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Nature-Inspired Construction of Two-Dimensionally Self-Assembled Peptide on Pristine Graphene Young Hyun No, Nam Hyeong Kim, Bramaramba Gnapareddy, Bumjoon Choi, YongTae Kim, Sreekantha Reddy Dugasani, One-Sun Lee, Kook-Han Kim, Young-Seon Ko, Seungwoo Lee, Sang Woo Lee, Sung Ha Park, Kilho Eom, and Yong Ho Kim J. Phys. Chem. Lett., Just Accepted Manuscript • DOI: 10.1021/acs.jpclett.7b00996 • Publication Date (Web): 27 Jul 2017 Downloaded from http://pubs.acs.org on July 31, 2017

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The Journal of Physical Chemistry Letters

Nature-Inspired Construction of Two-Dimensionally Self-Assembled Peptide on Pristine Graphene

Young Hyun No,1,# Nam Hyeong Kim,1,# Bramaramba Gnapareddy,2 Bumjoon Choi,3 Yong-Tae Kim,1 Sreekantha Reddy Dugasani,2 One-Sun Lee,4 Kook-Han Kim,1 Young-Seon Ko,1 Seungwoo Lee,1 Sang Woo Lee,3 Sung Ha Park,2* Kilho Eom,5* and Yong Ho Kim1, 6, 7*

1

SKKU Advanced Institute of Nano Technology (SAINT), Sungkyunkwan University, Suwon 16419,

Republic of Korea 2

Department of Physics, Sungkyunkwan University, Suwon 16419, Republic of Korea

3

Department of Biomedical Engineering, Yonsei University, Wonju 26493, Republic of Korea

4

Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, P.O. Box 5825,

Doha, Qatar 5

Biomechanics Laboratory, College of Sport Science, Sungkyunkwan University, Suwon 16419,

Republic of Korea 6

Department of Chemistry, Sungkyunkwan University, Suwon 16419, Republic of Korea

7

Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, Republic

of Korea

#

These authors contributed equally to this work.

*Corresponding Authors: Yong Ho Kim, E-mail: [email protected] Kilho Eom, E-mail: [email protected] Sung Ha Park, E-mail: [email protected] 1 ACS Paragon Plus Environment


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ABSTRACT Peptide assemblies have received significant attention because of their important role in biology and applications in bionanotechnology. Despite recent efforts to elucidate the principles of peptide self-assembly for developing novel functional devices, peptide self-assembly on twodimensional nanomaterials has remained challenging. Here, we report nature-inspired two-dimensional peptide self-assembly on pristine graphene via optimization of peptide-peptide and peptide-graphene interactions. Two-dimensional peptide self-assembly was designed based on statistical analyses of >104 protein structures existing in nature and atomistic simulation-based structure predictions. We characterized the structures and surface properties of the self-assembled peptide formed on pristine graphene. Our study provides insights into the formation of peptide assemblies coupled with twodimensional nanomaterials for further development of nano-bio-composite devices.

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We report a nature-inspired peptide self-assembly on pristine graphene based on statistical analyses of naturally existing protein structures and atomistic simulations to determine the optimal peptide sequence. Our nature-inspired self-assembled peptide on graphene was experimentally validated by evaluating its structural and surface properties.

Peptide self-assemblies have received considerable research attention because of their remarkable properties and novel structures that can mimic natural systems.1-7 For instance, peptide selfassemblies designed as amyloid-like superstructures have recently been shown to drive cellular apoptosis.8 Especially, research on two-dimensional peptide assembly has gained attention owing to the 2 ACS Paragon Plus Environment

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scarcity of such assemblies in nature, as well as their potential for diverse applications in transport, catalytic, and electronic devices.9-10 Only few two-dimensional peptide arrays are known to exist in nature, such as the S-layer proteins of archaea and bacteria.11 Moreover, the design principles of twodimensional peptide assembly have remained elusive despite significant advances in computational approaches.12 Over the last decade, nanomaterials are increasingly being used as templates for the twodimensional assembly of peptides because of their periodic lattice assisting the self-assembly process and their application in the development of biocompatible and biomimetic devices.13 Moreover, such assembled nanostructures retain the excellent properties of nanomaterials. In particular, graphene has received attention as a suitable template for two-dimensional peptide self-assembly because of its unique physical and electronic properties and its applicability in the nanobiotechnology.14-15 There have been previous attempts to assemble peptides on highly ordered pyrolytic graphite (HOPG) instead of pristine graphene.13, 16-17 However the surface properties of graphite are quite different from those of graphene. Thus, it is challenging to construct an ordered peptide self-assembly on a graphene in a liquid environment. The difficulty of peptide self-assembly on pristine graphene is due to peptide adsorption leading to a conformational change in the peptide chains, which prevents them from being assembled into the expected structure on graphene.18-19 The underlying principles of peptide self-assembly on twodimensional lattices have not been fully revealed yet. Herein, we report a two-dimensional peptide self-assembly, epitaxially aligned on pristine graphene, by optimizing both peptide-peptide and peptide-graphene interactions. The self-assembly was inspired from the statistical analyses of β-sheet structures found in nature based on the Define Secondary Structure of Proteins (DSSP) database and atomistic simulations to determine the optimal peptide sequences for the self-assembly structure. Specifically, we utilized the statistical analyses of structures of naturally occurring proteins to construct the peptide backbone structure leading to the formation of β-sheet-like assembly, which is geometrically compatible with graphene lattice. We 3 ACS Paragon Plus Environment


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subsequently employed atomistic simulations to determine the optimal peptide sequence that leads to peptide self-assembly on graphene. Our atomistic simulations suggested that the optimal peptide sequence minimizes not only the peptide-graphene interaction energy, but also the peptide-peptide interaction energy, resulting in the stable formation of two-dimensional peptide self-assemblies on graphene. The experimentally measured structural and surface properties of the peptide self-assemblies formed on graphene were consistent with those predicted from the atomistic simulations. Our study sheds light on a design rule for peptide self-assembly on a two-dimensional nanomaterial, which may open new avenues for the development of nano-bio-composite materials and devices. Figure 1a presents the protocol for constructing the models with an appropriate sequence for two-dimensionally self-assembled peptides on pristine graphene. In step 1, we performed statistical analyses of the β-strand structures available in the Protein Data Bank (PDB), in order to construct peptide backbone structures that would result in stable self-assembly on graphene, which closely resembles the structure of β-strands existing in nature (Figure 1b). The structural features of the βstrands were analyzed by measuring the inter-chain distance (ICD) and intra-residue distance (IRD). In general, dihedral angles (Φ and Ψ) are used to describe the coiled-coil protein backbone structure.20 However, ICD and IRD are key parameters in delineating the structural features of β-sheet assemblies such as amyloid structures,21-24 because the peptide backbone structure is not distorted when a β-sheet assembly is formed two-dimensionally. To perform the statistical analysis, 14,511 proteins that have βsheets as their main secondary structures are found in PDB, and Protein Topology Graph Library (PTGL) was employed to sort the protein structures based on the main secondary structure with using DSSP algorithm.25 We found the average values of ICD and IRD for 264,099 β-sheet domains among 14,511 proteins to be 8.7 ± 0.4 Å and 6.7 ± 0.1 Å, respectively (Figure 1b and S1). The ICD and IRD values of antiparallel β-sheet assemblies are similar to those of the total β-sheet protein domains. In the case of parallel β-sheet structures, the average ICD is 9.9 ± 1.3 Å, whereas the average IRD is similar to 4 ACS Paragon Plus Environment

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that of the antiparallel β-sheet structures (Figure S2). Interestingly, these values are similar to the hexagonal lattice symmetry of graphene, implying a lot of β-sheet structures in nature are possibly matched with graphene lattice. Based on structural statistics of these peptides that are matched with graphene lattice geometrically in terms of ICD and IRD values, we constructed model structure of peptide backbone such that graphene can assist the formation of highly ordered peptide-assembly structure on graphene if an appropriate peptide sequence is chosen (Figure 1b). Specifically, the ICD and IRD values of assemblies can determine the strand vector and assembly vector that are shown in Figure S3 and they indicate the possibility of different geometric symmetries on graphene for antiparallel and parallel assemblies (Figure 1c). Here, we note that our design approach based on design parameters (i.e. ICD and IRD) can allow for designing peptide assembly on other 2D nanomaterial such as MoS2 and WSe2 such that the optimal values of ICD and IRD depends on the geometric parameter of the 2D nanomaterial. In step 3, sequences of β-sheet domains were statistically analyzed for selecting candidates with optimum sequences. The sequence patterns of 264,099 β-sheet domains were investigated to find the most frequent sequence pattern forming stable β-sheet structures. Figure 1d shows that 33.7 % of β-sheet domains exhibited combinatorial arrangement of hydrophobic and hydrophilic sequences like the pattern (HPHP)n or (PHPH)n, where H and P indicate hydrophilic and hydrophobic residues, respectively. It should be noted that though 26% of β-sheet structures are made of many hydrophobic residues, these β-sheet structures cannot be considered for developing peptide assembly on a graphene, because they are more susceptible to structural collapse due to the positioning of hydrophobic residues facing water phase. In addition, the amino acids frequently found in combinatorial patterned sequences were analyzed (Figure S4). For more effective and accurate design of peptide assembly on a graphene, we reduce the range of peptide sequences in such a way that the charged residues was selected for hydrophilic residue in order to prevent additional aggregation,26 while the aromatic residue was chosen for hydrophobic residue in order to optimize the interaction between 5 ACS Paragon Plus Environment


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peptide and graphene. This rational design is necessary to exclude the inadequate structure candidates, and this rational design process can be found in the general nature-inspired design of protein structures based on computational methods such as Rosetta. Statistical analyses show that among the charged hydrophilic residues, lysine and arginine occur most frequently. Lysine was chosen owing to its relatively simple chemical structure that does not geometrically disturb the hydrogen bonding between β-strands. For selecting the aromatic residue, we consider phenylalanine, tyrosine, and tryptophan as they are the most prevalent aromatic residues in nature. For negative control experiment, valine was taken into account, as it is most frequently found in non-polar hydrophobic residues. Based on these statistical sequence analyses, four potential peptide-sequence candidates were selected for constructing the self-assembled peptides on graphene: (KF)4, (KY)4, (KW)4, and (KV)4. In the last step, we determined the optimal peptide sequence for constructing self-assembled peptides on graphene, by using atomistic molecular dynamics (MD) simulations. In particular, the atomistic MD simulations were performed to select the optimal peptide sequence from the sequence candidates such as (KF)4, (KY)4, (KW)4, and (KV)4. Further, we simulated the atomistic-scale dynamics of peptide assemblies from these sequences to verify whether the structure modeled from statistical analyses of β-sheet domains is stable. To study the structural stability and interface energies of peptide assemblies based on parallel or antiparallel stacking of the four peptide sequences, equilibrium MD simulations were performed. In these simulations, the assembled structures made of four peptide chains were initially placed on constrained graphene, and the distance between the peptide chains and graphene are set to be 8 Å (Figure S7). The MD simulations were performed for 40 ns. Figure 2a shows the equilibrated structures of eight possible candidates for two-dimensional self-assembled peptides on graphene. We found that antiparallel stacking of peptide chains with sequences (KF)4 and (KV)4, and parallel stacking of peptide chains with sequence (KF)4 were stably assembled on graphene. However, other five self-assembled peptide structures are quickly unfolded within 1 ns. 6 ACS Paragon Plus Environment

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To determine the most stable sequence and stacking symmetry, additional equilibrium MD simulations were performed for 100 ns, wherein graphene was unconstrained and free to move, to mimic the real harsh environment (Figure S5). We found that parallel stacking of peptide chain with sequence (KF)4 is deformed with unconstrained graphene, indicating the unstable energetic structure of parallel (KF)4. However, antiparallel stacking of peptide chains with sequences (KF)4 and (KV)4 leads to the stable assembly structure despite the harsh environment. In particular, as shown in Figure S5b, the rootmean-square distance (RMSD) for the assembly constructed based on antiparallel stacking of (KF)4 or (KV)4 chains barely change during 100 ns, whereas the RMSD of other candidates increased drastically within 1 ns. This tendency is consistent with the results of time-dependent ICD and the number of hydrogen bonds for the eight possible self-assembly structures. For the peptide self-assemblies based on antiparallel stacking of (KF)4 or (KV)4 chains, the average ICD values over 100 ns are 8.3 ± 0.3 Å and 8.4 ± 0.2 Å, respectively. These results are in accordance with the statistical analyses of naturally occurring β-sheet structures. However, for other assemblies, the ICD value increases significantly within 5 ns, even reaching up to 100 Å, which indicates that these assemblies are disrupted. In addition, for the self-assembly based on antiparallel stacking of (KF)4 or (KV)4 chains, the number of hydrogen bonds was counted as > 20 independent of time (Figure S5), indicating that peptide self-assemblies have sufficient contacts between the peptide backbones to conserve the assembled structure. However, the number of hydrogen bonds for the other six assemblies decreases with time, reaching less than 10 after 40 ns, which suggests that these assembled structures are ruptured and eventually are not stable. To gain quantitative insights into the energetics, we employed molecular mechanics Poisson– Boltzmann surface area (MM-PBSA) calculations (Figure 2b).27 This enables us to compute not only the peptide-peptide interaction energy, but also the peptide-graphene interaction energy. From the perspective of peptide-peptide interaction energetics, self-assembled peptides comprising antiparallel stacking of (KF)4 and (KV)4 chains are the most stable. However, the low peptide-peptide interaction energies of antiparallel (KY)4 or (KW)4 chains imply the inability of these peptides to be assembled. By 7 ACS Paragon Plus Environment


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contrast, the peptide-graphene interaction energetics indicates that antiparallel stacking of (KF)4, (KY)4, and (KW)4 chains are well-adsorbed on graphene, whereas the graphene surface does not assist the formation of self-assembly of (KV)4 chains owing to their low peptide-graphene interaction energy. Thus the self-assembly of (KV)4 chains is attributed to peptide-peptide interaction, but is not affected by the peptide-graphene interaction or geometric accordance with the graphene lattice. This suggests that peptide chains with the sequence (KF)4 exhibit graphene-driven peptide self-assembly, whereas chains with the sequence (KV)4 result in peptide self-assembly without any effect of the graphene. To validate our finding that the graphene promotes the self-assembly of (KF)4 chain, we utilized all-atom MD simulations of these assemblies in presence and absence of the graphene. Ramachandran plot was used to investigate whether these assemblies are maintained in absence of the graphene. Figure 2c shows that absence of the graphene results in disruption of the self-assembly structure of (KF)4 chains, whereas the self-assembly made of (KV)4 chains is stably maintained as a β-sheet-like structure. Peptides composed of repeating (KV) sequences are known to result in the formation of assembled structures like fibril structures.26, 28 To characterize the orientation of the self-assembled peptides made of (KF)4 and (KV)4 chains and to compare the symmetry of peptide assembly on graphene computed from simulations with that anticipated from the statistical analyses, the angles between the peptide assembly and the standard vectors of graphene lattice were calculated (Figure 2d, e). In the antiparallel stacking of (KF)4 strands, angle distribution is restricted with an average angle being measured as 176°, which is comparable to the expected angle of 169°. This result provides an evidence that the self-assembly of (KF)4 in an antiparallel arrangement is driven by the geometric lattice of the graphene. However, the all-atom MD simulation shows that the angles for an antiparallel (KV)4 assembly are randomly distributed, indicating that (KV)4 peptides they barely interact with the graphene lattice. This implies an important role of graphene lattice in the formation of two-dimensional peptide assembly made of (KF)4 chains. From the MD simulations, which provided insights into the structural and energetic perspectives for peptide self8 ACS Paragon Plus Environment

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assembly, antiparallel stacking of (KF)4 is chosen as the optimal sequence candidate for stable twodimensional assembly on graphene. Atomic force microscopy (AFM) measurements were performed to validate formation of the (KF)4-peptide-assembly on pristine graphene (Figure 3a). The liquid tapping AFM imaging technique was used to observe the morphology of self-assembled peptide on graphene in water, because drying of a sample may lead to deformation of the peptide assemblies. It should be noted that poly(methyl methacrylate) (PMMA) residuals was appeared which would be inevitably formed during the graphene transfer process. Moreover, the surface energy of pristine graphene for molecular adsorption is lower than that of graphite or HOPG, which can lead to different conformations.29 Despite this limitation, we observed well-organized two-dimensional self-assembled peptide patterns on pristine graphene, and found that organization of this peptide self-assembly occurs in the direction of the Bravais lattice vector of graphene, with multi- or single-domain (Figure 3a). Specifically, the fast Fourier transformation (FFT) result indicates the self-assembly of the peptide along the three directions of the hexagonal lattice of graphene, located at an angle of 120° from each other (Figure 3a inset). In particular, the regular selfassembly patterns are clearly shown in magnified AFM images (Figure 3b). The assembled patterns correspond to the model peptide-assembly structure anticipated from structural analysis and atomistic simulations. By contrast, (KY)4 and (KW)4 were deposited on graphene surface without any assembling features, while some of (KV)4 are aggregated but are not assembled on graphene (Figure S8). This suggests that the graphene assists peptide self-assembly from (KF)4 chains, such that the self-assembly is organized in a direction determined by the hexagonal lattice of the graphene, indicative of templated assembly. To validate the experimentally observed peptide self-assemblies on graphene, we compared the morphology of peptide self-assemblies measured from AFM experiments with that predicted from atomistic MD simulations. Figure 3c shows the probability distribution of widths for peptide assemblies formed on graphene, as estimated from AFM experiments and MD simulations. The width of the peptide 9 ACS Paragon Plus Environment


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self-assemblies measured based on the AFM images is 2.83 ± 0.22 nm, which is consistent with that (2.82 ± 0.03 nm) evaluated by MD simulations. In addition, we conducted Raman spectroscopy-based analysis to verify the peptide self-assembly on graphene. Figure 3d shows that peptide self-assemblies cause a downshift in the G-band of graphene and an upshift in the 2D band. This implies that peptide self-assembly resulted in the slight N-doping of graphene, while its intrinsic properties were conserved. Furthermore, the surface property of graphene decorated with peptide assemblies was evaluated using contact angle measurement and MD simulation (Figure S6). The contact angle of bare graphene was measured at 88.1°, while surface coating with the self-assembled peptide reduced the contact angle of graphene into 69.4°. This indicates that peptide self-assembly decreases the hydrophobicity of the graphene surface due to the hydrophilic property of peptides. The experimental result is consistent with the MD simulation results showing that the peptide assembly formation decreases the value of contact angle from 85.6° to 52.8°. These results demonstrate extremely hydrophobic surface of pristine graphene was physically changed by nanoscale-thin coating with self-assembled peptides. Our results thus suggest that the combination of peptide self-assemblies and graphene leads to the development of a new class of composite materials, which exhibits not only biocompatibility, but also excellent electrical properties owing to graphene. In conclusion, we first demonstrate the formation of a nature-inspired peptide self-assembly on a pristine graphene by optimizing the peptide-peptide and peptide-graphene interactions. The selfassembled peptide was designed based on statistical analyses of naturally occurring β-sheet structures, as well as atomistic simulations to determine the optimal peptide sequence leading to formation of stable peptide self-assembly on graphene. We have shown that the formation of peptide self-assembly with a specific orientation is attributed to the lattice structure of graphene, and that this self-assembly affects the surface properties of graphene. Also, this nature-inspired design approach using the parameter of ICD and IRD from naturally occurring proteins can provide the novel peptide construction which can form stable 2D self-assembly of peptides on various 2D materials like MoS2 and WSe2. Our work 10 ACS Paragon Plus Environment

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provides insights into the design principles of peptide self-assembly on a two-dimensional nanomaterial, which may open new avenues for developing novel biomimetic and biocompatible devices.

Supporting Information The Supporting Information is available free of charge on ACS Publications website at DOI:.## Materials and methods for the synthesis of peptide chains and pristine graphene, detailed information regarding the MD simulations, and the experimental methods for Raman spectra characterization and contact angle measurement are given in the supporting information file. Detailed results of statistical analyses of β-sheet structures, their sequence analysis, and results of the MM-PBSA calculations are also provided.

Notes The authors declare no competing financial interests.

ACKNOWLEDGMENTS This work was supported by the National Research Foundation of Korea (NRF) under Grant No. NRF2015R1A2A2A04002453, NRF-2017R1D1A1B03035855, and IBS-R015-D1; and the National Institute of Supercomputing and Network in Korea Institute of Science and Technology Information (KISTI) under Grant No. KSC-2017-C3-0002.

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22. Rochet, J. C.; Lansbury, P. T., Amyloid Fibrillogenesis: Themes and Variations. Curr. Opin. Struc. Biol. 2000, 10, 60-68. 23. van der Hilst, J. C. H.; Simon, A.; Drenth, J. P. H., Molecular Mechanisms of Amyloidosis. N. Engl. J. Med. 2003, 349, 1872-1873. 24. Yoon, G.; Lee, M.; Kim, J. I.; Na, S.; Eom, K., Role of Sequence and Structural Polymorphism on the Mechanical Properties of Amyloid Fibrils. Plos One 2014, 9. 25. Schafer, T.; Scheck, A.; Bruness, D.; May, P.; Koch, I., The New Protein Topology Graph Library Web Server. Bioinformatics 2016, 32, 474-476. 26. Schneider, J. P.; Pochan, D. J.; Ozbas, B.; Rajagopal, K.; Pakstis, L.; Kretsinger, J., Responsive Hydrogels from the Intramolecular Folding and Self-Assembly of a Designed Peptide. J. Am. Chem. Soc. 2002, 124, 15030-15037. 27. Liu, F. F.; Liu, Z.; Bai, S.; Dong, X. Y.; Sun, Y., Exploring the Inter-Molecular Interactions in Amyloid-Beta Protofibril with Molecular Dynamics Simulations and Molecular Mechanics PoissonBoltzmann Surface Area Free Energy Calculations. J. Chem. Phys. 2012, 136. 28. Haines-Butterick, L.; Rajagopal, K.; Branco, M.; Salick, D.; Rughani, R.; Pilarz, M.; Lamm, M. S.; Pochan, D. J.; Schneider, J. P., Controlling Hydrogelation Kinetics by Peptide Design for ThreeDimensional Encapsulation and Injectable Delivery of Cells. Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 7791-7796. 29. Lazar, P.; Otyepkova, E.; Banas, P.; Fargasova, A.; Safarova, K.; Lapcik, L.; Pechousek, J.; Zboril, R.; Otyepka, M., The Nature of High Surface Energy Sites in Graphene and Graphite. Carbon 2014, 73, 448-453.



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Figure 1. Nature-inspired construction of two-dimensional self-assembled peptides on pristine graphene. (a) Flowchart showing construction of the self-assembled peptides on pristine graphene. (b) Step 1: Statistical analyses of β-sheet protein structures found in nature to model the backbone structure of peptide self-assemblies. (c) Step 2: Organization of peptide self-assemblies on graphene is based on its lattice symmetry. The upper panel shows the self-assembled peptide formed as an antiparallel β-sheet on graphene, whereas the lower panel presents the parallel β-sheet structure of the self-assembled peptide on graphene. (d) Step 3: The sequence patterns of β-sheet structures found in nature were analyzed for selecting the optimum peptide sequence. Here, ‘H’ represents hydrophilic residue, and ‘P’ indicates hydrophilic residue. Statistical analyses showed that combinatorial arrangement of hydrophobic and hydrophilic residues results in the formation of β-sheet-like structures. We selected an aromatic residue as a hydrophobic residue because an aromatic residue can face the graphene surface, thus optimizing the interaction between the peptide chain and graphene surface. 14 ACS Paragon Plus Environment

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Figure 2. Structural and energetic analyses of peptide assemblies on graphene. (a) Representative structures of self-assembled peptides, obtained from equilibrium molecular dynamics simulations (at 40 ns). (b) Energetics of the graphene-peptide and peptide-peptide interactions for each peptide candidate. (c) Ramachandran plots for antiparallel assembly formed based on the peptide sequence (KF)4 or (KV)4, in the presence (left) or absence (right) of graphene. The angle of (d) (KF)4 and (e) (KV)4 assembled peptides along the standard vector of graphene, represented in Figure S3.



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Figure 3. Experimental characterization of (KF)4-peptide-assembly on pristine graphene. (a) Lowresolution (left) and high-resolution (right) atomic force microscopy (AFM) images of self-assembled peptides formed on graphene. The high-resolution AFM images show a multi-domain area, where peptide assemblies are arranged in two distinct directions, as well as a single-domain area, in which the self-assembled peptide is arranged in a single direction. Two distinct regions (indicated as region 1 and 2) show different organizations of peptide assemblies on graphene in two different directions, aligned with the graphene lattice vectors, the angle between which is given by 120° (the inset shows the fast Fourier transformation image). (b) Enlarged AFM images (left) of self-assembly formation on graphene with two different orientations, and the model structures (middle and right). Scale bar represents 20 nm. (c) Comparison between the widths of assemblies of (KF)4 chains, measured from AFM experiments and MD simulations. (d) Raman spectra of pristine graphene and peptide assembly-decorated graphene.


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Figure 1. Nature-inspired construction of two-dimensional self-assembled peptides on pristine graphene. (a) Flowchart showing construction of the self-assembled peptides on pristine graphene. (b) Step 1: Statistical analyses of β-sheet protein structures found in nature to model the backbone structure of peptide selfassemblies. (c) Step 2: Organization of peptide self-assemblies on graphene is based on its lattice symmetry. The upper panel shows the self-assembled peptide formed as an antiparallel β-sheet on graphene, whereas the lower panel presents the parallel β-sheet structure of the self-assembled peptide on graphene. (d) Step 3: The sequence patterns of β-sheet structures found in nature were analyzed for selecting the optimum peptide sequence. Here, ‘H’ represents hydrophilic residue, and ‘P’ indicates hydrophilic residue. Statistical analyses showed that combinatorial arrangement of hydrophobic and hydrophilic residues results in the formation of β-sheet-like structures. We selected an aromatic residue as a hydrophobic residue because an aromatic residue can face the graphene surface, thus optimizing the interaction between the peptide chain and graphene surface. 118x74mm (600 x 600 DPI)

ACS Paragon Plus Environment


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Figure 2. Structural and energetic analyses of peptide assemblies on graphene. (a) Representative structures of self-assembled peptides, obtained from equilibrium molecular dynamics simulations (at 40 ns). (b) Energetics of the graphene-peptide and peptide-peptide interactions for each peptide candidate. (c) Ramachandran plots for antiparallel assembly formed based on the peptide sequence (KF)4 or (KV)4, in the presence (left) or absence (right) of graphene. The angle of (d) (KF)4 and (e) (KV)4 assembled peptides along the standard vector of graphene, represented in Figure S3. 108x64mm (600 x 600 DPI)


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Figure 3. Experimental characterization of (KF)4-peptide-assembly on pristine graphene. (a) Low-resolution (left) and high-resolution (right) atomic force microscopy (AFM) images of self-assembled peptides formed on graphene. The high-resolution AFM images show a multi-domain area, where peptide assemblies are arranged in two distinct directions, as well as a single-domain area, in which the self-assembled peptide is arranged in a single direction. Two distinct regions (indicated as region 1 and 2) show different organizations of peptide assemblies on graphene in two different directions, aligned with the graphene lattice vectors, the angle between which is given by 120° (the inset shows the fast Fourier transformation image). (b) Enlarged AFM images (left) of self-assembly formation on graphene with two different orientations, and the model structures (middle and right). Scale bar represents 20 nm. (c) Comparison between the widths of assemblies of (KF)4 chains, measured from AFM experiments and MD simulations. (d) Raman spectra of pristine graphene and peptide assembly-decorated graphene. 113x75mm (300 x 300 DPI)


Nature-Inspired Construction of Two ... - ACS Publications

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