Nanoparticle Assembly

Additional material assembly has been achieved through the use of peptide-modified bolaamphiphile tubules that are generated using a peptidomimetic approach.293−301 In this regard, Matsui and co-workers exploited the bolaamphiphile bis(N-α-amidoglycylglycine)-1,7-heptane dicarboxylate as a self-assembling molecule.302,303 On the basis of the molecular structure and the 12664


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integration of biological molecules such as materials-directing peptides. This was first demonstrated by using carboxylateterminated Au nanoparticles (generated via nonbiological approaches)304 and metalloporphyrins;305 however, researchers subsequently adapted this method to incorporate materialsbinding peptides to exploit the biointerface to control nanoparticle assembly. Using biomimetic approaches, Djalali et al. were able to assemble Au nanoparticles along the bolaamphiphile nanotubes.295 In this regard, they noncovalently adsorbed the histidine-rich peptide (termed HRE: AHHAHHAAD) that was previously identified to bind hemozoin crystals and possessed the ability to passivate Au nanoparticles to the nanotubes.306,307 Interestingly, the integration of the peptide to the nanotubes is relatively simple, requiring only incubation of the nanotubes with the peptide in buffer at room temperature. Confirmation of peptide immobilization was achieved using Raman spectroscopy, via peptide peak observation on the nanotubes after coupling, as well as AFM imaging of the nanotubes after the reaction.295 Once the HRE peptide was adsorbed onto the nanotube surface, it was used to assemble Au nanoparticles along the template via the binding of the HRE to the growing inorganic materials.295 In this regard, the researchers employed a unique Au+ precursor, ClAuPMe3, as the metal ion source to grow nanoparticles. After incubating the metal ions with the HREmodified nanotube, NaBH4 was added to reduce the metal ions to generate and assemble the Au nanoparticles. Parts a and b of Figure 26 present a TEM image and analysis of the materials fabricated using this approach.295 The final nanoparticles produced were ∼6 nm in diameter and had a high density of ∼3.0 × 104 nanoparticles/μm2.295 Using a control system of the bolaamphiphile nanotube without the HRE peptide adsorbed, the Au nanoparticles that were generated and assembled using this system were polydisperse in size and randomly adsorbed onto the template (Figure 26c).295 Additional studies demonstrated that the morphology of the final Au assembly, including particle size, distribution, and density, was directly controlled by the reaction time, solution pH, and Au ion concentration.296 While the peptide nanotubes provide unique capabilities to assemble Au nanoparticles, not all of the nanotubes have the same diameter, where different sized nanotubes are typically prepared with the standard synthesis. For instance, in one synthesis, Gao et al. reported the production of nanotubes with diameters ranging from 10 to 320 nm.297 Note that differences in the overall tube diameter can be achieved with different batches of the monomer.297 While such diversity could be

protonation state of the molecule as a function of pH, it is able to self-assemble into two distinct structures. To this end, at low pH where the terminal carboxylates are protonated, the formation of nanotubes is achieved with an average diameter of 500 nm; however, at high pH values where carboxylate deprotonation is anticipated, helical nanoribbons are prepared with an average width of 2 μm (Figure 25).302 When structured

Figure 25. Bolaamphiphile-based structure. (Top) Bis(N-α-amidoglycylglycine)-1,7-heptane dicarboxylate bolaamphiphile structure. (a) Helical fibers generated by bolaamphiphile assembly at high pH. (b) Bolaamphiphile nanotubes prepared at low pH values. For (a and b) light microscopy was employed to image the materials. Reprinted with permission from ref 302. Copyright 2000 American Chemical Society.

in the nanotube morphology, this exposes numerous amide functional groups along the long axis of the tube to allow for hydrogen bonding with carboxylates, thus allowing for rapid

Figure 26. 1D assemblies of Au nanoparticles using the HRE-modified bolaamphiphile nanotube. (a) TEM analysis of the materials assembly; (b) particle sizing analysis of the assembled Au nanoparticles. (c) Control analysis of the Au nanoparticle generated and organized using the nanotube without peptide modification; (d) optical analysis of the materials in parts (a and c). Reprinted with permission from ref 295. Copyright 2002 American Chemical Society. 12665


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explore this capability, Yu et al. incorporated the Ag4 peptide (NPSSLFRYLPSD) previously isolated by Naik and co-workers with affinity for Ag.25,298 Interestingly, this peptide was also suggested to facilitate metal ion reduction; thus, it serves a dual purpose during nanoparticle fabrication. Yu et al. conjugated the biomolecule to the nanotube surface and subsequently exploited this structure to template the assembly of Ag nanoparticles. Interestingly, this peptide-modified nanotube was able to fabricate and assemble hexagonally shaped Ag nanoparticles at pH 7 (Figure 28).298 As the material-growth time increased, the size of the nanoparticles increased, reaching a maximum size of 50 nm in diameter after 72 h. Such a shape effect was anticipated as the Ag4 previously demonstrated the formation of nonspherical nanoparticles.25 Interestingly, when the free peptide was used to fabricate nanoparticles, multiple different nanoparticle morphologies were generated;25 however, when the Ag4 was adsorbed to the nanotubes, only hexagonally shaped particles were generated and assembled.298 This suggests that both the peptide binding of the inorganic particle to generate the biointerface and the constraint of the nanotube directly affect the morphology of the final material. Note that changes in particle dimensions could be achieved via changes in the reaction solution pH.298 To understand the mechanism of Ag hexagon formation and assembly using the Ag4-modified nanotubes, a variety of control experiments were conducted.298 First, when the nanotubes were used without peptide modification, inefficient Ag nanoparticle deposition was observed where only spherical structures were generated. Second, when a nonspecific dodecamer sequence (HGGGHGHGGGHG) was incorporated onto the tubes and used for Ag nanoparticle production and assembly, both spherical and hexagonal structures were observed. While inorganic materials were produced, they were more polydisperse in size, morphology, and surface density as compared to the Ag4-modified tubes.298 Note that, for both of these controls, an exogenous reductant had to be added, while with the Ag4-modified system, the peptide drove Ag+ reduction. Matsui and co-workers have been able to expand the peptidebased assembly of nanomaterials using bolaamphiphile nanotubes to various other metallic compositions using different materials-binding peptides. For instance, the assembly of Cu and Ni nanoparticles was accessed with the histidine-rich HG12 (HGGGHGHGGGHG) peptide that was employed for Cu and Ni binding.293,299 Interestingly, this peptide generated highly uniform assemblies of Cu and Ni nanoparticles on the nanotubes; however, when used as a nonspecific control peptide for the arrangement of Ag nanoparticles, inefficient nanoparticle organization was observed. This suggests that the specificity and the binding affinity of the peptide play a highly important role in controlling the overall nanoparticle assembly. Beyond Au, Ag, Cu, and Ni, Yu et al. demonstrated the generation of Pt nanoparticle assemblies using the nanotubes modified with the peptide HPGAH, which was shown to have affinity for Pt ions.301,308 Again using this approach, wellassembled Pt nanoparticles were observed. Beyond metallic nanoparticles, the bolaamphiphile nanotubes have also been exploited for the fabrication and assembly of semiconducting quantum dots. 294,300 Such effects were originally demonstrated using ZnS materials that were bound by the M1 peptide (VCATCEQIANSQHRSHRQMV).294,309 While this sequence was not originally identified with affinity for the inorganic material, it does preferentially fold to generate a zinc finger-like Cys2His2 motif.309 This structure was

useful, the ability to generate Au nanoparticle assemblies using nanotubes of a single diameter could be important for a variety of applications, especially optical/plasmonic capabilities, where forming 1D linear necklace-like assemblies of Au nanoparticles could be especially important. To achieve such capabilities, the researchers exploited size-exclusion chromatography to physically separate the nanotubes into different sizes.297 On the basis of the nanotube diameter and retention time on the column, Gao et al. were able to fractionate the original synthesis into specifically sized tubes. Using this approach, they were able to separate out nanotubes with an average diameter of 10 nm from the larger sized structures.297 Such a diameter rivals the size of the Au nanoparticles generated using the HRE-modified nanotubes;295 thus, 1D necklace structures of Au nanoparticles could be achieved using this approach. To generate the 1D nanoparticle necklaces, Gao et al. coupled the HRE peptide to the 10 nm bolaamphiphile tubes using standard approaches, which was confirmed using Raman spectroscopy.297 Next Au+ ions were incubated with the peptide-modified 10 nm nanotubes, allowing for metal complexation, followed by reduction with hydrazine hydrate. After reduction, the final materials were imaged using TEM, where the production of 1D linear nanonecklaces of Au nanoparticles was observed (Figure 27).297 Such materials are

Figure 27. Analysis of Au nanoparticle nanonecklaces generated using the HRE-modified 10 nm nanotube. (a−c) TEM images of the materials at different magnifications where the scale bars are (a) 100 nm, (b) 50 nm, and (c) 200 nm. (d) Electron diffraction pattern of the materials in part (a). Reprinted with permission from ref 297. Copyright 2005 John Wiley & Sons.

quite different than those structures that were assembled using larger-diameter nanotubes, as the previous materials were arranged over a substantially larger surface area. By using 10 nm nanotubes, the assembled Au nanoparticles could be strung together to allow for highly specific plasmonic coupling in one dimension, which could not be achieved using the materials assembled using larger nanotubes. As such, significantly different optical properties from these two different Au nanoparticle assemblies are anticipated. On the basis of the ability to introduce any peptide sequence to the bolaamphiphile nanotubes, the generation of various different inorganic nanoparticle assemblies could be achieved due to the selectivity of the materials-binding peptides. To 12666


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Figure 28. Analysis of Ag nanoparticle assembly using the Ag4-modified nanotubes. (a) Size of the Ag nanoparticles generated and assembled as a function of reaction time. (b) Ag nanoparticle hexagons assembled on the nanotube after 14 h at pH 7 (scale bar = 100 nm). Inset shows a highresolution image of the materials (scale bar = 15 nm). (c) Tilted image of one Ag hexagon of part (b) (scale bar = 10 nm). (d) Assembled Ag hexagons after 72 h of reaction at pH 7 (scale bar = 50 nm). (e) Assembled Ag hexagons and their diffraction pattern after 72 h of reaction at pH 7 using a smaller diameter nanotube (scale bar = 50 nm). Reprinted with permission from ref 298. Copyright 2003 American Chemical Society.

repeated pattern allows for the expression of numerous materials-binding peptides at highly oriented positions to control the arrangement and assembly of inorganic nanomaterials. As such, the biointerface can be exploited for the generation of inorganic material assemblies. While this level of organization is important, several works, notably including those using the tobacco mosaic virus, have demonstrated the use of viral capsids to arrange inorganic nanomaterials where materials-binding peptide sequences are not required.310−317 On the basis of this Review’s focus of using biointerfaces generated using materials-binding peptides, those systems are not discussed here, but they are important for accessing unique structures and provide potential alternative approaches to different inorganic assemblies. Belcher and colleagues have made impressive and expansive efforts at the genetic modification of the pVIII major coat protein of the M13 bacteriophage for the inclusion of materialsbinding peptides.13−16,38,47,57,58,318,319 They have extensively used this system for the fabrication of inorganic nanowires for applications in energy harvesting and storage, catalysis, biomedical diagnostics, magnetism, etc. While these approaches do lead to the controlled deposition and arrangement of inorganic nanomaterials and other energy-relevant molecules320,321 along the viral capsid, they are generally described in other areas of this Review based on their application. Here we describe two exemplar systems of controlled nanomaterial assembly using M13 phage modified with materials-binding peptides to generate a biointerface that controls material organization. A model example for the exploitation of the M13 bacteriophage capsid for materials assembly was for the generation of nanobatteries, where these composite structures may also demonstrate enhanced electrochemical capabilities.16 For this, Nam et al. exploited the repeating structure of the bacteriophage capsid to controllably integrate Au nanoparticles within a Co3O4 component. In this regard, the researchers exploited a bacteriophage genetically manipulated to present a tetraglutamic acid sequence at each copy of the pVIII coat protein (termed E4).16 The E4 system was important as this region of substantial negative charge was exploited to bind Co2+

anticipated to bind the Zn ions for eventual ZnS production and assembly on the nanotubes. In this regard, Zn2+ ions were incubated with the peptide-modified tubes to allow for metal ion complexation. Next Na2S was added to generate the ZnS quantum dots, which were regularly dispersed and assembled on the nanotube surface.294 Using a similar approach, the production and assembly of PbSe quantum dots was also achieved.300 For this material, the TAR-1 peptide (ISLLHST) was employed that was previously shown to coordinate Pb2+ ions.53 Interestingly, using this system, the growth and assembly of cubic PbSe nanoparticles on the nanotube interface was realized, where the morphology of the final materials appears to be dependent on the solution conditions. To this end, using a 2-ethanesulfonic acid (MES) buffer, nanocubes are generated; however, when a phosphate buffer was employed, PbSe nanorods were organized on the peptide-modified nanotubes.300 These differences in morphology appear to arise from the conformation of the peptides on the nanotube surface, which facilitated metal deposition and a controlled nanoparticle aggregation process to result in the different morphologies (cubes or rods).300 These morphologies appear to be dependent on the buffer used in solution, which may alter the peptide conformation and controlled nanoparticle aggregation process. Overall, bolaamphiphile nanotubes present a unique template to control the growth and assembly of nanoparticles. Because these nanotubes can be readily modified by different peptides, the incorporation of judiciously selected materials-binding sequences with affinity for limitless different material compositions is possible. The power of this approach is its broad applicability, which could be used to manipulate material properties including plasmonics/optics, catalysis, magnetism, etc. 3.4. Viral-Capsid-Designed Material Assembly Using Materials-Binding Peptides

Viral capsids oftentimes present numerous repeated protein units in highly arranged patterns. For instance, the M13 bacteriophage presents ∼2700 copies of the pVIII major coat protein arranged along the long axis of the virus.30 This 12667


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Figure 29. AuE4 virus for the assembly of Au nanoparticles within a Co3O4 component. (A) Diagram of the genetically engineered virus highlighting the materials-binding peptide motifs. (B) Au nanoparticles assembled using the AuE4; (C) materials after Co3O4 incorporation at various magnifications. Reprinted with permission from ref 16. Copyright 2006 American Association for the Advancement of Science.

Generation of the assembled materials followed a straightforward process. In this regard, the #9s1 was incubated with streptavidin-coated Au nanoparticles, which allowed for binding of the inorganic structures at the pIII region.41 Once this was complete, these materials were incubated with additional Au nanoparticles not coated with streptavidin, which led to their rapid incorporation along the pVIII region of the capsid. This is visually demonstrated in Figure 30A,41 where 5 nm Au nanoparticles bind along the pVIII region, while a 15 nm streptavidin Au nanoparticle is incorporated at the pIII domain.41 Figure 30B presents an image of two of the same constructs as observed in Figure 30A; however, they are positioned in direct side-by-side contact. On the basis of the size of the streptavidin-coated particles and the pIII region, multiple viruses can bind to one particle to generate more complex assembled structures from a single core (Figure 30D and E).41 Furthermore, as streptavidin can be coated on numerous inorganic particles of diverse compositions, different materials can be bound at the pIII domain. For instance, Huang et al. were able to replace the streptavidin-coated Au nanoparticles with comparable CdSe quantum dots (Figure 30C).41

ions for the controlled fabrication of Co3O4. The oxide was generated in a two-step fashion. First Co2+ that was complexed to the glutamic acid residues was reduced with NaBH4 to generated Co metal. Controlled oxidation of the metal in water resulted in the production of Co3O4 that encased the virus in the oxide.16 To incorporate Au nanoparticles into the Co3O4 component, controlled material assembly was employed. In this regard, Nam et al. exploited molecular biological approaches to incorporate a Au binding peptide (LKAHLPPSRLPS) into the E4 capsid.16 In this new, genetically modified system, termed AuE4, both the Au binding peptide and the E4 sequences were coexpressed on the surface of the virus (Figure 29).16 Interestingly, the Au binding domains were stochastically incorporated and not regularly positioned throughout the capsid based on the molecular biological approach used for its integration. Upon incubation of the AuE4 virus with 5 nm Au nanoparticles, binding of the particles to the exposed Au binding peptides occurred, resulting in the controlled assembly of the Au particles on the capsid (Figure 29).16 Next Co3O4 was incorporated at the E4 binding domains that were also expressed on the virus surface, leading to encapsulation of the assembled Au nanoparticles within the oxide component (Figure 29C).16 In a second unique hybrid system, Huang et al. exploited the diverse exposed peptide domains of the M13 bacteriophage to assemble multiple inorganic materials in controlled arrangements.41 In this regard, the researchers fused a Au binding peptide (VSGSSPDS) to the pVIII major coat protein while integrating a streptavidin-binding sequence (SWDPYSHLLQHPQ) at the pIII domain at the capsid terminus.41 This new construct, termed #9s1, thus had multiple materials-binding domains that could be employed to assemble complex nanoarchitectures. In this regard, Au nanoparticles could be integrated along the long axis of the virus, while any particle coated in a streptavidin ligand layer could be bound by the peptides at the pIII domain.

3.5. Challenges and Future Opportunities in Nanoparticle Assembly

While great advances have been made to exploit the peptidederived biointerface to direct and control nanoparticle assembly, current challenges must be overcome to progress this field further. In much of the pioneering work of Matsui and Rosi, chemical modification of materials-directing peptides is required to drive particle assembly. At present, many of these modifications have been serendipitously discovered, where the controllable generation of the assembly morphology cannot be predicted. For instance, as Rosi and co-workers have demonstrated, modification of the A3 peptide using C12 chains resulted in double-helical assemblies, while the addition of two alanine residues and a C6 chain at a terminus generated spherical Au nanoparticle superstructures. Ideally, from a more 12668


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The ability to use peptides to arrange multiple materials of disparate compositions also continues to be problematic. At present, Naik and colleagues have demonstrated the feasibility of this approach using multidomain peptides (e.g., to organize Au nanoparticles regiospecifically on graphene); however, additional demonstrations of this capability are limited. Much of this limitation arises from the formation of self-assembled peptide templates to control nanoparticle assembly, where the ability to controllably organize materials-binding peptides with affinity for different material compositions is incredibly difficult. Modern approaches employ only a single peptide in the template to direct the assembly of one type of nanoparticle. By introducing two peptides into the template, stochastic arrangements of the peptides within the framework would be achieved, thus resulting in particle assemblies of random arrangements and orientations, as dictated by the peptide arrangement within the template. Exciting opportunities are available to selectively control the arrangement of materials-binding peptides within these assembling frameworks, which would give rise to the controlled orientation of the different nanoparticles within the overall 3D structure. Finally, while it is likely that materials-binding peptides with different affinities could access nanoparticle assemblies with multiple-particle compositions, the selective affinity of these peptides must be enhanced to access such capabilities. Current research has shown that, while biocombinatorial selection techniques are able to identify peptides with affinity for the target material composition, they are quite likely to have affinity for different material compositions as well. For instance, the A3 peptide was originally isolated with affinity for Ag; however, extensive research has demonstrated its strong binding for Au. For peptide-based approaches for multimaterial particle assembly to be viable, the selective affinity for the different compositions within the structure must be greatly enhanced as compared to present-day systems. Some recent results have suggested that such capabilities are possible, but highthroughput screening methods are required to fully assess such capabilities in a rapid, straightforward manner. From these approaches, highly selective peptides for the different particles in the assembly could be realized and used to drive the production of multimaterial assemblies. In addition to the challenges associated with assembly creation, their characterization provides key issues with understanding the assembly process. This is especially noteworthy for TEM imaging of the materials, where solvent evaporation could give rise to the observed structures. Characterization of the assemblies in the native state (i.e., dispersed in solution) is critically important for understanding both the assembly process and the actual structure of the materials. Solvent evaporation is known to provide shearinduced forces and other effects on the sample, which could give rise to specific assemblies. At present, solution-based TEM imaging is possible, but only a limited number of facilities are available to conduct this technique, which requires specialized equipment. Additionally, cryo-TEM characterization is possible where the structures in solution are locked into their assembled morphology via flash freezing of the sample; however, this then requires complex imaging of the frozen sample. While solutionbased imaging analysis is available, its widespread application remains substantially limited.

Figure 30. Nanoparticle assembly achieved using the #9s1 virus capsid. Au nanoparticles are arranged along the long axis of the virus, while binding to a secondary material occurs at the pIII region due to peptide/streptavidin binding. Schematically, yellow and green spheres represent Au and CdSe nanoparticles, respectively, while the red and white regions represent the streptavidin or virus components, respectively. Reprinted with permission from ref 41. Copyright 2005 American Chemical Society.

comprehensive understanding of the chemical interactions at play, the ability to predict the assembly morphology without trial-and-error experimentation would be a significant breakthrough to fabricate organized structures with desired properties for specific applications. Beyond the biological component, nanoscale spatial resolution control over the individual assemblies remains difficult to achieve. While peptide-based approaches have demonstrated remarkable capabilities with regards to controlling individual nanoparticle sizes, their interparticle spacing, and their threedimensional arrangement, reliable approaches to control such structural features are needed. For instance, the ability to directly place nanoparticles at specific locations within a 3D arranged structure with controllable interparticle spacings and particle sizes (either the same or even differently sized nanoparticles) cannot be achieved without extensive further studies. If such structural control could be readily achieved, the one-pot synthesis of highly resolved 3D assembled materials could be accessed with significant property control. 12669


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Figure 31. Graphene/virus complex with the enhanced colloidal stability of the hybrid graphene/nanoparticle nanocomposites. (a) Scheme of the inorganic-nanoparticle nucleation on the graphene/virus template. The virus enables a close contact between inorganic nanoparticles and the graphene. (b) (Top) Peptide sequence of pVIII protein of p8cs#3 and EFE. (Bottom) Zeta potential of EFE and p8cs#3. (Inset) Hydrophobicity plot of the pVIII major coat proteins of p8cs#3 virus as a function of the amino acid location. (c) Left vial: graphene solution after 24 h of incubation with bismuth nitrate, showing the aggregation of graphene on top. Right vial: graphene/FC#2 complex solution after 24 h of incubation with bismuth nitrate without any aggregation. (d) AFM image of the graphene/FC#2 complex. (Inset) Height profile of line A showing the thickness of graphene as ∼0.8 nm. Reprinted with permission from ref 331. Copyright 2012 John Wiley & Sons.

4. PEPTIDE-BASED MATERIALS FOR ENERGY One of the central challenges inherent to the sustainable creation of materials for the efficient and clean generation, harvesting, conversion, and storage of energy is to minimize the total costs of production; these costs may include the use (and responsible disposal) of costly (and hazardous) solvents, high thermal budgets, and expensive postprocessing in the synthesis process. Moreover, the particular demands of these materials typically require that strong synthetic control be exerted over the structuring of these materials at the nanoscale. Bioinspired approaches based on peptide-directed growth, assembly, and activation of inorganic materials comprise a powerful strategy that combines the dual benefits of environmentally benign synthetic conditions with exquisite control over the resulting nanostructure of the material.

capacity fade (due to, for example, mechanical stress arising from the charge/discharge cycle) over time. As detailed earlier (see section 2.1), the filamentous M13 phage possesses several external coat proteins located on different sites of the virus exterior, which can be genetically manipulated to incorporate peptide sequences with versatile functionalities such as materials-binding sequences. In this strategy, the pVIII major coat (located on the length of the filament) and the pIII minor coat (located at the end of the filament) of the M13 phage comprise common targets for genetic modification, so as to display peptide sequences amenable to the growth, binding, and organization of energy-relevant inorganic nanomaterials, as described for materials assembly. However, many of the earlier studies, including the pioneering research reported by Belcher and co-workers in the creation of anode materials for lithium ion batteries (LIBs), focused their attentions on the E4 clone of M13 (and/or variations thereof). This clone presents a peptide sequence enriched in negatively charged residues on the pVIII major coat protein (typically three/four glutamates). While facilitating the virus-templated growth of mesoporous materials based on metal oxide nanowires such as Co3O416,322 and FePO4,323 this Glu-enriched sequence is not a materials-specific

4.1. Energy-Storage Materials

Energy-storage materials have been a strong focus of such biobased, peptide-directed synthetic approaches, particularly those strategies based on the virus-templated growth and organization of nanostructured inorganic metal oxides accessed via the biointerface. Among the pivotal qualities required of these oxide materials as battery anodes, there is a need for materials with a high discharge capacity while minimizing 12670


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beyond LIBs. Na-ion batteries (NIBs) remain relatively unexplored using materials-binding peptide approaches and yet promise cheaper and safer energy-storage solutions compared with LIBs, albeit with an increased weight, which may limit the range of their applications. However, the electrode-design requirements for NIBs are similar to those for LIBs and can therefore be beneficially explored using peptide-mediated synthesis. Recently, to create a new cathode material for NIBs, Belcher and co-workers332 used the SWNTbinding genetically modified M13 phage to assemble SWNTs and subsequently grow nanostructured FePO4 under ambient conditions on these SWNT/virus assemblies. As reported previously for virus/SWNT assemblies used in LIB cathode materials, the presence of the SWNTs both enhanced capacity and mitigated capacity fade of the NIB cathode. One challenging task in using virus-templated approaches is to go beyond the production of metal oxides, by fabricating complex inorganics such as nanostructured lithiated poly ion materials. This was recently reported by Belcher and coworkers,333 where a dual-function pVIII sequence modification was found to both promote virus−SWNT attachment (as reported previously for other metal oxide cathode materials) and, via a preseeding of manganese oxide on the virus coat, facilitate the formation of crystalline LiMnBO3 nanoparticles templated on the virus exterior. Although this process requires an annealing step, the annealing schedule is much shorter than that required by traditional synthesis approaches, and therefore, the virus-templated approach can reduce the thermal budget associated with the inorganic synthesis of this complex material. This study encouragingly suggests that similar peptidemediated approaches for the synthesis of other complex electrode materials are possible. Nevertheless, the cycling performance of this particular cathode material suggests that considerable scope for optimization remains for future work. Biobased approaches for the creation of LIB anode materials have received less attention to date.16,318 In their pioneering study on virus-templated LIB materials, Belcher and coworkers16 combined the E4 modification of the M13 phage with a second pVIII insertion of a Au-binding sequence determined from phage-display experiments.17 This virus construct was used to first grow and organize Au nanoparticles along the length of the virus, followed by growth of nanostructured Co3O4, as discussed earlier. The presence of the Au nanoparticles was proposed to provide a conductive network and was found to enhance capacity relative to the Co3O4 grown in the presence of the E4 clone. In another example using noble metals, Belcher and co-workers318 explored their virus-templated approach in the pursuit of suitable LIB anode materials from metal alloys. Through the use of engineered M13 clones that displayed a Au-binding sequence41 on the pVIII major coat protein, Belcher and coworkers created alloyed Ag/Au nanowires that showed promising cycling performance. Very recently, efforts using peptide-mediated fabrication have shifted to lithium−air (Li−O2, LOB) battery electrode materials.324,335 Two essential pillars of LOB electrode functionality are the catalysis of the oxygen-reduction and oxygen-evolution reactions (ORR and OER, respectively). LOB cathode materials typically require a high porosity, ideally operating on at least two length scales: smaller pores to confer a large, active interfacial area to support catalysis and facilitate O2 diffusion through the material and larger pores to accommodate the deposition of discharge products such as Li2O2, the

peptide sequence and has been used to nonspecifically grow a range of metal oxide materials.319,324−329 In contrast, Fong and co-workers330 used similar nonspecific materials-nucleating sequences (in this case, these authors used a negatively charged sequence, which they denoted as the FLAG sequence), but in partnership with a nonvirus-based approach. Instead, these authors constructed a chimeric hybrid where FLAG was fused with an elastin-like protein (ELP). The ELP−peptide hybrids were shown to facilitate the formation of a cross-linked porous hydrogel while also promoting the formation of inorganic nanomaterials at the cross-linking sites. These hydrogels were sacrificed to create heteroatom-doped (N and/or F), carbonized mesoporous anode materials for LIBs, where the FLAG sequence promoted the formation of additional catalytically active MnF2 nanocrystals colocated in the carbonized pores. The use of materials-specific peptides, as opposed to the nonspecific E4 motif, has found excellent utility in the phagebased production of battery electrodes. One key desirable structural requirement for battery electrode materials is the need to realize an ideally cocontinuous, interpenetrating network of conductive material and electrode material on the nanoscale, so as to maximize the interfacial contact area between the conductive phase and the active phase, mitigate mechanical stresses during the charge/discharge cycle, and create an efficient percolating network that can enhance electronic transport. To meet these requirements, Belcher and co-workers14,331−333 published a series of studies using engineered phage modified with materials-binding peptides as a strategy to incorporate and disperse nanostructured networks of conductive material throughout the active oxide phase, particularly for realizing metal-ion battery cathode materials with superior performance. For example, Belcher and coworkers14 further modified the E4 clone of M13 to engineer the minor pIII coat at the distal end of the phage to present a single-walled carbon nanotube (SWNT)-binding peptide sequence, identified from phage-display experiments. This dual-function phage design conferred selective adsorption of conductive SWNTs to maximize SWNT dispersion throughout the nanocomposite, while the E4 sequence modification facilitated the nucleation and growth of FePO4 along the long axis of the virus. The capacity of the resulting cathode material was comparable with that of commercial c-LiFePO4 cathodes. In an attempt to incorporate dispersed graphene into a nanocomposite comprising metal-oxide coated M13 virus filaments, Belcher and co-workers331 introduced three distinct mutations into the one phage clone: (1) a sequence to facilitate graphene binding into the pVIII major coat (actually derived from phage-display experiments screened against SWNTs334), (2) an additional two-point mutation of the nongraphenebinding region of pVIII with glutamate to enrich negative charge (to facilitate growth of the oxide material), denoted EFE, and, finally, (3) the incorporation of a second, different SWNT-binding sequence334 into the pIII minor coat. These authors tested this virus clone (denoted FC#2) construct by creating hybrid graphene/virus/bismuth oxyfluoride cathode materials for LIBs; in particular, their control experiments suggested that the presence of the trimodified virus clone was essential for dispersing graphene throughout the nanocomposite, providing superior cathode performance (see Figure 31). Recent efforts in using materials-binding peptides for fabricating metal ion battery cathode materials have diversified 12671


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TiO2 nanowires in photovoltaic anode materials (Figure 32). Similar to the requirements for LIB electrodes, an inter-

presence of which can eventually block the active sites of the electrode and diminish capacity. Peptide-based synthetic approaches have been demonstrated to meet these challenging structural requirements and, in addition, can obviate the need for hazardous solvents in their synthesis while also curbing the energy-intensive demands associated with creating these materials. Engineered virus-templated approaches have been recently used to meet these LOB cathode requirements.324 Belcher and co-workers repurposed the same phage clone used in their graphene-dispersed LIB cathode studies,331 namely, the trimodified FC#2 clone, to template the growth of partially crystalline MnOx; then, with the addition of poly(acrylic acid), noble metal (Au and Pd) nanoparticles were grown on the exterior of the manganese oxide nanowires. The enhanced surface area of the templated inorganic material was found to mitigate catalyst blocking from discharge products, particularly for the Pd/MnOx/virus composite. Incorporation of the Pd nanoparticles was also found to extend the cycling stability of the electrode. Similar studies have been reported328 using the E3 (triglutamate) clone of M13 to fabricate both Co3O4 and cobalt manganese spinel oxide nanowires for similar purposes; however, these did not make use of specific materials-binding sequences. Alternatively, Fong and co-workers335 have focused on peptide-based approaches to fabricating LOB electrode materials. These authors used chimeric molecules comprising ELP (ELK16) fused with a nonspecific metal-binding peptide, denoted by these authors as FLAG. The presence of their FLAG sequence was found to be critical to the formation of cross-links in the network with the Mo4+ precursor, resulting subsequently in the presence of spatially colocated MoO2/ Mo2C nanocrystals dispersed throughout the hydrogel matrix. The colocation of the MoO2 and Mo2C nanocrystals is particularly advantageous because these materials catalyze the ORR and OER reactions, respectively. The resulting 3Dnetworked soft material was then annealed at high temperature, resulting in a carbonized solid, porous, nitrogen-doped support containing the colocated MoO2 and Mo2C nanocrystals. This process yielded electrode materials with outstanding electrochemical performance in terms of round-trip efficiency, rate performance, and cycling performance. However, again, materials-specific peptides per se were not used in the chimeric fusion protein. In summary, the prospects for widening the basis of the engineered virus-template approach pioneered by Belcher and co-workers are substantial and remain to be fully explored. Translation to nonvirus-based strategies, particularly to the use of fusion proteins, in partnership with genuine materialsbinding peptides, could serve to provide further synthetic control of the nanoscale structuring and organization between the conducting and active phases of battery electrode materials.

Figure 32. Process of virus/SWNT complexation and biomineralization of TiO2 on the surface of the virus/SWNT complex. Adapted with permission from ref 334. Copyright 2011 Nature Publishing Group.

penetrating cocontinuous network of conducting and active phases comprises a key design strategy for enhancing the performance of photovoltaic devices, so as to optimize electron diffusion lengths (e.g., to enhance photocollection) while not adversely affecting other parameters of the device, such as the electron−hole recombination. In this study, these authors first used phage-display experiments to identify an appropriate SWNT-binding sequence. The exploitation of materials-binding peptides, as opposed to nonspecific negatively charged sequences, remains to be realized in the generation of both piezoelectric and photovoltaic materials and presents interesting opportunities for future research. 4.3. Energy-Conversion Materials

Similarly, the development of fuel cell materials has enormous potential to benefit from the peptide-directed growth, organization, and activation of inorganic nanomaterials. In particular, the search for commercially viable electrode materials for polymer electrolyte fuel cells (PEFCs) has been the focus of intense research efforts, with Pt/carbon cathodes best facilitating oxygen-reduction reaction (ORR) catalysis. However, these cathodes suffer from stability challenges: the Pt nanostructures on the carbon support tend to agglomerate with time, degrading the catalytic activity. Very recently, Liu and coworkers337 reported the use of peptides inspired by the Ptbinding sequences derived from Huang and co-workers,59 to grow and stabilize small Pt nanoparticles (∼2 nm) chiefly displaying the Pt(111) facet, on carbon black substrates. These authors used room-temperature electron reduction to prepare these interfaces and contrasted the ORR performance of this interface with control systems (e.g., without the presence of peptide). The peptide/Pt/carbon composite featured an ORR activity higher than that of the commercial Pt/C electrode, along with enhanced stability, which the authors attributed to the enrichment of Pt(111) facets on their fabricated nanoparticles. This work serves to illustrate the enormous promise held by peptide-based approaches for both controlling nanoparticle shape and composition at the electrode interface

4.2. Energy-Harvesting Materials

In contrast, the peptide-directed synthesis of energy-harvesting and energy-conversion materials has seen much less focus. Many of these existing examples, with applications to photovoltaics and piezoelectric materials, are not based on material-binding peptides but rather on the E3/E4 engineered M13 virus,319,325,327 or recently, on a Lys-rich pVIII insert on M13 (to promote interactions with inorganic precursor anions).336 In contrast, Belcher and co-workers334 reported the use of SWNT-binding sequences to modify the M13 phage for realizing the coassembly of SWNTs with virus-templated 12672


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Figure 33. Schematic illustration of the virus-templated electrode assembly, using phage engineered with Au-binding peptides on the pIII coat of M13, to realize a glucose oxidase fuel cell. Reprinted with permission from ref 338. Copyright 2016 American Chemical Society.

Figure 34. Schematic illustration for the fabrication of the PS/Pt gyroid nanohybrids using a block copolymer template from the hydrolysis of polystyrene-b-polylactide (PS−PLLA) for electroless plating. Transmission electron micrographs of the nanohybrids after seeding (b), followed by 2day growth (c) and 5-day growth (d). The inset shows the corresponding illustration. Reprinted with permission from ref 340. Copyright 2015 Nature Publishing Group.

and immobilizing and/or dispersing these nanoparticles on a carbon support to prevent their agglomeration (and concomitant loss of activity) under operating conditions. Experimental efforts to design chimeric peptides to accomplish this would be extremely advantageous and to date have remained unexplored. Moreover, there are considerable economic and geopolitical pressures to substantially reduce the loading of Pt in commercial PEFC electrode materials. As illustrated recently by Bunker and co-workers,3 the use of peptide-directed synthesis to create surface-segregated bimetallic nanoparticles is one viable route to achieve this and could result in cheaper nanomaterials where only the near-surface region of the nanoparticles is enriched in Pt. The development of biofuel cells, which are energygeneration devices that are typically advantageous for small portable or implantable devices, are associated with a different set of challenges. One of the key criteria for a successful biofuel cell design is to establish direct electron transfer between the biocatalyst (typically a complex enzyme) and the electrode surface. Dunn and co-workers338 recently explored the use of peptide-directed strategies, via materials-specific Au-binding sequences, to realize this direct electron transfer for an exemplar glucose oxidase (GOx)-based biofuel cell. To accomplish this, these authors used virus-templated assembly, by engineering the pIII minor coat of the M13 phage to recognize the Au electrode surface, thereby anchoring the phage to the substrate. This phage also served as a scaffold onto which prefunctionalized Au nanoparticles presenting carboxylic

acid groups could be assembled. The GOx were then covalently attached to these carboxylates to complete the virus/Au nanoparticle/GOx/electrode assembly (see Figure 33). These authors confirmed that this approach delivered superior surface coverage of the attached enzyme, which retained its catalytic activity in the oxidation of glucose, resulting in a high peak current per area. These promising results suggest exciting alternative approaches, based on bifunctional, chimeric protein fusions with materials-binding sequences. For instance, by following the general approach of Baneyx and co-workers,339 strategies based on the insertion of electrode-binding sequences into permissive sites of the enzyme (far from the active site) could comprise a promising and new area for achieving direct electron transfer between the enzyme and the electrode in these biofuel cells. 4.4. Challenges and Future Opportunities in Energy Materials

In summary, most of the key advances made to date in the area of peptide-directed synthesis and organization of energy-related materials have been realized using virus-templated approaches based on the genetic modification chiefly of the filamentous M13 phage to display materials-binding sequences. Furthermore, the main achievements in this space have focused on energy-storage materials, particularly lithium ion battery electrode materials. Energy-harvesting materials, chiefly for piezoelectric and photovoltaic materials, offer rewarding opportunities for further development. The peptide-directed 12673


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A well-studied system for peptide-capped nanoparticle catalysis is materials derived from the Pd4 peptide (TSNAVHPTLRHL) (refs 3, 26, 32−34, 62, 75, 76, and 355−358). This peptide was originally isolated via phage display with affinity for Pd metal.26 Using standard synthetic techniques, ∼2 nm Pd nanoparticles capped by the Pd4 peptide can be generated. Interestingly, nanoparticles of generally the same size can be prepared using this peptide regardless of the Pd/peptide ratio (at Pd/peptide ratios < 5).32,33 This effect arises from the binding event between the peptide and the nanoparticle surface. To this end, at a size of ∼2 nm, the growing Pd structure becomes crystalline and displays facets that the peptides recognize and bind to arrest growth.32 These particles have been extensively used for catalysis, particularly to drive C−C coupling reactions (Figure 35). For instance, Pd4-

growth, assembly, and activation of fuel cell electrode materials have also been vastly unexplored and provide exciting possibilities for new avenues of research, particularly for identifying solutions that curtail the current dependence on Pt group metals for their successful application. The key design criteria in the synthesis and organization of many different types of energy, conversion, harvesting, and storage materials have one requirement in common: the need to create an interface between the active phase and the conductive phase that maximizes interfacial area. Formation of nanostructured, interpenetrating, cocontinuous phases between the active phase and a conductive phase could be achieved by exploiting the exceptional level of control that materials-binding peptides can offer. Particularly promising is the use of softtemplating approaches to create gyroid structures, which could be subsequently used to create 3D gyroid structures of inorganic material. In recent studies, synthetic polymers have been used to accomplish this, e.g., for creating 3D, porous Pt networks340 (Figure 34), and even for fabricating Li−S battery cathodes.341 The incorporation of materials-binding peptides into this soft gyroid template, to gain enhanced compositional and structural control over these nanostructured materials, is completely unexplored and would open an entirely new research avenue for the green synthesis of energy materials in general.

5. CATALYSIS Catalysis is required to generate a variety of life’s daily necessities; thus, new approaches for chemical transformations are continually in demand. In light of growing energy and environmental concerns, new catalytic approaches are required that are energy-efficient, ecologically friendly, and sustainable. Bioinspired approaches represent new methods to access such capabilities, where materials-directing peptides have demonstrated unique capabilities for the generation of functional catalytic materials. This is especially important where recent studies have suggested that peptide binding and biointerface formation may have dramatic implications on nanoparticle catalyst metal surface features,2,3,62,65,342 which are directly translatable to the overall reactivity. Additional approaches that exploit templates displaying inorganic materials-binding peptides also present intriguing approaches to adapt biological processes for catalytic material synthesis and activation, as discussed below. Finally, systems that exploit enzymatic and viral-based catalysis provide promising avenues for catalytic capabilities343−349 but are not discussed herein as they are not focused on biointerfaces between biomolecules and inorganic materials.

Figure 35. Scheme for the synthesis of peptide-capped Pd nanoparticles and the mechanism for the model Stille coupling reaction of reacting 4-iodobenzoic acid with PhSnCl3 to generate biphenylcarboxylic acid. Reprinted with permission from ref 26. Copyright 2009 American Chemical Society.

capped Pd nanoparticles can drive the Stille coupling of 4iodobenzoic acid and PhSnCl3 to generated biphenylcarboxylic acid with a turnover frequency (TOF) of ∼2200 mol product (mol Pd × h)−1.34 Remarkably, this reaction is performed in water at room temperature, thus meeting specific goals for green reactivity. They can also drive Suzuki coupling; however, the TOF values are substantially lower and the reaction is highly dependent on the base used.355 For example, the Pd4capped Pd nanoparticles catalyzed the coupling of 4iodobenzoic acid with phenylboronic acid to generate biphenylcarboxylic acid with a TOF value of 337 ± 93 mol product (mol Pd × h)−1 using K3PO4 as a base.355 In this reaction, the base likely plays a role in deprotonation of the Pd2+ intermediate and/or the phenylboronic acid reagent. Computational analysis of the binding event between the Pd4 peptide and the Pd metal indicated that the histidine residues at the 6 and 11 position likely served as anchor points.154 In this regard, these two residues noncovalently bind to the Pd nanoparticle during growth, capping the materials at a specific size, but also generating the biointerface between the two components. Coppage et al. exploited mutation studies where these two residues were selectively exchanged with alanines.34 By swapping the imidazole side chain of histidine for a simple methyl group of alanine, binding at the 6 or 11 position could be inhibited, thus substantially changing the

5.1. Peptide-Capped Nanoparticle Catalysis

Peptide-capped nanoparticles have been extensively studied for their catalytic application, especially for Pd-based structures.26,32,34,76 Pd is a well-known catalytic material with capabilities to drive reactions such as C−C coupling, olefin hydrogenation, etc., the basis of which has been extensively reviewed elsewhere.350−353 While the early studies in this area of bioinspired nanocatalysts were reviewed previously,354 significant advances have occurred in recent years focusing on the catalytic capabilities of these materials, including atomically resolved characterization of their structures from the inorganic core to the biological shell, focusing heavily on the structural effects of the biointerface. 12674


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biointerfacial structure. A library of three mutant peptides was generated that modified the parent Pd4 peptide at the 6 (A6: TSNAVAPTLRHL), 11 (A11: TSNAVHPTLRAL), and 6 and 11 position (A6,11: TSNAVAPTLRAL).34 Through these manipulations, changes to the biointerface should occur as the binding between the peptide and the nanoparticle must be altered, thus affecting the catalytic properties. Using the Pd4 peptide and three mutated sequences, peptide-capped Pd nanoparticles were prepared where the average size of the final nanoparticles was dependent on the peptide sequence and varied over a small window of 2−4 nm.33,34 As discussed in section 2.3, CD spectroscopy was employed to characterize the biointerfacial structure, which demonstrated that the mutations to the sequence did noticeably alter the peptide structure when bound to the nanoparticle. Catalytic analysis of these materials for the standard Stille coupling reaction demonstrated surprising results. In this regard, the parent Pd4-capped Pd nanoparticles displayed a TOF value of 2234 ± 99 mol product (mol Pd × h)−1; however, for the A6-capped materials, a substantially enhanced TOF value of 5224 ± 381 mol product (mol Pd × h)−1 was observed. Modification of the peptide at the 11 position resulted in diminished reactivity with TOF values of 1298 ± 107 and 361 ± 21 mol product (mol Pd × h)−1 for the A11- and A-6,11-capped Pd nanoparticles.34 Additional mutations to the Pd4 peptide were exploited to further understand the biointerface structural effects on the catalytic properties.76 While alanine residue incorporation could diminish affinity at the anticipated binding site, swapping of the native histidine residue for a cysteine was used to enhance the affinity via the exposed thiol group that is known to strongly bind metallic nanomaterials.359,360 As such, a new library of sequences was developed that modified the 6 and 11 positions of the Pd4 peptide for native/intermediate binding (histidine), weaker binding (alanine), or stronger binding (cysteine).76 Using these rules, a series of six mutant peptides were analyzed termed C6, C11, C6,11, A6C11, C6A11, and A6,11. The letter denotes for what amino acid histidine was substituted at the indicated position. Using these sequences, stable Pd nanoparticles were readily generated with average sizes between 2.0 and 2.5 nm, capped on the surface with the peptide.76 Once prepared, the materials were examined via CD spectroscopy, which confirmed variations in the biointerfacial structure as a function of the peptide sequence. Such results were consistent with computational modeling studies of the peptide-binding event.76 These cysteine-containing peptide-capped particles were subsequently exploited for the model Stille coupling of 4iodobenzoic acid with PhSnCl3 to generate biphenylcarboxylic acid. As shown in Figure 36, the reactivity was highly dependent on the peptide sequence and the biointerfacial structure at the particle surface.76 The parent Pd4-capped Pd nanoparticles presented a standard TOF value of ∼2200 mol product (mol Pd × h)−1. When a cysteine residue was incorporated at the 6 position of the peptide, reactivity nearly doubled, while incorporation at the 11 position resulted in a near tripling of the reactivity.76 These results strongly demonstrate that the biointerfacial structure plays a key role in the catalytic capabilities of peptide-capped materials. While CD spectroscopy confirmed that the mutations to the Pd4 peptide did play a significant role in manipulating the biointerfacial structure, such sequence changes could also alter the underlying inorganic surface. To access such information,

Figure 36. Comparison of the Stille coupling reactivity for the Pd4and cysteine peptide-capped Pd nanoparticles. TOF values are provided for the model coupling of 4-iodobenzoic acid with PhSnCl3 to generate biphenylcarboxylic acid. For comparison, the TOF for the reaction driven using the A6,11-capped Pd nanoparticles is shown. Reprinted with permission from ref 76. Copyright 2013 American Chemical Society.

Bedford et al. exploited atomically resolved X-ray-based characterization methods to interrogate the complete structure of the inorganic materials.62 Coupled with computational methods, this analysis provided unique atomic-level understanding of the structure/function relationship of the peptidecapped Pd materials. These authors generated pair distribution function (PDF) analyses of high-energy X-ray diffraction (HEXRD) data of the peptide-capped Pd nanoparticles.62 PDF data were acquired for all of the materials capped with the different mutated peptides (i.e., histidine mutations with either alanine or cysteine at both the 6 and 11 positions). These data can then be fitted with reverse Monte Carlo (RMC) methods, which was used to generate a structure of the average material in the sample (Figure 37, RMC column).62 As is evident, the RMCderived nanoparticle structures display a highly disordered Pd surface that veers far from the anticipated structure for singlecrystal Pd nanoparticles. While the surface is highly disordered, the inner core Pd atoms of the particle were more ordered (Figure 37, RMC Core column).62 This suggests that the peptide-binding event at the particle surface to generate the biointerface imparts significant disordering of the metal atoms, where the disordered structure of the materials was observed to be dependent on the peptide sequence. Note that only a single amino acid residue difference is present in many of these sequences, demonstrating strong localized effects of the peptide on the surface structure. While the RMC analysis of the PDF data provides key structural information, these morphologies arise from the averaging of all particles in the sample. As a result, imperfections are likely, including metal atoms not in direct contact with the nanoparticle. To address these issues, the RMC structures were computationally relaxed using MD approaches (Figure 37, MD column).62 Once relaxed, the peptide sequences used to generate the particles were computationally adsorbed onto the nanoparticle surface (in the presence of water), thus providing, for the first time, a complete structure of the peptide-capped nanoparticles at the atomic level from inner metallic core to the bioligand layer (Figure 37, MD (peptide + water) column).62 As is evident from the analysis, all of the different peptide-capped nanoparticles were strikingly different, resulting in dramatically altered peptide conformations, biointerfacial structures, and 12675


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Figure 37. Morphologies of the peptide-capped Pd nanoparticles using the indicated peptide. RMC indicates the particle determined from the reverse Monte Carlo analysis of the PDF data, while RMC Core shows the core of the RMC particles. HRTEM presents a TEM image of the individual particles. Finally, MD presents the RMC particles after relaxation using MD approaches, while the last column presents the particles after peptide adsorption as determined computationally. Reprinted with permission from ref 62. Copyright 2015 American Chemical Society.

Figure 38. Catalytic analysis of the peptide-capped Pd nanoparticles for Stille coupling. (a) Leaching mechanism; (b) abstraction energy for the Pd atoms of the Pd4-capped Pd nanoparticle. (c) Comparison of the computationally derived atom abstraction rate with the experimentally determined TOF values for the model Still coupling reaction. Reprinted with permission from ref 62. Copyright 2015 American Chemical Society.

metal atom disordering, all of which were dependent on the peptide sequence employed to prepare the materials.62 Using the atomically resolved structures of the nanoparticles, their reactivity for Stille coupling was computationally assessed and compared to experimental results (Figure 38).62 As discussed below in more depth, the peptide-capped Pd nanoparticles likely follow an atom-leaching mechanism75 where the first step of the process, oxidative addition, abstracts a Pd atom from the nanoparticle surface from which the reaction is subsequently completed in solution. This atom continues to be recycled through the reaction process, where the final fate of the atom upon reaction completion remains

unclear. Using MD simulations, the amount of energy required to abstract a Pd atom from the nanoparticle surface was calculated and compared for each atom within the particle using the PDF-derived structures (Figure 38).62 In general, those atoms that were the most disordered required the least amount of energy for abstraction from the particle, as anticipated. From this information, the relative abstraction rate can be derived for each nanoparticle, which compared quite favorably with the experimental TOF values, suggesting that the disordered atoms on the particle surface are likely the reactive species.62 Similar approaches were considered for the same peptide-capped 12676


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nanoparticles using olefin hydrogenation as the reaction where different reactive sites were observed based on the surfacedependent reduction process.62 While it is clear that the biointerface likely plays a role in controlling the catalytic activity via two considerations (i.e., controlling nanoparticle metal atom surface disorder via peptide binding and the overall structure of the biointerface controlling metal exposure to solution), it is important to understand the catalytic mechanism being processed by the nanoparticle catalysts. For Stille coupling, two possible processes could be occurring: the reaction could be driven directly on the nanoparticle surface361,362 or oxidative addition could be abstracting metal atoms from the surface where the reaction is processed in solution.357,363−365 The second mechanism is commonly referred to as the leaching mechanism in the literature. To probe this effect, Briggs et al. exploited a bifurcated reaction process as well as X-ray-based analysis of the reaction.75 In the standard reaction process, the two reagents, 4-iodobenzoic acid and PhSnCl3, are commixed with the nanoparticles; however, in the bifurcated process, the aryl halide and Pd4-capped Pd nanoparticles are mixed together in the absence of the tin reagent. After 30 min, the PhSnCl3 is added to the reaction mixture, where the reaction is initiated only when the tin compound is added to the system.75 Using the bifurcated reaction process, extended X-ray absorption fine structure (EXAFS) analysis of the Pd4-capped Pd nanoparticles was processed.75 In this case, clear Pd−Pd bonds are evident from the nanoparticles prior to the reaction starting; however, for the Pd materials incubated with the 4iodobenzoic acid, no Pd−Pd bonds can be observed. This is consistent with complete degradation of the nanoparticles in the presence of the aryl halide starting materials. This result was confirmed through SAXS analysis of the reaction mixture under the same conditions.75 Prior to aryl halide addition, the nanoparticles displayed a feature consistent with the scattering associated with a particle of ∼2.4 nm. This value was quite close to the one observed by TEM analysis (2.0 nm). After aryl halide addition, no scattering was observed from the sample, suggesting complete nanoparticle degradation by the 4iodobenzoic acid, which was fully consistent with the EXAFS results.75 When the same nanoparticles were analyzed after the standard reaction was completed (i.e., both the aryl halide and PhSnCl3 were commixed simultaneously with the nanoparticles), clear changes in the particle structure were evident by EXAFS and SAXS, consistent with surface structural changes to the nanoparticles arising from metal atom leaching.75 Figure 39 presents the proposed mechanism. In the first step, surfacedisordered Pd atoms are abstracted from the nanoparticle surface due to aryl halide oxidative addition. Once leached, these Pd2+ complexes can continue the reaction in solution via transmetalation with the PhSnCl3, followed by reductive elimination to generate the final product and regenerate Pd0 atoms in the reaction mixture. The fate of these metal atoms remains unclear; however, three processes are possible: (1) The metal atoms can continue back through the catalytic cycle; (2) the metal atoms can redeposit onto the remaining Pd4-capped particles in solution; or (3) the free Pd0 can aggregate to form bulk Pd black. One interesting capability/application of the Pd4-capped Pd nanoparticles is their ability to drive low-temperature catalytic selectivity. Pacardo et al. demonstrated that the nanoparticles can drive the Stille coupling of aryl iodides at room temperature; however, slightly elevated temperatures of 40

Figure 39. Proposed leaching mechanism for Stille coupling using peptide-capped Pd nanoparticles. In the first step, oxidative addition causes Pd leaching from the nanoparticle surface. Transmetalation and reductive elimination subsequently occur in solution. Multiple pathways for the leached Pd atom upon reaction completion are possible. Additional research is required to determine the final fate. Reprinted with permission from ref 75. Copyright 2015 Royal Society of Chemistry.

°C were required to drive coupling at aryl bromides.356 Using this sensitivity to temperature, the ability to selectively react with iodo-based substrates in solution over bromo-based reagents was demonstrated. To this end, when a mixture of 4-iodobenzoic acid, 4-bromobenzoic acid, PhSnCl3, and the Pd nanoparticles was allowed to react at room temperature, the iodo-containing substrates rapidly reacted to form the biphenylcarboxylic acid product while the 4-bromobenzoic acid reagent remained stable in solution. Once the first reagent was consumed, heating of the reaction system to 40 °C caused rapid reactivity from the remaining brominated molecules in solution to produce the final product.356 If the same reaction mixture was studied under an initial temperature of 60 °C, reagent selectivity was completely lost where both the iodoand bromo-based substrates reacted simultaneously. Furthermore, it was also demonstrated that intramolecular selectivity could also be achieved using the Pd4-capped nanoparticles;356 when 3-iodo-5-bromobenzoic acid was employed as the substrate, coupling at the iodo group preferentially occurred over the bromo-substituent at room temperature. Beyond C−C coupling reactions and olefin hydrogenation, recent studies from Chen and colleagues have demonstrated that the Pd4- and Pd4 mutant-capped Pd nanoparticles are also quite reactive for electrocatalytic ORR.358 ORR is a key reaction required for fuel cells where extensive efforts have been made to enhance catalytic capabilities for this reaction. In this study, the researchers exploited the Pd4 peptide and cysteine containing mutant sequences discussed above to fabricate peptide-capped Pd nanoparticles to probe their catalytic efficiency for ORR. In general, similar sequence effects were observed for the ORR reaction as compared to Stille coupling where the sequence played an instrumental role in controlling the electrocatalytic process.358 To this end, the Pd nanoparticles capped with the C11 and A6C11 demonstrated the most efficiency for electrocatalytic ORR, while the C6, C6,11, and C6A11 displayed intermediate efficiency. Remarkably, the 12677


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particles displayed the most Au at the nanoparticle surface.3 Such a result corresponds with the known affinity of the peptide for Au. As the amount of Au in the sample increased, Pd surface enrichment was generally observed, suggesting that the peptides preferentially pulled the Pd atoms to the surface over the Au. Once the structures of the different materials were confirmed, they were used as electrocatalysts for the methanol oxidation reaction.3 As anticipated, the bimetallic peptidecapped nanoparticles demonstrated enhanced catalytic efficiency over their monometallic Pd counterparts. To this end, using the particles generated with a Pd/Au ratio of 3:1, the Pd4-capped particles were the most efficient; however, the AuBP1- and H1-capped species demonstrated minimal reactivity. As the amount of Au in the sample increased to the 1:1 ratio, the catalytic efficiency of the materials shifted wherein the Pd4- and AuBP1-capped particles were moderately reactive.3 Interestingly, a shift in the potential was observed for these materials for the reaction, likely arising from the increased amount of Au at the particle surface. A further voltage shift was observed using the particles prepared at a Pd/Au ratio of 1:3, as anticipated. For these particles, the Pd4- and AuBP1-capped species were reactive, while the H1-capped materials remained generally not reactive. Surprisingly, the H1-capped nanoparticles demonstrated negligible reactivity regardless of the Pd/Au ratio employed in the synthesis, while the Pd4 and AuBP1 particles were typically reactive at some level.3 Multidomain peptides have also been exploited by Naik and co-workers for the fabrication of multicomponent nanocatalysts.69,70 In their initial work, they used the previously described FlgA3 peptide for the generation of bimetallic AuPd nanoparticles.70 In this system, the researchers fabricated Au nanoparticles using the peptide where the Au-binding A3 domain was anticipated to be bound to the Au surface. Introduction of Pd2+ ions and their subsequent reduction resulted in the deposition of catalytically active Pd nanoparticles onto the Au surface. From this, a Au core Pd shell-type structure was prepared, all of which was generated via the control of the biointerface. TEM imaging of the materials clearly demonstrated the composite material structure, which was highly reactive for the hydrogenation of 3-buten-1-ol.70 Analysis of the reactivity of the bimetallic peptide-capped nanoparticles demonstrated a 2-fold enhancement in TOF values as compared to monometallic Pd particles, all due to the bimetallic effect on the electronics of the system making the AuPd structures more reactive.70 In a second system, again using the FlgA3 peptide, Naik and colleagues generated CdS nanoparticles surface-decorated with Pt nanoparticles.69 For this system, a cysteine residue was appended to the C-terminus of FlgA3 (termed FlgA3C) for binding to the CdS material. Once generated, Pt2+ ions were reduced at the sulfide material surface, producing the multicomponent materials.69 Remarkably, linear “raspberry”like materials were prepared with the Pt nanoparticles being presented at the biointerface of the CdS core structure. These materials demonstrated enzyme-like reactivity for the reduction of NO3− where CdS photoexcitation was employed to drive the reaction. The reactivity of the CdS/Pt structures was 23-fold higher than the reactivity for nitrate reductase, an enzyme with known reactivity for NO3− reduction.69 This effect arises from the intimate interaction between the two components allowing for rapid electron transfer and enhanced reactivity, all of which

parent Pd4-capped Pd nanoparticles presented the lowest degree of reactivity for ORR from all of the samples studied.358 Additional studies by Bedford et al.3 support the results of Chen and colleagues that indicate that the peptide sequence and the biointerface can alter the electrocatalytic functionality of peptide-capped nanoparticles. These researchers exploited the Pd426 and AuBP139 peptides with known Pd and Au binding affinity to generate bimetallic PdAu nanoparticles. Changing of the inorganic composition of nanoparticles is known to alter their catalytic functionality, where bimetallic materials can generate enhanced reactivity due to electronic changes as a function of composition and through geometric effects of the two metal atoms in the particle.366−374 In this study, the researchers designed a new peptide that combined the two anchoring halves of the AuBP1 peptide on Au and the Pd4 sequence on Pd to generate the H1 sequence (WAGAKRHPTLRHL).3 This was anticipated to enhance binding to the PdAu bimetallic species by maintaining characteristics of Au and Pd binding from the parent biomolecules. Using the AuBP1, Pd4, and H1 peptides, bimetallic PdAu nanoparticles were generated at selected Pd/Au ratios of 1:0, 3:1, 1:1, 1:3, and 0:1.3 Each system was able to generate peptide-capped bimetallic nanoparticles of ∼2 nm in size where the arrangement of the atoms in the structure appears to be dependent on the peptide sequence employed. Such information was accessed through high-resolution atomically resolved characterization of the nanoparticles via EXAFS, PDF, and computational analysis (Figure 40).3 For instance, all of the nanoparticles prepared with a Pd/Au ratio of 3:1 generally demonstrated surface enrichment of Pd regardless of the peptide sequence employed; however, the AuBP1-capped

Figure 40. Nanoparticle configurations of the peptide-capped PdAu materials as determined from RMC modeling of atomic PDFs for (A) AuBP1 (3:1); (B) H1 (3:1); (C) Pd4 (3:1); (D) AuBP1 (1:1); (E) H1 (1:1); (F) Pd4 (1:1); (G) AuBP1 (1:3); (H) H1 (1:3); and (I) Pd4 (1:3) samples. The values listed in parentheses indicate the Pd/ Au ratio employed to generate the materials. Reprinted with permission from ref 3. Copyright 2016 American Chemical Society. 12678


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reactivity was determined. In this regard, a contact score was calculated based on the enthalpic contribution of the peptidebinding event to the nanoparticle.2 In general, as the contact score increased, the activation energy of the reaction driven by the individual nanoparticle increased. This fits well with previous studies that suggested a correlation between Ea and the number of anchoring residues,64 which is a reflection of the enthalpic contribution of peptide binding to the Au surface. While peptide-capped nanoparticles have demonstrated intriguing reactivity, their biointerfacial structure remains static. In this regard, upon nanoparticle fabrication, the structure of the surface remains roughly constant, within standard equilibrium fluctuations. Recent studies from Lawrence et al. have demonstrated that the integration of non-natural moieties can be exploited to allow for remote manipulation of the catalytic properties of peptide-capped Au nanoparticles.376 In this regard, a non-natural azobenzene photoswitch was coupled into the peptide sequence at either an N- or C-terminal cysteine residue appended onto the Au-binding AuBP1 peptide.66,87 To distinguish between the structures, MAMCAuBP1 and AuBP1C-MAM denote the biomolecules with the azobenzene moiety (termed MAM) incorporated at either the N- or C-terminus, respectively. Both experimental and computational analyses have shown that the MAM molecule does not inhibit binding of the biomolecule to the nanoparticle surface and can be used to generate peptide-capped Au nanoparticles with diameters of ∼2.5 nm.66,87 On the basis of the isomerization state of the azobenzene (cis or trans), the biointerfacial structure on the nanoparticle surface can be selectively and reversibly manipulated between two different conformations (Figure 42).66,87,376 This is accessed via actuation of the azobenzene unit via optical illumination of the materials with light of an appropriate wavelength. Lawrence et al. reasoned that, because the biointerfacial structure can be directly and reversibly changed, the catalytic reactivity from the nanoparticle in the two distinct configurations would be different.376 In this regard, Au nanoparticles capped with the two biomolecules (MAM-CAuBP1 and AuBP1C-MAM) in the two configurations (cis and trans) were exploited for the catalytic reduction of 4-nitrophenol. This reaction was important as it was well-known to occur directly on the metal surface of the particle.375 Interestingly, when the reaction was processed at temperatures between 20 and 40 °C to calculate k values, the particles capped with the AuBP1CMAM peptide in the cis and trans forms were stable and generated the anticipated linear correlation of k as a function of temperature; however, the MAM-CAuBP1-capped particles were not stable, resulting in a nonlinear correlation. As such, activation energies could only be calculated for the AuBP1CMAM-capped Au nanoparticles in the trans and cis configurations, giving rise to Ea values of 23.0 ± 3.5 and 35.3 ± 4.0 kJ/mol, respectively.376 From this, the nanoparticles were substantially more reactive for the catalytic process using the peptide with the azobenzene in the trans configuration over the cis, suggesting that the biointerfacial structure is more conducive to reactivity in the trans morphology. Remarkably, the nanoparticles were highly recyclable for catalytic functionality both for multiple reaction cycles and for switching of the peptide conformation between the trans and cis states, demonstrating a highly robust and controllable system.376 This is a strong demonstration of how biointerfacial effects can significantly alter the catalytic functionality of peptide-capped

was achieved through material integration controlled by the peptide and the biointerface. Atomically resolved structure/function analyses have also been completed for peptide-capped Au nanoparticle catalysts.64 For these systems, however, the reaction is typically focused on the reduction of 4-nitrophenol to 4-aminophenol that is processed directly at the metallic surface.375 This work was initially studied by Li et al. using a peptide library originally designed to elucidate the binding effects of different peptide sequences to Au.64 In this regard, a variety of different peptides were exploited to fabricate Au nanoparticles in water, followed by their reaction analysis. The reduction of 4-nitrophenol was an ideal reaction as Au nanoparticles are highly reactive for this process and it is easily monitored using UV−vis spectroscopy. Using these spectroscopic data, pseudo-first-order rate constants (k) can be calculated for each nanoparticle catalyst.64 The reaction was processed at selected temperatures between 20 and 50 °C, from which activation energies (Ea) were calculated. Using the eight reactive peptide-capped Au nanoparticle catalysts, the Ea values ranged from 9.05 ± 0.1 to 25.6 ± 3.1 kJ/mol.64 While the nanoparticles were generally reactive for the reduction process, it appeared that the reactivity correlated with the number of anchoring residues of the peptide sequence to the Au surface. Additional PDF analysis of the peptide-capped Au nanoparticle catalysts provided enhanced understanding of their catalytic activity and the effects of the biointerface on the reactivity.2 Similar to the Pd nanoparticle PDF analysis, Au nanoparticle structures were assessed through a combination of experimental PDF and modeling analyses to provide a complete structure of the material from inorganic core to biological surface (Figure 41).2 From the atomic-level features accessed by the PDF-determined structures, a significant correlation between the peptide contacts to the nanoparticle to the

Figure 41. Structural information for selected peptide-capped Au nanoparticles as determined from PDF and modeling analyses using the indicated peptides as the capping agent. (a) Peptide as a spacefilling structure; (b) available reactive Au surface area. Reprinted with permission from ref 2. Copyright 2016 American Chemical Society. 12679


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numerous metal ion binding species would be present in the hydrophilic domain; thus, the R5 aggregate could serve as a biomimetic framework to template the production of inorganic materials. Jakhmola et al. used the R5 template for the production of Pd nanomaterials.379 In this regard, the peptide was allowed to assemble in solution to which varying amounts of Pd2+ were added to complex with the biomolecules. Upon complexation, reduction of the metal ions was processed using NaBH4. Initially, the materials were fabricated at Pd/peptide ratios of 60, 90, and 120 using a peptide concentration of ∼8 μM.379 Remarkably, as shown in Figure 43, the structure of the final

Figure 42. Reconfigurable biointerfacial switching for catalysis. (a) Scheme for the process where the biointerface structure is switched between two configurations via isomerization of an azobenzene unit integrated into the AuBP1 peptide. In one configuration, the reaction is more efficient as compared to the second configuration. (b) AuBP1C-MAM and MAM-CAuBP1 hybrid biomolecules employed to facilitate biointerfacial switching. Included is the contact score for each residue and the MAM unit of the biomolecule showing changes for each component as a function of the azobenzene isomer state. Reprinted with permission from ref 376. Copyright 2016 American Chemical Society.

Figure 43. TEM images of the (a) Pd60, (b) Pd90, and (c) Pd120 materials templated by the R5 framework. (d) High-resolution image of the Pd120 materials. Reprinted with permission from ref 380. Copyright 2011 American Chemical Society.

materials was highly dependent on the amount of Pd2+ loaded within the template.379 For instance, at a ratio of 60, spherical nanoparticles were observed with an average diameter of 2.9 ± 0.6 nm. As the ratio increased to 90, the inorganic structures became elongated to form short nanoribbon-like materials. As a measure of dimension, the width of the nanoribbons was 3.9 ± 0.8 nm on average. With further addition of Pd to the template, highly integrated nanoparticle networks (NPNs) were prepared at a ratio of 120. These materials were clearly aggregated structures of individual nanoparticles to generate the highly branched NPN morphology. The NPNs demonstrated an average width of 4.1 ± 1.2 nm.379 When additional metal was complexed with the peptide, rapid Pd black precipitation was evident, suggesting material saturation occurred at a Pd/peptide ratio of 120. Note that, to distinguish between the different materials prepared at the different Pd/peptide ratios, the samples will be denoted as Pd60, Pd90, and Pd120 where the number represents the ratio employed during synthesis. On the basis of the unique morphologies of the final materials, tuned as a function of the amount of metal loaded within the template, a controlled aggregation process was proposed (Figure 44).379,380 In this regard, at a low metal/

nanoparticles and provides potential pathways for dynamically controlling such properties from a single system. 5.2. Self-assembling Peptide Templates for Catalytic Materials

Natural systems rely on biomolecular assembly for the fabrication of functional structures such as the protein capsids of viruses30 or for proteins (e.g., ferritin).377 Kröger and colleagues originally isolated the silaffin peptides responsible for the precipitation of silica in diatoms.4,5 These peptides were heavily post-translationally modified structures, which eventually led to the identification of a second, nonmodified peptide termed R5 (SSKKSGSYSGSKGSKRRIL).4 The R5 peptide also retained the ability to precipitate SiO2 from solutions of silicic acid where it was dependent on peptide assembly to generate an aggregated structure in solution on the size of ∼800−900 nm (peptide concentration ∼8 μM).74,378,379 This aggregation event was suggested to arise from the C-terminal RRIL motif where the peptides assembled to put the isoleucine and leucine residues into a hydrophobic core, presenting the serine and lysine residues to solution.74 In this arrangement, 12680


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Figure 44. Proposed scheme for the R5-templated fabrication of Pd nanomaterials. The top and bottom present the synthesis at low and high Pd/ peptide ratios, respectively. Reprinted with permission from ref 380. Copyright 2011 American Chemical Society.

to react is increased in Pd90 over Pd120). As such, diminished reactivity could be anticipated from the Pd90 nanoribbons over the Pd60 nanoparticles and Pd120 NPNs.379,380 While the Pd60, Pd90, and Pd120 materials spanned the breadth of structures that were generated, Bhandari et al. expanded the number of ratios explored for this system.381 In this regard, the research team studied the production of the inorganic materials at Pd/peptide ratios between 60 and 120 at intervals of 10 units. This allowed for the observation of the evolution of the material morphology where slower changes from nanoparticles to NPNs as the ratio increased were observed at the different increments in the Pd/peptide ratio, as anticipated. In this study, the authors exploited the peptidetemplated Pd materials for the hydrogenation of allyl alcohol to generate 1-proponal where no difference in TOF values was observed as a function of material structures;381 all of the structures gave rise to a TOF value of ∼3000 mol product (mol Pd × h)−1.381 This lack of difference in reactivity was quite different than that observed for the same materials for Stille coupling and 4-nitrophenol reduction; however, the authors reasoned that the small substrate sizes (allyl alcohol and H2) were substantially small enough that substrate diffusion through the biotemplate did not affect reactivity.381 Additional hydrogenation analyses using various olefins employing the Pd60, Pd90, and Pd120 have been demonstrated where the TOF values for these substrates were dependent on substrate isomerization and not necessarily the overall molecular structure.382 Beyond Pd, the R5-template has been exploited for the fabrication of catalytically reactive Au,378 Pt,381 and bimetallic PdAu65 and PdPt.342 For all of the materials, the morphology of the structure was highly dependent on the composition of the material. For instance, using the R5 template, Au NPNs were prepared at Au/peptide ratios of 30 and 60.378 At higher ratios, bulk Au precipitation was noted; however, for the stable materials, no independent nanoparticles or nanoribbons were noted. These Au structures were polycrystalline, with average widths of 6.7 ± 1.1 and 7.1 ± 1.3 nm for the Au30 and A60 samples,378 respectively; thus, they were larger in dimensions than the Pd materials. These Au NPNs were catalytically reactive for the reduction of 4-nitrophenol to 4-aminophenol, where no substantial difference in reactivity based on structure was noted. In this regard, the Ea value for the reaction driven by

peptide ratio, upon reduction zerovalent Pd nanoparticles are generated in the sample. These particles are highly dispersed throughout the biological framework and are far enough apart to avoid aggregation. As the amount of metal increases, the density of nanoparticles within the template increases, thus diminishing the interparticle spacing and allowing the particles to aggregate. This aggregation event is likely to occur in a linear fashion due to the branched nature of the peptide template, resulting in nanoribbons at a ratio of 90 and NPNs at a ratio of 120 due to the extensive amount of metal loaded within the template at the highest ratio.379,380 These different materials were subsequently employed as catalysts for both Stille C−C coupling and 4-nitrophenol reduction.379,380 The materials were reactive for both catalytic reactions; however, the TOF values for the Stille coupling were notably lower than the values observed for the same reaction catalyzed by the Pd4-capped nanoparticles. To this end, using the Pd60, Pd90, and Pd120 materials to drive the Stille coupling of 4-iodobenzoic acid with PhSnCl3 to generate biphenylcarboxylic acid, TOF values of 452.4 ± 16.4, 334.3 ± 38.3, and 437.1 ± 14.3 mol product (mol Pd × h)−1, respectively, were determined.379 While these values are appreciably lower than the Pd4-capped materials discussed earlier, a unique trend of higher values for the Pd60 and Pd120 over the Pd90 was observed. Such a trend, on average, was noted for a variety of different substrates for Stille coupling, as well as for the reaction rates of the same three materials for the 4-nitrophenol reduction reaction.380 These differences in reactivity were attributed to the overall structure of the peptide-templated Pd nanomaterials.379,380 In this regard, for the Pd60, the nanoparticles are highly dispersed within the peptide template and unaggregated; thus, they are anticipated to present the greatest metallic surface area to solution. Conversely, for the Pd120, while the Pd materials are aggregated to generate the NPN structure, the greatest amount of metal is loaded into the template for these structures. As a result, the metal catalysts are likely to be pushed substantially closer to the template surface, thus minimizing the penetration depth these substrates must traverse through the template to react at the metal. For the Pd90 structures, both of these factors are negatively affected by the morphology (i.e., the nanoribbons are more aggregated than the Pd60 nanoparticles, thus having a lower surface area, and the penetration depth of the substrates 12681


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Figure 45. TEM analysis of the bimetallic PdAu nanomaterials templated by the R5 framework. Scale bar = 50 nm. Reprinted with permission from ref 65. Copyright 2015 American Chemical Society.

the Au30 sample was 29.0 ± 1.4 kJ/mol, while the value for the Au60 sample was 27.7 ± 1.6 kJ/mol.378 When the same template was employed to generate Pt nanomaterials, only spherical structures were generated, regardless of the metal/ peptide ratio.381 Subsequent X-ray-based analysis of bimetallic PdPt structures prepared in the same template suggested that only a small fraction of the Pt2+ in these structures was reduced,342 which likely gives rise to the lack of morphological differences in these structures due to the limited amount of Pt reduced inside the template. Using the Pt nanoparticles templated by the R5 framework, the materials were reactive for the hydrogenation of allyl alcohol; however, these reactions were substantially slower than those driven by the Pd materials with TOF values of ∼900 mol product (mol Pd × h)−1.381 Beyond heterogeneous catalytic processes, the R5-templated Au and Pt structures have also demonstrated reactivity for electrocatalytic O2 reduction where the morphology of the structure played an important role in controlling the reactivity.383 Because the R5 peptide is able to promiscuously bind and stabilize different inorganic material compositions, it has recently been exploited to generate bimetallic structures to probe compositional effects on reactivity.65,342 In this analysis, Merrill et al. were able to synthesize PdAu structures through a cocomplexation method.65 The peptide template was loaded with both Pd2+ and Au3+ at the same time. Upon reduction, bimetallic alloyed materials were generated, as confirmed by both EXAFS and PDF analysis of the materials.65 Additional TEM imaging and energy-dispersive spectroscopy (EDS) mapping confirmed the formation of the alloyed structures. For these materials, the metal/peptide ratio was maintained at 60; however, the Pd/Au ratio varied from 100% Pd to 100% Au. As shown in Figure 45, at a composition of 100% Pd (termed Pd100), spherical nanoparticles were observed. As the amount of Au in the sample increased, the morphology of the structures changed, whereby the materials became elongated at a 50:50 ratio of Pd/Au, to NPNs at higher Au concentrations,65 consistent with previous studies of the monometallic materials.378 Once these materials were fully characterized for

their structural morphology and atomic composition, they were exploited as catalysts for olefin hydrogenation. Regardless of the olefin substrate employed, enhanced reactivity was observed from the sample containing ∼30% Au,65 consistent with prior studies of bimetallic PdAu nanoparticles.367,384,385 In the R5templated materials, sufficient amounts of Au are present in the system to modulate the reactivity where the more electronegative Au pulls electron density from the Pd component to enhance the reactivity of the particles for olefin hydrogenation. In very recent work, Merrill et al. further studied the R5 framework for the generation of PdPt bimetallic catalysts.342 Again a cocomplexation process was studied where the formation of PdPt bimetallic alloyed materials was anticipated. Remarkably, the peptide template played an important role by controlling the reduction potential of the Pt2+ ions in the sample. For this system, the metal/peptide ratio was again maintained at 60 and the Pd/Pt ratio was varied from 100% Pd to 100% Pt. For all of the compositions, TEM imaging confirmed the production of spherical nanoparticles with average dimensions between 1.5 and 4.5 nm. These materials were extensively characterized by EXAFS, X-ray photoelectron spectroscopy (XPS), and PDF analyses, all of which consistently demonstrated Pt reduction that was dependent on the amount of Pd in the sample.342 At high concentrations of Pd, Pt2+ ion reduction was observed; however, as the amount of Pt2+ in the system increased, the quantity of oxidized Pt in the final material increased.342 In fact, when the materials were composed of only Pt, negligible levels of Pt reduction were observed. This effect was attributed to the binding of the Pt2+ to the amines of the peptide, which has been shown to shift the reduction potential, thus making it more difficult to reduce.386,387 As such, when Pd was in the system, it was rapidly reduced, thus serving as a seed crystal to drive Pt reduction. In general, the oxidized Pt species tended to be on the material surface, as anticipated based on the rates of metal ion reduction; however, the Pt metal that was reduced tended to form alloyed compositions with the Pd component.342 When these PdPt biotemplated materials were studied for olefin hydrogenation, enhanced reactivity was noted from the samples 12682


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that possessed 20−30% Pt over monometallic Pd;342 however, the degree of enhancement was not as dramatic as observed with the PdAu materials.

the adsorption via TEM imaging, the modified viruses were incubated at pH 10 and 80 °C to drive the condensation process, resulting in the encapsulation of the capsid in STO and nanowire fabrication.319 For these materials, their final structures were fully confirmed via TEM and XRD analysis. Once prepared, the viral templated STO structures were exploited to drive photocatalytic reactions. For this system, photocatalytic water reduction for the evolution of H2 was studied, where Pt nanoparticles were deposited on the STO as cocatalysts.319 Using this system, H2 gas was rapidly evolved where the phage-templated structures were substantially more reactive than commercially available titania and STO powders (10-fold enhancement).319 The authors reasoned that the reactivity was greatly enhanced due to the small nanoparticle size of the STO materials on the viral capsid. This allowed for optimized reactive surface area presentation to drive a more efficient reaction as compared to the commercial structures. Interestingly, Nuraje et al. subsequently demonstrated that sample treatment of the STO materials at temperatures between 600 and 700 °C under a continuous flow of ammonia allowed for selectable degrees of nitrogen integration into the STO materials.388 Photocatalytic H2 evolution analysis using these nitrogen-doped structures, with Pt cocatalysts, displayed enhanced reactivity with structures that contained 2.7−3.8% N in the sample.388 Beyond reductive-based reactions, Belcher and co-workers have designed important phage-based catalysts for oxidative reactions. For instance, this team has generated IrO2 nanowires with an embedded photosensitizer.51 To this end, Nam et al. incorporated an IrO2 binding peptide (AGETQQAM), identified via phage display, to the pVIII major coat protein of the M13 bacteriophage. Prior to oxide generation, the photosensitizer ZnDPEG (Zn(II) deuteroporphyrin IX 2,4ethylene glycol) was chemically coupled to the phage filament. Once coupled and confirmed, IrO2 deposition was processed. For this, sodium hexachloroiridate reacted with citrate in solution to hydrolyze the compound in the presence of the modified phage. This resulted in deposition of IrO2 at the peptide-binding sites, leading to nanowire formation.51 These composite materials were subsequently exploited as catalysts for water oxidation, leading to substantial O2 production. Using these materials, very high turnover rates (∼0.85 s−1) and turnover numbers (∼790) were observed for O2 evolution, which were much higher than control systems.51 This high degree of reactivity was suggested to arise from the structure of the materials that positions the IrO2 component in close proximity to the photosensitizers, where this reactivity was found to be dependent on the thickness of the IrO2 layer. In a separate study, Lee et al. exploited the M13 phage to make core@shell bimetallic nanowire electrocatalysts.390 For this, the researchers incorporated a Au-binding peptide into the pVIII major coat protein (VSGSSPDS), where this new phage was denoted as p8#9. By incorporating this peptide, the authors were able to deposit Au nanoparticles along the phage filament to generate Au nanowires (Figure 47).390 To grow the materials, the p8#9 bacteriophage was incubated with Au3+ ions in the presence of the surfactant cetyltrimethylammonium bromide (CTAB),391−395 which is a known surfactant used for Au nanomaterial synthesis. The growth of the metallic nanowires can be observed spectroscopically, which demonstrated the reduction of the Au3+ to Au+. This was followed by complete reduction to Au0 and nucleation of individual Au nanoparticles, followed by the formation of Au nanowires as

5.3. Virus-Based Nanoparticle Catalysis

Belcher and colleagues have made extensive efforts for the fabrication of bioinspired nanomaterial catalysts for both H2 evolution and oxidation reactions.51,319,388−390 For these systems they exploited the pVIII major coat protein of the virus for the incorporation of inorganic materials. As such, the team is able to deposit inorganic materials along the long axis of the filamentous phage, thus generating catalytically reactive nanowire materials. In initial work, Neltner et al.389 were able to deposit Rh− Ni@CeO2 nanomaterials directly onto the M13 phage filament. To achieve this, the pVIII major coat was modified to express an AEEE peptide sequence used to adsorb the materials onto the surface.389 These structures were calcined at 400 °C to remove the virus component. Imaging of these materials as compared to control structures demonstrated dramatic differences (Figure 46).389 When no phages were present, bulk

Figure 46. TEM imaging of Rh−Ni@CeO2 materials prepared with (a) 0, (b) 107, (c) 1010, and (d) 1013 phage/mL in the reaction. Note the difference in the phage-free control (a) and the reactions with the biotemplate (b−d). Reprinted with permission from ref 389. Copyright 2010 American Chemical Society.

aggregated materials were generated; however, the phagetemplated structures were well-dispersed, even after calcination to remove the virus. These materials were subsequently exploited for the steam reformation processes for the generation of H2 from a mixture of air/EtOH/water/Ar (1.7:1:10:11). From these materials, 100% EtOH conversion was observed at a low temperature of 300 °C where 60% of the product stream was H2.389 Nuraje et al. also used the M13 phage modified on the pVIII coat protein with the AEEE sequence to generate viruses coated with strontium titanate (STO).319 Specifically for the STO, ethylene glycol precursors of the materials were allowed to adsorb onto the negatively charged virus. Upon confirmation of 12683


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Figure 47. Fabrication of Au@Pt core@shell nanowires using the p8#9 phage. (a) Synthetic scheme to generate the materials. (b and c) Au core before (b) and after (c) Pt deposition to generate the core@shell structures. (d) UV−vis absorbance of the materials; (e−g) elemental mapping of the materials via EDS. For this, Au is red, Ag is blue, and Pt is green. Note that a small amount of Ag is present in the Au core. (g) Diagram of the anticipated colors due to metal overlap. Reprinted with permission from ref 390. Copyright 2012 Royal Society of Chemistry.

5.4. Challenges and Future Opportunities in Nanoparticle Catalysis

additional materials were generated along the phage surface. Through judicious selection of the reagent concentrations, the thickness of the nanowires could be selected from 10 to 50 nm in diameter.390 These monometallic Au nanowires demonstrated reactivity for electrocatalytic CO oxidation. Of note, the 40 nm thick wires demonstrated enhanced reactivity (1.2 mA cm−2 at 0.65 V vs reversible hydrogen electrode (RHE)) over materials with diameters of 20 and 30 nm (∼0.1 mA cm−2 at 0.65 V vs RHE).390 The authors reasoned that such differences likely arise from differences in the Au facets presented on the thicker wire as compared to the thinner materials. Using the Au nanowires templated by the peptide-modified p8#9 phage, the authors subsequently deposited Pt metal onto the Au surface to generate a core@shell bimetallic material.390 To do this, Pt4+ ions were adsorbed onto the Au metal and eventually reduced using ascorbic acid. The thickness of the new Pt metal shell could be readily controlled by the amount of Pt added into the reaction mixture. Figure 47 presents both the synthetic method and an analysis of the materials before and after Pt deposition, demonstrating the remarkable core@shell structure of the nanowires.390 Once prepared, the Au@Pt materials were exploited as electrocatalysts for the ethanol oxidation reaction. These bimetallic materials demonstrated remarkable activity that was substantially enhanced as compared to a Pt/C control system. To this end, the phagetemplated structures displayed reactivity that was 5−6.5 fold greater than the bulk control catalyst, as determined by the Au/ Pt metal ratio used to fabricate the bimetallic materials.390

The use of biomimetic methods for the fabrication of nanoparticle catalysts poses specific challenges but promises great potential for future applications. In general, as with most nanoparticle catalytic systems, the structure at the particle surface is critically important in controlling the reactivity. Peptides present fantastic opportunities to address this structural level of control via alternative pathways from traditional alkyl thiol interfaces. For peptide-based systems, the use of noncovalent interactions to generate the biointerface allows for locally weak, but collectively strong, connections between the biomolecules and the particle surface. As such, these interactions could be selectively manipulated to facilitate catalytic reactions without destabilizing the colloidal suspension; however, little research in this direction has been published presenting such capabilities. Beyond basic reactivity capabilities, the surface-exposed biointerface also controls the selectivity of these structures. Tuning of the biointerface could be exploited to control reagent selectivity for peptide-capped materials; selectivity based on reagent size, charge, structure, solubility, etc. could be accessed via tunable surface structures. From these opportunities for catalysis by the biointerface, the basis comes down to controllable surface structures of the peptide-capped nanoparticles. Such surface structures are critically important, especially for catalysis where reactive atoms tend to be surface defects that could be programmed into the material, based on the peptide sequence. As such, new opportunities are possible for the a priori design of peptide 12684


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Figure 48. Bacterial adhesion on bare and TiBP1-Spacer-AMP peptide-modified titanium surfaces against Streptococcus mutans (left column), Staphylococcus epidermidis (middle column), and Escherichia coli (right column). Adapted with permission from ref 93. Copyright 2016 American Chemical Society.

6.1. Peptide-Based Surface Coatings for Implant Materials

sequences that not only stabilize the particle but also confer controllable catalytic reactivity. This could be achieved by the incorporation of reactive defect atoms via peptide/metal binding; however, other interactions are possible. This also requires the ability to predict surface structures based on the peptide sequence. At present, such capabilities are not possible but could be realized with additional research efforts on both individual peptide sequences, as well as large libraries of peptides where a correlation between atomically resolved structures of the particles (from inner core to peptide biointerface) and the catalytic process are required. This would likely necessitate strong collaborations between experimentalists and computational modelers as current analysis instrumentation is not readily available to probe such critically important atomic-level features. A burgeoning area of nanocatalysis research is the use of bimetallic and multimetallic materials for reactivity, where only a recent number of papers have employed peptides to generate such functional structures. Enhanced catalytic function from these materials, as discussed earlier, arises from the synergistic interactions between two or more metals in the particle, where metal atomic arrangements are key to accessing such capabilities. This atomic-level arrangement appears to be a fruitful area of research to be explored using peptides. In this regard, the ability to control atomic arrangements could be possible using peptides with specific affinities. For instance, core@shell structures could be achieved wherein the peptide may pull one metal to the particle surface, thereby sequestering the second metal into the core, based on the peptide affinity. While such capabilities are currently speculative, they could be achieved with additional research efforts, leading to additional long-term catalytic capabilities, all accessed via biointerfacial structures controlling material properties.

The noncovalent surface modification of implant materials was one of the earlier examples of exploitation of materials-binding peptides, with the goal of generating bioactive coatings that would facilitate a positive biological response from the host, such as osseointegration. While some earlier studies focused on the generation of passive, fouling-resistant biomedical surfaces,396−398 a more ambitious goal has been to devise surface coatings that can elicit and direct the complex cascade of biomolecular cues that can produce a bioactive interface that, for example, can facilitate integration into the host tissue or help resist infection at the implantation site. The central concept in these studies is the use of bifunctional (also referred to as chimeric) peptides (or peptide/protein constructs) containing at least two domains: one domain comprising a materials-binding sequence (relevant to the implant material surface) and the other domain comprising a peptide sequence (or a protein) that retains biological activity (e.g., that can direct cell adhesion and/or facilitate cell proliferation or discourage/kill bacterial pathogens). One of the earliest examples of this strategy was reported by Belcher and co-workers in 2005, who used phage display to identify peptide sequences with strong binding to the surface of a conducting polymer, chloride-doped polypyrrole (PPyCl).399 These authors isolated the PPyCl-binding peptide and constructed a bifunctional entity by conjugating the C-terminus of the PPyCl peptide to a sequence that promoted cell adhesion; their in vitro assays indicated that cell adhesion (PC12 cells) did indeed occur on the peptide-treated PPyCl surfaces relative to the untreated substrates. Interestingly, these authors indicated that the PPyCl-binding sequence was sensitive to the dopant type (in this case, chloride). Despite this promising start, however, to date the use of phage display and the subsequent construction of engineered bifunctional peptides have unfortunately not yet been extended to the study of any other organic conducting polymer (OCP) materials of relevance to bionics and nerve-regeneration applications. This might be due to the challenges in the processing of these OCP materials, particularly in terms of generating structurally and morphologically consistent target substrates. Considerable opportunities exist in this space to make transformational

6. BIOMEDICAL TECHNOLOGIES The use of biocombinatorially identified materials-binding peptides offers enormous promise in the realm of biomedical technology and has been the subject of considerable exploration over the past decade. Particular attention has been focused on the areas of surface engineering of tissue implant materials, regenerative medicine, imaging and diagnostics, and therapeutics, as discussed herein. 12685


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molecule were found to both resist fibronectin adsorption and bacterial (Staphylococcus aureus) colonization in vitro.406 Building on these early pioneering works, Sarikaya and coworkers explored the use of such chimeric peptides for the purposes of creating both bioinert surfaces (via coating substrates with materials-binding-peptide/PEG constructs) and cyto-compatible surfaces (by attaching RGD to the materials-binding peptide),397 using Au, Pt, glass, and titania substrates. The PEGylated-peptide surface coatings (based on three different Au-binding sequences) were applied to the Au substrate. A key finding was that the coverage (and therefore the potential effectiveness) of the coating was dependent on three factors: the materials-binding sequence, the PEGattachment point on the peptide, and the number of tandem repeats of the materials-binding sequence. These authors reported successful creation of antifouling surfaces for both Au and Pt substrates. Their bioactive peptide-RGD coatings based on glass and titanium (titania) substrates were shown to be effective in both cell adhesion and cell spreading assays, using NIH 3T3 mouse embryonic fibroblasts. This work demonstrated that the design of the chimeric peptide can be very influential in the successful realization of these interfacial properties. Following earlier successes in creating chimeric protein− peptide hybrids based on naturally occurring mineralization peptides to mineralize recombinant silk,407,408 Kaplan and coworkers409 reported a mineralization strategy using chimeric peptide/protein constructs that attached a Ag-binding sequence identified from phage-display experiments (Ag-4)25 to a silk protein. This novel strategy generated new antimicrobial biomedical materials that incorporated the attractive mechanical properties, ease of aqueous processing, and biocompatibility of silk. These peptide/protein chimeras were found to foster the nucleation and growth of Ag nanoparticles in the silk matrix, with a narrow size distribution. The resulting Ag/silk hybrid materials were found to inhibit the growth of both S. aureus and E. coli bacteria. Mineralization of solid implant substrates, via use of chimeric peptides, has been recently explored in a few scenarios. For example, Gitelman and Rapaport410 used a chimeric peptide as a mineralizing agent to explore strategies for improving the bonding between orthopedic implants and the host tissue. These authors constructed a chimeric peptide comprising a Tibinding sequence and a mineralization domain, designed to promote formation of calcium phosphate materials. Their assays showed this peptide coating on the titanium substrate not only promoted the adsorption of calcium and phosphate ions but also supported improved adhesion and spreading of human fetal osteoblast cells relative to their controls. In a similar vein, Hashizume411 and co-workers used bifunctional peptides to noncovalently modify poly(ether imide) (PEI) substrates, to encourage the deposition of hydroxyapatite (HAP). The chimeric peptide comprised a fusion of a PEIbinding domain (denoted p1), as identified from phage-display experiments reported by Serizawa and co-workers,412 and a HAP-binding peptide, identified from phage-display experiments reported by Sarikaya and co-workers (HABP).413 Serizawa and co-workers chose the C-terminus of p1 as the attachment point for HABP, based on previous work regarding the performance of p1-based chimeric peptides in general. Nonetheless, the p1-HABP peptide was found to perform best as an immobilizer of preformed HAP particles, rather than as a mineralization agent.

advances in both of these research areas, via the identification and use of new, OCP-binding peptides. The titanium surface was another focus of early developments in the field of implant surface engineering. Under physiological conditions, titanium naturally oxidizes to form a titania layer, which comprises the target substrate. The phagedisplay experiments reported by Shiba and co-workers400 identified the hexapeptide TBP-1 as an effective titania-binding sequence. Shiba and co-workers subsequently exploited this discovery by inserting TBP-1 at either terminus of the bone morphogenic protein (in its mature form, denoted BMP-2).401 These authors demonstrated that this conferred effective and reversible immobilization of BMP-2 on titania surfaces, while the biological function of the TBP-1-modified BMP-2 in the immobilized state was maintained via their in vitro experiments. While demonstration of in vitro viability is a key step in developing materials-binding peptides for biomedical purposes, it is also critical that the utility of this approach can be demonstrated as highly effective in vivo. Several years later, these authors took this important step of showing that this protein/peptide construct could induce the spatially localized formation of bone-like tissue at the implant/tissue interface in living hosts.402 Shiba and co-workers also showed how the minTBP-1 hexapeptide could be used to prevent the formation of biofilms on titanium implant surfaces.403 In contrast to PEG-based strategies, these authors realized this goal by covalently attaching antimicrobial peptides to their minTBP-1 peptide. Their assays revealed a diminished propensity for biofilm formation for surfaces treated with these chimeric molecules (tested for a specific peridontopathic bacterium, P. gingivalis). Along similar lines, Tamerler and co-workers93 have recently shown how the adsorption of chimeric peptides to titanium grade V implant material could substantially reduce the adhesion of three types of bacteria that are common to complications with orthopedic implants, S. mutans, S. epidermis, and E. coli (Figure 48). The titania-binding peptides used in these chimeric molecules were selected from both phage display and cell-surface display approaches, while the antimicrobial domains were mined from the literature. This study also made use of knowledge-based approaches for predicting the secondary structure of these chimeric peptides, although these structural predictions were not verified via experimental analysis or explored using molecular simulations. As part of a follow-up study, Tamerler and co-workers404 reported results of CD spectroscopy to probe structure of chimeric peptides in solution (but not when adsorbed at the titanium interface). These authors also made limited use of molecular simulation to explore the structures of the in-solution (not surface-bound) peptides; however, the utility of their findings in this respect was restricted by the limited simulation protocols used in this work. The titanium substrate was also the focus of work by Grinstaff and co-workers, who used their own phage-display experiments to isolate titania-binding peptide sequences. In earlier work Grinstaff and co-workers conjugated Ti-binding peptides to the integrin-binding motif RGD (and variants).405 Ti substrates coated with these molecules were found in vitro to promote endothelialization (using human umbilical vein endothelial cells). In a separate study, these authors covalently linked one of their Ti-binding sequences to polyethylene glycol (PEG). Ti substrates coated with this PEGylated-peptide 12686


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Figure 49. Schematic illustration of molecular mechanisms underlying the antimicrobial activity of HBAMP. HBAMP may damage bacterial cell membrane by disrupting lipid bilayer ①, translocate into cell interior ②, and interact with intracellular targets, which result in regulation of certain genes that control growth, transition, and biofilm formation ③. (A) HBAMP bound on tooth surface; (B) HBAMP free in saliva. Reprinted with permission from ref 418. Copyright 2016 Nature Publishing Group.

approach necessarily place severe constraints on the utility of these structural findings. The antimicrobial studies summarized earlier have been chiefly focused on Ti surfaces due to the strong effort to date on surface treatments of orthopedic implant materials. However, these chimeric peptide approaches also have bright prospects in oral healthcare. To illustrate this, a strategy based on chimeric peptides to prevent formation of pathogenic biofilm formation on tooth surfaces was very recently reported by Gong and co-workers, who used a bifunctional peptide denoted HBAMP (Figure 49).418 This chimeric peptide comprised two domains: a hydroxyapatite (HAP)-binding domain and a synthetic broad-spectrum antimicrobial sequence, KLSW (KKVVFWVKFK). The HAP-binding sequence was determined by earlier phage-display experiments reported by Mao et al.419 Gong and co-workers assayed the growth of four oral planktonic bacteria, S. mutans, S. sanguinus, A. viscosus, and L. acidophilus. Promisingly, this approach showed encouraging results on HAP targets (not actual tooth surfaces), inhibiting biofilm formation, while retaining stability in saliva and also supporting cyto-compatibility, as assayed with the attachment and proliferation of human gingival fibroblasts. However, very little is currently known regarding the function of this approach in vivo, nor is there much known about the structural details of this HAP/peptide interface. The generation of structure/ property relationships for HAP-based surfaces, and the in vivo performance evaluation of these chimeric peptides, should be a key priority in the future.

Polystyrene substrates were extensively studied by Grinstaff and co-workers. This team initially exploited polystyrenebinding sequences isolated from phage display in the generation of peptide-PEG conjugates to create nonfouling surfaces.396 Conjugation of these polystyrene sequences to integrin-binding motifs was successfully demonstrated not only for promoting endothelialization but also for enabling delivery of therapeutics via enzymatic release.414 Grinstaff and coworkers most recently extended this bifunctional peptide approach to polystyrene stent coatings that could selectively promote proliferation of endothelial cells while preventing platelet adhesion.415 In this work, these authors made use of a polystyrene-binding peptide covalently attached to the integrinbinding motif (RRETAWA). Note that these authors did not use the commonly exploited RGD motif (widely used in orthopedic applications) because this tripeptide lacks the ability to differentiate between adhesion of endothelial cells and platelets, which is an undesirable trait for cardiovascular implant materials. The use of chimeric peptides to promote cell adhesion on Au surfaces (as opposed to antifouling surface treatments, as described earlier) was recently reported by Netti and coworkers.416 These authors made use of a Au-binding peptide isolated from previous417 biocombinatorial selection experiments and covalently attached this to a bioactive domain, of which two different sequences were considered: GRGDS and IKVAV. The influence of the attachment point of the bioactive domain (either at the N- or C-terminus of the Au-binding sequence) was also explored. The surface density of attached human dermal fibroblast cells on the Au substrate was improved when the chimeric peptides were used, particularly when the bioactive domain was attached at the N-terminus. In this instance, the authors reported the use of molecular simulations; however, again, the limitations to their simulation

6.2. Materials for Regenerative Medicine

In a complementary counterpoint to implant material applications, chimeric molecules based on materials-binding peptides also show exceptional promise in the realm of tissue regeneration. Bone regeneration via the modification of silk matrices has been a chief target of the work of Kaplan and 12687


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Figure 50. Schematic representation of the folding, self-assembly, and resultant hydrogelation of MDG1, cMDG1, and MAX8 peptides. Sequences of the three peptides are shown. Reprinted with permission from ref 425. Copyright 2010 Elsevier.

colleagues.420−424 Motivated by success in creating biodegradable osteo-inductive matrices by combining silica nanoparticles with silk fibroin,421 Mieszawska et al.420 demonstrated that fusion of the silaffin-derived silica-binding peptide (R5) with the self-assembling domain of dragline silk protein (from Nephila clavipes) led to the nucleation and growth of silica nanoparticles dispersed on the surface of the silk substrate, with controllable silica loadings. These authors successfully demonstrated the bone regenerative potential of these silk/silica substrates via observations of the adhesion, spreading, and differentiation of human mesenchymal stem cells (hMSCs) adsorbed on these hybrid supports. Recently, Perry and coworkers investigated the influence of connection point of the silica-binding peptide, located at either the N- or C-terminus of the silk protein.423 Although both chimeric constructs supported cell viability and differentiation of hMSCs in vitro, the N-terminal location of the silica-binding sequence supported a higher potential to induce silica growth, which translated into a greater propensity to promote hMSC differentiation. Recently, Kaplan and co-workers424 extended this approach to create fusions of the spider-silk inspired domain with a HAP-binding sequence, and again, these authors explored the impact of fusing the peptide at either the C- or Nterminus, or both, on the formation of crystalline HAP. The use of chimeric biomolecules has also been applied to hydrogels for creating new tissue-regeneration scaffolds. Sarikaya and co-workers425 created a fusion of a hydrogelforming peptide (MAX8)426 with a hydroxyapatite-binding peptide (HABP1) identified from phage-display experiments.413 MAX8 is known to form Ca2+-triggered hydrogels that are cyto-compatible. These authors connected HABP1 at the C-terminus of MAX8 (denoted MDG1) and also explored control systems in the form of MAX8 alone and a hybrid comprising the reversed HABP1 sequence attached to the Cterminus of MAX8 (denoted cMDG1). Only the MDG1 chimeric peptide was found to induce crystallized HAP in the hydrogel matrix (Figure 50), with both controls yielding poorly crystalline forms. Mouse cementoblast cells were used to assay the MDG1-derived hydrogel for cell viability, with indications that the cells could direct subsequent mineralization of the hydrogel network.

In contrast to the use of bifunctional peptide/protein constructs, Sarikaya and co-workers427 used information from knowledge-based approaches and HAP-binding sequences identified from phage-display experiments to create amelogenin-derived peptides (ADPs) for the purposes of tooth regeneration. One peptide, ADP5, was reported to facilitate cell-free mineralization of a cementum-like HAP layer on bare human root dentin. This “cementomimetic” layer featured comparable mechanical properties likened to native cementum that could support the attachment and growth of human periodontal ligament (hPDL) fibroblast cells in vitro, relative to unmineralized controls. Interestingly, ADP5 was not identified to be one of the strongest binders to HAP surfaces, indicating that materials-recognizing peptides for regeneration and growth applications may be better identified via tests other than those merely probing binding affinity (e.g., from growth kinetics assays). In summary, the utility of materials-binding peptides in regenerative medicine shows enormous promise, and currently there appears to be tremendous scope for developing these strategies in the future. 6.3. Peptide-Materials Recognition for Medical Imaging and Therapies

The ability to image the location of therapeutics, and to image both cells in vitro and tissue in vivo, is an indispensable technique for advancing medical science. Ideally, the optimal bioimaging label should be brilliant; be biocompatible; be physically, chemically, and photostable in biological milieu; offer high sensitivity and a high signal-to-noise ratio; resist photobleaching; and operate at deep tissue penetration. Fluorescent dyes and proteins, and nanoparticle-based approaches (such as semiconducting quantum dots (QDs)), comprise traditional and widely used solutions to achieving such biolabeling and imaging. However, fluorescent dyes and proteins can suffer from limitations, namely, photobleaching, low signal-to-noise due to background autofluorescence, short penetration depth into tissue (due to reliance on UV excitation), and resultant tissue damage due to long-term exposure to this UV radiation. QDs also suffer limitations from reliance on UV excitation and additionally may be cytotoxic and chemically unstable in living tissue. These limitations become particularly acute when applied to imaging of challenging in vivo scenarios, such as the neuroimmune system.428 As an 12688


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Figure 51. In vivo imaging of rats: QDs injected into the abdomen (a); UCNPs injected below the abdominal skin (b). Adapted with permission from ref 429. Copyright 2011 Elsevier.

Figure 52. Schematic illustration of (a) the fabrication of UCNP@SiO2(RB) and its functionality and (b) LPG-mediated bioconjugation of UCNP@ SiO2(RB) with antibodies and their application in targeted PDT. Reprinted with permission from ref 432. Copyright 2016 American Chemical Society.

workers,432 who created a fusion of a silica-binding peptide435 and the Streptococcus Protein G′ (an antibody binding protein, PG). This chimeric peptide/protein conjugate was shown to bind via the materials-binding domain to the exterior silica coating on the UCNP, where the externally presented protein was displayed outward and thus made available for antibody immobilization, which could subsequently specifically target cancer cells (Figure 52). These authors demonstrated the viability of this photodynamic therapy (PDT) approach to selectively target and kill human colorectal adenocarcinoma HT-29 cells in vitro. The synthesis of UCNPs with tightly controlled and consistent composition, size, and shape can be accomplished in organic solvents,436 while generation of particles of the same quality in aqueous media has yet to be reported. In contrast, several bioinspired approaches, making use of materials-binding peptides, have been exploited to produce individual QD nanoparticles of consistent size and quality under aqueous conditions, suitable for bioimaging purposes. This is opposed to the use of genetically engineered filamentous M13 phage to nucleate and grow QD nanocrystals on the pVIII protein coat to form semiconducting nanowires.58 Baneyx and co-workers437 reported a one-pot fabrication of biofunctionalized ZnS nanoparticles, via the use of ZnS-binding sequences identified from cell-surface display experiments. These authors inserted

alternative imaging agent, upconversion nanoparticles (UCNPs) doped with rare earth (RE) elements can address these limitations; they convert depth-penetrating near-infrared (NIR) radiation into visible light without incurring extensive tissue damage, they are both chemically stable and photostable, and they are not cytotoxic. UCNPs possess enormous potential not only for deep-tissue imaging,429 (Figure 51) but also for cell-targeted drug delivery, theranostics,430 diseased cell detection,431 and photodynamic therapy.432,433 However, a key challenge to fully realizing these exciting possibilities is the need to biofunctionalize the surface of these UCNPs. In the asproduced state, UCNPs suffer from agglomeration in aqueous media because they are typically capped with hydrophobic ligands such as oleic acid. Current strategies to inhibit this agglomeration include coating the UCNPs with a thin silica layer as well as ligand-displacement strategies, particularly those using phosphate- or phosphine-containing ligands including DNA, proteins, and peptides.434 Biofunctionalization of UCNPs with proteins or peptides can bring additional benefits in the form of targeting motifs. The use of chimeric peptide/protein molecules based on materialsbinding peptides comprises an exceptionally promising oneshot strategy to enable ligand displacement, prevent agglomeration, and provide biotargeting capabilities. Very recent first steps in this direction have been reported by Zvyagin and co12689


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one of these sequences into a fusion designer peptide (comprising the antibody-binding domain derived from S. aureus protein A, followed by the disulfide-constrained ZnSbinding peptide inserted into E. coli Thioredoxin A). This resulted in crystalline, optically stable ZnS nanoparticles with a narrow size distribution, decorated with the fusion protein. These authors also found that the particle-adsorbed fusion protein could further attach IgG antibodies to generate immune-QDs. Baneyx and co-workers339 have since optimized their designer protein construct to produce smaller, brighter ZnS nanocrystals. As an alternative approach, Gupta and coworkers438 made use of the P22 bacteriophage, which can be ∼60 nm in diameter. Genetic engineering can localize materials-binding peptides inside the viral cavity; in this instance, a CdS sequence derived from phage-display experiments was used, resulting in spatially confined CdS nanoparticles. UV−vis and photoluminescence measurements reported by these authors confirmed the suitability of such nanoparticles for bioimaging purposes. Going beyond the production of QDs, viruses engineered to display materials-binding peptides offers an alternative strategy to using chimeric peptides and peptide/protein fusions, particularly for achieving both cell-targeting and selective binding functionalities of the inorganic probe. Belcher and co-workers exploited the filamentous M13 phage to express materials-binding peptide sequences on the external pVIII coat of the virus and applied this to in vivo imaging of prostate cancer.439 To achieve this targeted imaging, the distal end (pIII coat) of the phage was also engineered to display a celltargeting SPARC peptide, while the contrast agent comprised presynthesized iron oxide nanoparticles that were assembled via the triglutamate motif expressed on the pVIII coat of the phage. SWNTs can also be used as bioimaging agents, due to their ability to fluoresce under NIR irradiation. Belcher and coworkers similarly used the M13 phage, engineered to present SPARC on the pIII coat and a SWNT-binding sequence334 on the pVIII coat, to create targeted NIR fluorescent cancer probes based on SWNTs.440,441 These authors demonstrated the use of these probes for the purposes of in vivo tumor delineation to provide surgical guidance for the excision of submillimeter tumors. In a similar vein, the SWNT-modified M13 phage was adapted by Belcher and co-workers,442 who replaced the SPARC peptide functionality with a peptide sequence that bound antibodies. This construct was successfully demonstrated to image bacterial infection in vivo, using mice infected with E. coli. The use of phage as a vehicle for the tandem presentation of both cell-targeting and material-binding functionalities was also recently reported by Nam and co-workers,443 who engineered the icosahedral T7 phage to display the Au-binding peptide sequence GBP112 on the exterior coat of the virus, together with a prostate cancer cell-targeting peptide. In particular, the virus-displayed Au-binding peptides facilitated localized clustering of the Au nanoparticles (as opposed to immobilization of single Au nanoparticles). This localized nanoparticle clustering, promoted by the GBP peptide, was an essential element to realizing cancer cell death via photothermal therapy under very low light irradiation (Figure 53).

Figure 53. Schematic illustration of cancer-selective photothermal therapy via prostate cancer-targeted intracellular delivery of T7templated AuNP nanoclusters, where T7 phages are genetically modified to display gold-binding and prostate cancer cell-targeting peptides on the viral surface. Reprinted with permission from ref 443. Copyright 2015 American Chemical Society.

and despite the exceptional progress and considerable body of work published to date, this area remains in its infancy. As regards developments for implant materials, the range of studies published to date indicates that chimeric peptide coatings, based on materials-binding peptides, hold great promise for realizing successful surface treatments for tissue implants. Such coatings have the capacity to inhibit pathogenic biofilm formation and to encourage the adhesion and proliferation of cells. Much of the emphasis to date has been on orthopedic implants, in which both discouragement of pathogens and the promotion of attachment/spreading of fibroblast cells are important and relevant. Two key areas for extension in this field are clear: (1) expansion of chimeric peptide implant-coating strategies to both non-Ti implant materials and other relevant hard tissue substrates (for instance, HAP-based substrates such as tooth enamel), and (2) extension into nonorthopedic implant scenarios (particularly in the cardiovascular realm, which brings additional challenges). Recent progress in these interrelated areas indicates emerging trends that, with further work, have substantial capacity to deliver transformative outcomes in healthcare technologies. In particular, it is clear that the design of the architecture of the chimeric peptide is central to optimizing the performance of this surface-treatment strategy. For example, it is unclear in many instances if the covalent attachment of a materialsbinding peptide to its counterpart domain (e.g., antimicrobial or integrin motif, etc) diminishes the performance of either function. Furthermore, this peptide−peptide fusion might cause a reduction in materials-binding specificity or even affinity for the materials-recognition domain. In some of the examples summarized above, a linker/spacer was positioned between the

6.4. Challenges and Future Opportunities in Biomedical Technologies

Overall, the possibilities for exploitation of materials-binding peptides in creating functional biomedical technologies are vast, 12690


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two domains. The refinement of optimal linker design is another open question ripe for combinatorial screening approaches and subsequent data mining. While molecularlevel structural details would provide key insights into these design aspects, in common with the majority of these biomedical studies summarized earlier, the structural abiotic/ biotic interface remains relatively unexplored by experimental characterization beyond some limited CD spectroscopy analyses.93,410 To date, published molecular-simulation data in this area have been hampered by limited protocols; insights from more sophisticated advanced molecular-simulation approaches have the capacity to provide future possibilities to address this challenge. Basic research to enable the successful and widespread translation of materials-binding peptides into the regenerative medicine space is a huge unmet need. Despite the exciting advances made to date, particularly for incorporation of materials-directing peptides into silk matrices, much of the fundamentals in terms of tuning the control of these interfaces via the use of chimeric peptides remain to be established. The exploration of other soft matter matrices, particularly hydrogels, functionalized with materials-directing peptides have only received very limited attention to date, particularly in terms of MD simulation efforts,444 and offer interesting and versatile possibilities to design multifunctional materials that can combine tissue regeneration with stimulus-responsive properties. In terms of imaging and targeted therapies, opportunities await for the adaptation of existing materials-binding sequences for new imaging applications as well as photothermal, photodynamic, and drug-delivery therapies. Such opportunities also exist for extending the applicability of targeted in vivo imaging, via the identification and characterization of materialsbinding peptides for new inorganic substrates, such as the rareearth doped UCNPs, for the purposes of realizing controlled biofunctionalization for these versatile nanomaterials. The resulting new imaging platforms arising from this research will enable critical advances in medicine in the areas of surgical guidance for tumor removal, early-stage cancer detection, cancer therapy, and the imaging of the central nervous system. To reach this point, substantial effort is required in elucidating the fundamental physics and chemistry that govern the structures and properties of these new biointerfaces.

Further applications of this peptide−materials interface are emerging as interesting and useful future directions for generating functional materials. In particular, impressive progress has been made for peptide-based sensor materials as detailed in the comprehensive review provided by Naik and co-workers.446 For example, Mannoor et al.447 reported the use of a chimeric peptide containing a graphene-binding domain and an antimicrobial sequence to create a wireless sensor for the presence of bacteria on tooth enamel. Another application with encouraging potential for exploitation is the use of engineered peptides to tether (and maintain) live cells to inorganic surfaces, to provide living biofilms, as reported recently by Stratis-Cullum and co-workers.448 In partnership with progress in experimental techniques, computational approaches are poised to accelerate the process of discovery, characterization, and, ultimately, design of materials-binding peptides across all application areas discussed here. Advances in computational techniques are much needed for data collection and generation, as is done using molecular dynamics simulations, for the purposes of elucidating connections between structural traits of these peptides and the physicochemical properties of the biointerface. However, the development of knowledge-based computational approaches lags behind the advances made in molecular simulation over the past decade, despite excellent and encouraging recent progress.261,52,449 Further developments in knowledge-based approaches are much needed, chiefly to mine existing characterization data in order to identify sequence traits that can deliver specific properties, but also to predict new sequences with desired multifunctional properties. The use of knowledge-based approaches could facilitate the targeted design of not only the peptides themselves but also the linkers (which may or may not be peptides) incorporated into chimeric peptide constructs. Nevertheless, regardless of the advances in techniques used to mine materials-binding peptide data sets, at a fundamental level the foundation for any knowledge-based approach is the database that connects a given peptide sequence with its binding affinity, molecular structures, and additional traits (catalytic, antibacterial, etc.). These data sets should ideally be the product of harmonized and consistent experimental and simulation protocols and standards. However, consensus on what form these protocols and standards should take is not clear at present; establishment of these guidelines would comprise a critical contribution to this field. The exploitation of knowledge on peptide−materials interactions has vast potential in a huge range of underexplored areas. For example, the ability to engineer living cells to realize in situ biosynthesis of inorganic nanomaterials450,451 with unprecedented levels of control is in relative infancy. Incorporation of materials-binding peptides into these in situ systems may provide a strategy to realize this degree of synthetic control. Furthermore, advances in new applications of materials-directing peptides await fresh developments, for example, in addressing energy-related problems beyond the current focus of battery storage and electrode materials (e.g., in the low-cost generation of carbon-capture and storage materials). The exploitation of materials-binding peptides have enormous translational potential to the food industry, particularly in contributing to the current revolution in foodbased nanoscience, to create foods with lower salt and fat content, while also maximizing flavor, consumer experience, and health benefits.452 Peptide-mediated nanotechnology also has the potential to make valuable contributions to improving

7. SUMMARY AND OUTLOOK The use of peptides as agents to recognize, functionalize, activate, and organize materials has developed and matured enormously, particularly over the past decade. The peptideenabled biointerface can, in principle, confer exceptional nanoscale-level control in the arrangement of nanomaterials, resulting in successful applications in catalysis, nanomaterials assembly, energy materials (particularly battery electrode materials), and biomedical materials. Nonetheless, the ability to expand the versatility of this peptide-mediated approach depends on our ability to elucidate and exploit structure/ property relationships of these biointerfaces. A key challenge to address this will be to advance experimental and molecularsimulation techniques to enable a clearer, more integrated characterization of the surface-adsorbed peptide structures. The techniques relevant to sequence screening and identification are also ripe for reappraisal, as was recently demonstrated by Wilke et al.445 12691


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our food security, e.g., via application of nanomaterials-based strategies to agriculture, particularly in improving crop viability in hostile environments, protection of crops from disease and pests, and enhancing plant fertilization.453 One thing is clear from the body of work reported to date in this field, namely, that the possibilities offered by the peptide−materials interface have only begun to be realized. We expect to see a greater focus on applications of the biointerface to problems that benefit society in future.

AUTHOR INFORMATION Corresponding Authors

*E-mail: tiff[email protected]. *E-mail: [email protected]. ORCID

Tiffany R. Walsh: 0000-0002-0233-9484 Marc R. Knecht: 0000-0002-7614-7258 Notes

The authors declare no competing financial interest. Biographies After graduating with a B.Sci(Hons) from the University of Melbourne, Tiffany Walsh earned her Ph.D. degree in theoretical chemistry from the University of Cambridge, U.K., as a Cambridge Commonwealth Trust scholar. Following a Glasstone Fellowship in the Dept. of Materials at the University of Oxford, she joined the faculty of the University of Warwick, U.K., in the Dept. of Chemistry and the Centre for Scientific Computing. In 2012 she returned to Australia to the Institute for Frontier Materials at Deakin University, where she is Professor of Bio/Nanotechnology. Her research interests focus on computational modeling of the aqueous interface between biomolecules and solid surfaces, using molecular dynamics simulations. Marc R. Knecht completed his B.S. degree in Chemistry from Duquesne University. Following this time, he pursued graduate work in chemistry at Vanderbilt University. Upon receiving his Ph.D., he completed postdoctoral studies in the group of Professor Richard M. Crooks at the University of Texas at Austin. In 2007, he began his independent career as an assistant professor of chemistry at the University of Kentucky. Subsequently he joined the University of Miami as an associate professor of chemistry in 2011. His research interests lie in experimental understanding of peptide-driven fabrication and activation of inorganic materials for applications in catalysis, assembly, and plasmonics, paying particular attention to the atomic level structure of the materials from inorganic core to peptide surface.

ACKNOWLEDGMENTS This work was supported in part by the Air Force Office for Scientific Research, Grant no. FA9550-12-6201-0226. REFERENCES (1) Meyers, M. A.; Lin, A. Y. M.; Chen, P. Y.; Muyco, J. Mechanical Strength of Abalone Nacre: Role of the Soft Organic Layer. J. Mech. Behav. Biomed. Mater. 2008, 1, 76−85. (2) Bedford, N. M.; Hughes, Z. E.; Tang, Z.; Li, Y.; Briggs, B. D.; Ren, Y.; Swihart, M. T.; Petkov, V.; Naik, R. R.; Knecht, M. R.; et al. Sequence-Dependent Structure/Function Relationships of Catalytic Peptide-Enabled Gold Nanoparticles Generated under Ambient Synthetic Conditions. J. Am. Chem. Soc. 2016, 138, 540−548. (3) Bedford, N. M.; Showalter, A. R.; Woehl, T. J.; Hughes, Z. E.; Lee, S.; Reinhart, B.; Ertem, S. P.; Coughlin, E. B.; Ren, Y.; Walsh, T. R.; et al. Peptide-Directed PdAu Nanoscale Surface Segregation: 12692


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