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Integrated modeling and experimental approaches to control silica modification of design silk-based biomaterials Nina Dinjaski, Davoud Ebrahimi, Ling Shengjie, Suraj Shah, Markus J. Buehler, and David L Kaplan ACS Biomater. Sci. Eng., Just Accepted Manuscript • DOI: 10.1021/acsbiomaterials.6b00236 • Publication Date (Web): 09 Aug 2016 Downloaded from http://pubs.acs.org on August 12, 2016

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ACS Biomaterials Science & Engineering

Integrated modeling and experimental approaches to control silica modification of design silk-based biomaterials Dinjaski Nina1,2*, Ebrahimi Davoud2*, Ling Shengjie1,2*, Shah Suraj1, Buehler Markus J.2†, Kaplan David L.1† 1 2

Department of Biomedical Engineering, Tufts University, Medford, MA, 02155, USA Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

†To whom correspondence should be addressed: David L. Kaplan. E-mail [email protected]; Tel. +1 617 626 3251; Fax + 617 627 3231 Markus J. Buehler. E-mail [email protected]; Tel. +1 617 452 2750 * These authors contributed equally to this work.

Abstract: Mineralized polymeric biomaterials provide useful options towards mechanically robust systems for some tissue repairs. Silks as a mechanically robust protein-based material provide a starting point for biomaterial options, particularly when combined with silica towards organic-inorganic hybrid systems. To further understand the interplay between silk proteins and silica related to material properties, we systematically study the role of three key domains in bioengineered spider silk fusion proteins with respect to β-sheet formation and mineralization: i) a core silk domain for materials assembly, ii) a histidine tag for purification, and iii) a silicification domain for mineralization. Computational simulations are used to identify the effect of each domain on the protein folding and accessibility of positively charged amino acids for silicification and predictions are then compared with experimental data. The results show that the addition of the silica and histidine domains reduces β-sheet structure in the materials, and increases solvent accessible surface area to the positive charged amino acids, leading to higher levels of silica precipitation. Moreover, the simulations show that the location of the charged biomineralization domain has small effect on the protein folding and consequently surface exposure of charged amino acids. Those surfaces display correlation with the amount of silicification in experiments. The results demonstrate that the exposure of the positively charged amino acids impacts protein function related to mineralization. In addition, processing parameters (solvating agent, the method of β-sheet induction and temperature) affect protein secondary structure, folding and function. This integrated modeling and experimental approach provides insight into sequence-structure-function relationships for control of mineralized protein biomaterial structures. Keywords: spider silk, silk-silica fusion proteins, biomineralization, sequence-structure relationship, modeling

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1. Introduction Exquisite designs of natural materials that optimize function have been used as inspiration for biomaterial designs. In particular, sequences encoding spider silks have been considered for biomaterial designs due to their unique material properties1–4 determined by the constituent amino acid sequences and the hierarchical assembly of the protein chains into fibers. To tailor material properties, it is essential to understand sequence-structure-function relationships.5,6 As a start in this direction, the integration of genetic engineering with computational modeling has provided new insights into these relationships towards improved biomaterial designs.5 One area with the potential to advance tissue regeneration are organic-inorganic material systems, such as silk-silica materials, where there have been a number of studies to examine relationships between silk and silica forming domains related to composite material formation.7–12 Previous molecular simulations of biosilicification focused on the adsorption of biomolecules on silica surfaces or silica nanoparticles13–20 and the mineral in the form of nanoparticles with certain sizes or surfaces were placed in contact with the protein. While those simulations provide insight on the importance of certain residues in the binding process, they do not address mechanisms involved in control over the organization of the silica particles precipitating on biopolymer substrates (e.g., peptide-mediated silicification), which is important in terms of functional material features such as mechanics. Moreover, restricted options remain for computational-based material designs due to the limited knowledge of the effect of specific spider silk domains on biomineralization, used primarily to provide scaffolding structure in the current study. Thus, here we used integrated modeling and experimental approaches to examine the effect of the presence and location of silk and silica binding peptide domains on protein folding and accessibility of key amino acid residues for silicification. Bioengineered spider silks are attractive as biomaterial substrates as their properties can be fine-tuned through sequence modification and they can incorporate diverse functional domains.7,21,22 Several functionalized spider silks have been developed that perform new functions.23 Recombinant silk-silica fusion proteins catalyze biomineralization and have shown utility as scaffolds for tissue engineering.22,24 Silk-silica chimeras have been designed by fusing modified dragline silk copolymers (termed 15mers to represent a core census repeat found in Nephila clavipes major ampullate dragline silk (SGRGGLGGQGAGAAAAAGGAGQGGYGGLGSQGT)15) with the silica-binding peptide R5 (SSKKSGSYSGSKGSKRRIL) derived from the Cerithiopsis fusiformis silaffin gene.7,25 The silk component serves as an organic scaffold that controls material stability and allows multiple modes of processing, whereas the short R5 domain induces silica precipitation in vitro and serves as an important osteoinductive element with potential control of remodeling rate and tissue regeneration outcomes in vitro.7,22 With the prior studies above, there remains a need for efficient biomaterial design schemes where trial and error is replaced with systematic guidance from modeling; integrating the two approaches into a more efficient understanding of optimized designs. The addition of functional domains (e.g., silica formation) to the silk sequence influences protein secondary structure and folding and thereby the function of the material. All the constructs also carry histidine tags to facilitate purification of the recombinant proteins, thus the potential role for this tag in silicification outcomes is also studied here. The development of predictive platforms to capture the mechanisms by which the silk and functional domains affect fusion protein structure-function is important for more efficient material designs. The versatility of recombinant spider silk and the large body of previous work showing the potential of modeling-based biomaterial design, make this integrated approach suitable to extend design options. The goal of the present study is to use this integrated modeling/experimental approach to control biomineralization process using silk as a template and silica formation as the inorganic component. This strategy is pursued to improve our ability to forecast the influence of the addition of biomineralization domains to silk sequences in terms of protein structure and folding, and to identify more suitable optimal 2 ACS Paragon Plus Environment

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processing parameters. Understanding the mechanism by which these key factors impact biomineralization allows for the more rational design of silk-based materials to tightly control and optimize the process. 2. Materials and Methods 2.1. Recombinant production of silk and silk-silica fusion proteins The following constructs are synthesized: 15mer-ch, nh-15mer, R5-15mer-ch, nh-15mer-R5 and nh15mer-silaffin (Figure 1). The genes encoding the recombinant silk proteins are based on the sequence of the MaSp I protein of N. clavipes. Spider silk fusion proteins are constructed by assembling spider silk based domains and silica binding peptide R5. The spider silk domain consist of 15 repeating units of (SGRGGLGGQGAGAAAAAGGAGQGGYGGLGSQGT), responsible for β-sheet formation. Histidine tags are placed either on the C- or N-terminal domains of the spider silk sequence (15mer-ch, nh-15mer). In addition, a control recombinant 15mer spider silk sequence lacking His-tag is also produced. The R5 domain (SSKKSGSYSGSKGSKRRIL) is either fused to the N- or C-terminal domain of the silk sequence, whereas the histidine tag is placed on the opposite terminus (R5-15mer-ch, nh-15mer-R5). To examine the influence of the presence of multiple R5 domains, the entire silaffin gene is fused to the nh15mer sequence (nh-15mer-silaffin). Using these motifs, six unique recombinant proteins have been cloned: 15mer, nh-15mer, nh-15mer-R5, nh-15mer-silaffin, 15mer-ch and R5-15mer-ch (Figure 1A).22 All genetic constructs are cloned into commercially available pET30a(+) vector (Novagen, San Diego, CA, USA) as described previously.22 The silaffin gene is synthesized (Invitrogen, Grand Island, NY, USA) as a NheI/SpeI fragment from the pUC57-silaffin vector, and cloned following a previously described procedure.22 Constructs are transformed into high efficiency Escherichia coli DH5α competent cells (NEB, Ipswich, MA, USA) for screening. Chosen samples are sequenced with T7 and T7 terminal primers (Genewiz Inc., Cambridge, MA, USA). Constructs are expressed in E. coli strain BL21 Star (DE3) (Invitrogen, Grand Island, NY, USA). The proteins are produced and purified as described previously.26 Briefly, for large-scale expression the recombinant strains are grown overnight at 37°C in Luria-Bertani medium. Afterwards, a seeding culture is transferred to yeast extract medium and cultured at 37°C pH 6.8 using a New Brunswick BioFlo 3000 bioreactor (New Brunswick Scientific, Edison, NJ, USA). Gene expression is induced with 1 mM isopropyl-β-D-thiogalactopyranoside (IPTG) (Sigma-Aldrich, St. Louis, MO, USA) when the optical density OD600 reached approximately 0.8.27 Purification is performed using immobilized metal affinity chromatography following a previously described procedure.26 The proteins are dialyzed against water using a Slide-A-Lyzer cassettes (Pierce, Rockford, IL, USA) with a molecular weight cut-off of 2,000 Da and the protein solution is then lyophilized. The purity of expressed proteins is verified by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) followed by Colloidal Blue staining. 2.2. Preparation of silk and chimera films Lyophilized recombinant silk-silica fusion proteins (nh-15mer, 15mer-ch, nh-15mer-R5, R5-15mer-ch) are dissolved at a concentration of 2.5% (wt/vol) in either 1,1,1,3,3,3-hexafluoroisopropanol (HFIP) (Sigma-Aldrich, St. Louis, MO, USA) or ultrapure water. The proteins are allowed to dissolve overnight at 4°C. PDMS (Sylgard 184 PDMS, Mlsolar, Campbell, CA, USA) disks (R=6 mm) are used as a substrates to deposit 20 µL of each protein solution. Films are air-dried overnight and subsequently subjected to either water vapor annealing22,25 or methanol vapor25 to induce crystallization (formation of β-sheets). For water annealing, the films are incubated in an isotemp vacuum oven at –25 inHg and at either room temperature or 60°C for 1 h or 24 h. For methanol treatment, the films are exposed to methanol vapors overnight at room temperature and then air-dried.



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2.3. Analysis of β-sheet content by Fourier Transform Infrared Spectroscopy (FTIR) Fourier transform infrared spectroscopy (FTIR) is carried out using a FT/IR-6200 (Jasco Instruments, Easton, MD, USA) to investigate protein conformation. Absorbance spectra are collected from 4000 to 600 cm-1 by averaging 64 scans at a resolution of 4.0 cm-1. Fourier self-deconvolution is performed with PeakFit software with Lorentzian peak profile (half-bandwidth of 25 cm-1 and a noise reduction factor of 0.3). Quantification of the secondary structure is based on analyzing the amide I region (1700 – 1600 cm1 ). Background absorption is subtracted from the sample spectra to establish baseline. Spectral deconvolution is performed using the procedure described previously.28 Briefly, Fourier selfdeconvolution (FSD) is performed over the amide I region on the spectra with Lorentzian peak profile (half-bandwidth of 25 cm-1 and a noise reduction factor of 0.3). The average secondary structure percent composition of the spider silk fusion proteins, in particular, the β-sheet content, is assessed by integrating the area of each deconvoluted curve, and then normalizing to the total area of the amide I peak. 2.4. Biosilicification reaction on recombinant fusion protein films To induce silica precipitation and analyze the effect of β-sheet content on biosilicification, protein films (15mer, nh-15mer, 15mer-ch, nh-15mer-R5, R5-15mer-ch, poly(lysine)- and poly(glutamic acid)modified Bombyx mori silk,29 H(AB)126) are treated with prehydrolyzed tetraethyl orthosilicate (TEOS) in 100 mM bis-tris propane/citric acid buffer at pH 7.0 according to protocols previously described.25 Briefly, a total of 1 mL of 30 mM TEOS is added into each well of a 24-well plate to cover the film formed on the PDMS substrate for one hour at room temperature. The films are then washed once with distilled water and air-dried overnight. Poly(lysine)29 modified B. mori silk and poly(glutamic acid)29 modified B. mori silk are used as highly positively and highly negatively charged controls to examine the influence of charge on silicification. These films are prepared following the same procedure as stated for silk and chimeras films (see Section 2.2). Afterwards, films are subjected to silicification reaction, as described above. H(AB)126 is an artificial spider silk construct with different silk domains compared to nh-15mer, but carries the same His-tag at the N-terminal domain. Therefore, this sequence is used as a control to examine the influence of silk sequence on silicification. The H(AB)12 film is prepared and silicified as stated for the rest of the recombinant constructs. 2.5. Analysis of film surface morphology and silica particle size by Scanning Electron Microscopy (SEM) Recombinant protein films are attached with carbon tape to SEM stubs. Samples are coated with gold and then observed using Scanning Electron Microscope (SEM) (Carl Zeiss SMT, Oberkochen, Germany) at an accelerated voltage of 5 kV to analyze levels of silicification and particle size. A minimum of 50 particles are averaged to determine the particles size. 2.6. Computational Methods The computational set up to study effect of amino acid sequence (type and ordering of different protein building blocks) on the secondary structure and folding of protein constructs is summarized in Figure 2A. All MD simulations are performed using the GROMACS 5.0.1 suite30 and the OPLS-AA force field.31,32 In all cases, the three dimensional periodic boundary conditions are applied. The atomistic structures are visualized using VMD molecular graphic software.33 The procedure starts with initial guess of protein 3D structures (Figure 2A). Previously, it has been shown that the molecular weight of the silk domain correlated to the size of the silica particle formed.25 Here we focus on the effect of the different domains or blocks in the bioengineered silk fusion proteins to identify trends which could be correlated with experiment. We have modelled six monomers of silk to reduce computational cost of the simulations using I-TASSER method of homology modelling.34–36 Then replica exchange molecular dynamics 4 ACS Paragon Plus Environment

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(REMD) are performed to create an ensemble of energy minimized models in implicit water (with dielectric coefficient ξ=80). Implicit solvation calculations are carried out using the generalized Bornformalism and the OBC model37 for calculating the Born radii. The long range electrostatic Coulombic interactions are calculated using the reaction field method38 with a cutoff radius of 10 Å. The same cutoff radius is used for short range interactions. The equations of motions are integrated using the leap-frog algorithm39 with the integration time step of 2 fs (femtosecond). Each replica is simulated for 10 ns. During REMD simulations, all bond lengths and angles are constrained using the LINCS algorithm.40 For silk, nh-silk, silk-ch, nh-silk-R5, R5-silk-ch and nh-silk-silaffin, the number of replicas covering temperatures from 300 K to 500 K are 15, 16, 16, 20, 20 and 21, respectively. The distribution of temperatures are determined by using temperature generator for REMD simulation proposed Patriksson and van der Spoel.41 The exchange attempts are made every 5 ps. All the REMD simulations are performed in the canonical (NVT) ensemble using the Nose-Hoover42,43 thermostat for the system. The simulation trajectories are saved every 5 ps for subsequent analyses. For each case, the last 2.5 ns ensembles (from 7.5 ns to 10 ns) are analyzed from the lowest temperature replica (i.e., 300 K) to select the most probable representative structure. The single linkage clustering algorithm based on root mean square deviations (RMSDs) with 1 Å cutoff is used to cluster conformations. In this algorithm two samples belong to the same cluster if their minimum distance is less than the cutoff value. For each case, the structure with the smallest average distance from the other structures in the most populated cluster is chosen as the representative structure for the next step. The representative structures are solvated in the center of cubic boxes with a side length of 115 Å. The solvation process is performed by stacking equilibrated boxes of SPC water molecules. Solvent molecules are removed from the boxes if the distance between an atom in the solvent and an atom in the protein is less than their van der Waals radii. Each system is energy minimized using steepest descent algorithm and a 50 ps NVT simulation followed by another 50 ps NPT simulation to prepare the system for a longer NPT simulation of 20 ns (for silk, nh-silk and silk-ch), 40 ns (for nh-silk-R5 and R5-silk-ch), and 100 ns (for nh-silk-silaffin). All the simulations are performed at pressure of 1 atm and temperature of 300 K. In all explicit solvent simulations, the equations of motions are integrated with an integration time step of 1 fs. The long range electrostatic coulombic interactions are calculated using particle mesh ewald summation.44 The Nose-Hoover42,43 thermostat and Parrinello-Rahman45 barostat are used to control temperature and pressure in the system. The properties of the systems are reported by averaging over the last 10 ns trajectories of the simulations. The secondary structures are determined with the DSSP algorithm.46 The algorithm uses the atomic coordinates and hydrogen bonding patterns to assign each residue to the following structural elements: βbridge, extended β-strands, 3-10 helix, α-helix, π helix, β-turns and bends. All other residues are labeled unassigned. For our analyses, we combined the β-bridge, extended β-strands and β-turns into a single structural element of β-sheet. Figure 2B shows final sample structures of the proteins in water solvent. 2.7. Statistics Data are expressed as mean ± standard deviation. One or two-way analysis of variance (ANOVA) and Tukey post-hoc analysis were used to determine statistically significant differences. Statistical significance was accepted at the p < 0.05 level and indicated in figures as *p < 0.05.

3. Results 3.1. Recombinant production of spider silk and silk-silica fusion proteins The designed protein sequences and their successful expression/purification is shown in Figure 1. Three recombinant silk only constructs (controls) were produced: 15mer lacking His-tag, nh-15mer with His-tag 5 ACS Paragon Plus Environment


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positioned at N-terminal and 15mer-ch with His-tag at C-terminal. The recombinant silk-silica variants successfully generated include: silk-silica fusion proteins carrying the silica binding peptide R5 either at N- or C-terminus of the spider silk 15mer (R5-15mer-ch, nh-15mer-R5) and the His-tag positioned on the opposite terminus. The multimer R5 (silaffin) was fused to the C-terminal region of the 15mer (Figure 1). 3.2. Influence of protein sequence on secondary structure FTIR analysis was performed to identify the impact of sequence location on the secondary structure of the recombinant proteins. In addition, molecular dynamics simulations were performed to provide information on protein folding and distribution of charged amino acids on the accessible surface area of proteins, as the type and ordering of different protein building blocks were changed to compare with the experimental results. REMD simulations in implicit water followed by regular explicit water molecular dynamics simulations on representative structures, were used to study the mechanism of change in the folding of proteins at the molecular level (Figure 2). Structural changes during equilibration with explicit solvent indicated that the last 10 ns of simulation in each case provided sufficient convergence of three metrics: the root-mean-square deviation (RMSD), solvent accessible surface area (SASA), and total βsheet content (Figure 3). Therefore, the structural properties of the proteins are reported by averaging the results over the last 10 ns of simulations. Based on the results it was found that the C-terminal position of the histidine tag (15mer-ch) resulted in decreased overall crystallinity, when compared to the N-terminal position in the nh-15mer (Figure 4). The addition of the R5 domain to the silk, based on the FTIR spectra of water based nh-15mer and nh-15mer-R5 films, water annealed for 24 h at room temperature, the reduction in β-sheet content was not statistically significant (Figure 4). Furthermore, the N-terminal (R515mer-ch) vs. C-terminal (nh-15mer-R5) localization of R5 domain did not affect β-sheet content, showing a minor effect of the localization of the R5 domain on protein secondary structure when the films were made in water and water annealed at room temperature for 24 h. This finding was supported by the modeling data showing no change in the β-sheet content related to the re-location of R5 domain (Figure 4). Additionally, the influence of the multimer biomineralization domain on protein crystallinity was assessed. β-sheet content was determined for the nh-15mer, nh-15mer-R5 and nh-15mer-silaffin water based films after the induction of β-sheet formation via water annealing at room temperature for 24 h (Figure 4). The presence of the R5 single copy at the C-terminal domain did not induce a significant change in protein secondary structure when compared to the nh-15mer where the biomineralization domain was absent. However, the addition of R5 multimer (silaffin) resulted in a statistically significant decrease of β-sheet content by about 5% when compared to the nh-15mer and nh-15mer-R5 samples. Even though the addition of R5 as a single copy to the C-terminus did not significantly change protein crystallinity, the shift towards lower crystalline structures in the nh-15mer-silaffin indicated the involvement of silaffin in protein secondary structure. The computational simulation can capture the trends of changes in β-sheet content except for the nh-silk-sillafin. In the nh-silk-R5 the amount of βsheet structures obtained by modeling predictions was less than in the nh-silk-silaffin. In the simulations, for each case, the folding of one protein sequence was pursued. The results from the simulation of the nhsilk-silaffin protein (right bottom of Figure 2B) showed a free chain that could interact with other protein(s) in a system which affects the intra molecular hydrogen bonds. In other words, in a larger system, interaction of proteins through the free chain could decrease β-sheet content.

3.3. Influence of processing conditions on secondary structure The silk component in the recombinant constructs allows for multiple modes of processing to obtain material formats fine-tuned for specific applications. Processing parameters, including solvent based β6 ACS Paragon Plus Environment

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sheet induction methods, water annealing temperature and time, have been varied to determine their effect on protein secondary structure. The nh-15mer-R5 was dissolved in water or HFIP, formed into films, and then β-sheet formation was induced via water annealing at room temperature or treatment with methanol vapor for 24 h. The nh-15mer-R5 films dissolved in HFIP or water that did not undergo a β-sheet induction procedure were included as a control. The secondary structure of these differently processed nh15mer-R5 films was analyzed by FTIR (Figure 5A). The solvent effect was a result of significantly higher protein crystallinity in the water annealed HFIP based films than in the water based water annealed films, 47.82% ± 1.72 and 34.45% ± 2.14, respectively. This effect has not been observed when methanol was used as the β-sheet induction method. In general, water annealing resulted in lower β-sheet content when compared to methanol. To evaluate the effect of the time used in water annealing (Figure 5B) and the temperature, on β-sheet content (Figure 5C), nh-15mer-R5 water based films were subjected to 1 h or 24 h water annealing treatment at room temperature, whereas the effect of the temperature was assessed after incubation of films at higher temperature (60°C). These studies indicated that increasing both the length of time in water annealing and the annealing temperature resulted in significantly higher crystalline structures. 3.4. Control over silicification process Biomineralization was performed in vitro to determine the effect of the different protein secondary structures, induced either by modifying protein sequence or processing parameters, on the ability of the constructs to precipitate silica. The influence of silk and silk-silica sequence on the silicification process was assessed by SEM (Figure 6A). The position of the biomineralization domain had little effect on silicification when the protein was dissolved in water and water annealed at room temperature for 24 h. Interestingly, the control sample, nh-15mer lacking the R5 domain but carrying a His-tag at the Nterminal domain, induced silica precipitation. To verify that the silica precipitation could be attributed to the positively charged His-tag, 15mer constructs lacking a His-tag were prepared and this protein failed to support silicification (Figure 6B). Furthermore, biosilicification on poly(lysine) modified B. mori silk,29 highly positively charged cocoon silk, resulted in silica precipitation, whereas negatively charged poly(glutamic acid) modified B. mori silk29 did not induce silica precipitation. These results showed that the silicification process was not sequence specific, as both His-tag and poly(lysine) domains were able to induce the precipitation of silica. In addition, the previously designed H(AB)12 silk-like construct with modified silk domain when compared to the nh-15mer, and harboring the same His-tag at the N-terminus of the protein6 was analyzed for the importance of the silk sequence in the process. The core silk sequence did not impact biomineralization and the driving factor was the positively charged amino acids. Interestingly, when the histidine tag was placed at the C-terminal domain of the recombinant spider silk construct, low silica precipitation was observed. Although the 15mer-ch and nh-15mer-silaffin proteins had similar β-sheet content, 30.18 ± 1.08% and 30.54 ± 1.76%, respectively (Figure 3), their potential to induce silica precipitation was different. These results demonstrate that the secondary structure did not influence protein function, but rather protein folding and exposure of the positively charged amino acids. Computational modeling was performed to determine the mechanism by which protein folding and secondary structure influence biomineralization. Figure 7 shows solvent accessible surface areas for the different positively charged amino acids in the various protein constructs: Histidine (H), Arginine (R) in silk or R5 bonding peptide and Lysine (K). Putting a histidine tag on the C-terminus resulted in less exposure of the histidines and arginines (Figure 7A). Moreover, silk and silk-ch showed the least total SASA of positively charged amino acids among all protein constructs (Figure 7D). This result correlates well with the results from the experiments that showed no or low silicification in those two cases (Figure 6 A, 15mer-ch and Figure 6 B, 15mer). We conclude that there is a minimum value for the SASA of charged amino acids in order to initiate silicification, 14.22 ± 0.68 nm2 for a single protein is the smallest value which resulted in silicification for the nh-silk constructs. Figure 7B shows that switching the R5 position resulted in differences in the availability of R and K for silicification, but did not affect the



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exposure of H. While the total charges SASA for the nh-silk-R5 were greater than for R5-silk-ch, the difference was small, which could explain the minimal effect on silicification observed in experiments. The effect of different processing parameters on protein secondary structure and silicification was assessed. Films formed from the recombinant proteins were varied in terms of solvent (water or HFIP) and β-sheet induction method (methanol, water annealing, water annealing time, water annealing temperature). By controlling processing parameters and protein sequence, the protein folding, final secondary structure and biomineralization features were tunable. The effect of protein solvent on silica precipitation is shown in Figure 8, indicating that HFIP based films resulted in higher β-sheet content (Figure 5) and low silica precipitation. Induction of β-sheet structure by methanol vapors had a similar effect on crystallinity and biomineralization (Figure 8). Water annealing time had minimal effect on the silicification process, however, this variable was inversely related to the water annealing temperature, with 22°C inducing the most optimal silica precipitation (Figure 8). 3.5. Control of silica particle size The deposited silica particle size analysis was carried out to determine the influence of the protein sequence and β-sheet content on particle diameter. Water based recombinant protein films were prepared and water annealed for 24 h at room temperature to induce β-sheet formation. After in vitro silicification reactions the films were imaged by SEM and the diameter of the silica particles was measured (Figure 9). The average particle size was inversely proportional with β-sheet content. Moreover, a larger particle size distribution was observed with decreasing crystallinity. In addition, the higher the number of charged amino acids the higher average particle diameter and larger size distribution. Interestingly, the position of R5 domain did not have impact on particle size distribution. Figure 7C shows the decreased availability of H and increased availability of R and K for the nh-silksilaffin compared to the nh-silk-R5. For the nh-silk-silaffin, the total amount of charged SASA was around 2.7 times larger (58.45 ± 1.27 nm2 versus 21.83 ± 0.8 nm2) than for the nh-silk-R5. Compared to all other proteins (Figure 7D), the nh-silk-silaffin had the largest solvent charged SASA which explains the higher average of particle diameter for this protein. 4. Discussion Computational approaches have proven useful in advancing the understanding of the ability of recombinant silks to form secondary structures and to further elucidate fundamental relationships between sequence and material properties.5,47 In parallel, genetic engineering provides a pathway to selectively analyze the influence of different silk domains on protein structure.26,48 As demonstrated in this study, the same approach is also applicable to functionalized recombinant spider silk, where the proteins are designed through combinatorial positioning of 3 domains: His-tag for protein purification, a core spider for crystallinity of the materials and processing, and a biomineralization domain (R5 or silaffin) for silica precipitation. The biomineralization R5 functional domain was positioned at the C- or N-terminal domain of the spider silk, and did not affect the crystallinity or the biomineralization potential of the proteins. In contrast, the N-terminal/C-terminal location of His-tag, as well as the addition of R5 multimer (silaffin) to C-terminal domain, significantly impacted the β-sheet content. This suggests that in addition to protein sequence, control over the position of the functional domain may provide an additional mode to regulate protein folding. While the influence of localization of the fusion domain on protein folding and solubility has been previously shown,49,50 it has not been used for protein design purposes in multiscale prediction platforms as was pursued here. Importantly, not all alterations in protein secondary structure result in modified protein function. For instance, even though protein secondary structure of nh-15mer-R5 and nh-15mer-silafin is different, their 8 ACS Paragon Plus Environment

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potential to induce silica precipitation is similar. In contrast, the secondary structure of nh-15mer-silaffin and 15mer-ch is similar, but nh-15mer-silaffin is a better catalyzer of silicification. Computational modeling showed that placing the histidine tag on the C-terminus resulted in less exposure of the histidines and arginines and that silk-ch showed the least total SASA of the positive charged amino acids among all protein constructs. This explains the experimental results showing low silicification for this protein. Furthermore, modification of the solvating agent significantly influenced both the protein secondary structure and function towards mineralization. Thus, the protein secondary structure plays a minor role in determining the potential of the protein to induce silicification, whereas folding and exposure of charged functional groups play key roles in biomineralization. While the critical role of positively charged domains for the initiation of silicification, independent of the specific amino acid, has been previously demonstrated,51–53 the influence of differences in protein folding on the exposure of these domains on has not been assessed. Modeling showed that there is a minimum value for the SASA of charged amino acids in order to initiate silicification, 14.22±0.68 nm2 for a single protein is the smallest value which resulted silicification for the nh-silk construct. Additionally, switching the position of the R5 resulted in differences in the availability of R and K for silicification, but did not affect the exposure of H. This integrated modeling/experimental approach demonstrates that although silk sequence does not impact the biomineralization process directly, it does guide protein folding and determines the exposure of positively charged amino acids, subsequently available for mineralization. Biomaterial fabrication allows for an additional level of fine tuning protein secondary structure. There are numerous cases where the mechanical properties of recombinant spider silk can be modified by controlling processing parameters.5,6,47,54 Thus, the processing conditions should be selected to allow for optimal protein folding and subsequently function. The present study demonstrates the influence of solvating agent, β-sheet induction method and β-sheet induction conditions on protein folding and thereby silicification. The significantly higher β-sheet content of water annealed HFIP based films than water based films, 34.5% and 47.8%, was confirmed. In addition, room temperature water annealing treatment resulted in lower β-sheet content when compared to methanol. This is in agreement with previously reported results on B. mori silk, showing high β-sheet content for MeOH treated silk films reaching up to 55% and significantly lower β-sheet content for films water annealed at room-temperature (~30% βsheet).55 Similar results have been shown for recombinant spider silk.6,47 Furthermore, increasing the time of water annealing and the temperature resulted in significantly higher crystalline structure content in the materials. In addition to the unique features of silk (biodegradability, biocompatibility, material properties), the protein can be useful as a blank template to incorporate functionalities and expand promising options for numerous applications in regenerative medicine. Functionalization of spider silk for bone regeneration has been well studied.7,22 As a prototype, spider silk has been widely studied with diversified characterization or simulation methods, exploiting multiscale engineering approaches to gain insight into structure-function relationships. Nevertheless, integrated modeling and experimental approaches to identify optimal design and processing conditions and their use for tight control of biomineralization has not been pursued. The present study provides a new platform for predictive biomaterial design and its use to control protein function related to mineralization. Advances in biomaterial science and biomedical engineering are dependent on the efficiency of biomaterial design in terms of the ability to fine tune material properties for specific applications. The integrated approach of genetically programmed protein polymer and material synthesis coupled with molecular modeling presented here, provide efficient predictions of functional properties for the biomaterials, in this case propensity for mineralization. 5. Conclusions The present work demonstrates the development of a predictive approach to biomaterial design by integrating modeling and experimental approaches. The approach allows for efficient identification of key 9 ACS Paragon Plus Environment


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parameters in material design to control function, here the focus is on mineralization via silica. This guided protein design scheme provides valuable insight into key factors such as protein folding, and exposure and alignment of charged units. This approach overcomes some of the disadvantages inherent in current protein design processes by providing directions to fine tune protein sequence and processing parameters to allow for optimal protein folding for biomineralization. The development of a predictive platform for specific protein design should provide new inroads into the bioengineering of wide range of functional biomaterials. Acknowledgments We thank the NIH (U01 EB014976, R01 DE017207) for support of this work. The computational resources used for this project were provided by the National Science Foundation through the Extreme Science and Engineering Discovery Environment (XSEDE) and the Texas Advanced Computing Center under Grant Numbers TG-DMR140101 and TG-MSS090007. References (1)

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TOC figure


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Figure 1. Schematic of designed silk-silica fusion proteins and recombinant production of the constructs. A. Schematic representation of designed fusion proteins, His-tag (yellow box) added to spider silk 15mer (dark blue box) at the N-terminal end of nh-15mer and nh-15mer-R5 constructs, and C-terminal end of 15mer-ch and R5-15mer-ch constructs; R5 domain (green box) added to the C-terminus of nh-15mer-R5 and N-terminal of R5-15mer-ch, whereas silaffin (dark green box) was added to the C terminus of nh15mer-silaffin; B. SDS-PAGE of purified recombinant silk-silica chimeric proteins nh-15mer (40 kDa), nh-15mer-R5 (43 kDa), 15mer-ch (40 kDa), R5-15mer-ch (43 kDa) and nh-15mer-sillafin (55 kDa), run on the 4%-12% Bis-Tris acrylamide gel and stained with Simple Blue dye. Marker (M) sizes are indicated on the left; C. Underlining amino acid sequence of silk and silk-silica fusion proteins.



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Figure 2. Simulation of protein folding. A. The simulation procedure. The procedure starts with initial prediction of the protein structure from homology modeling. Replica exchange simulations in implicit solvents (water and ethanol) are performed to find protein folding at ambient (300 K) temperature. For each case, the most probable structure was selected using single linkage clustering algorithm. The representative structures were then refined in explicit solvents and average properties reported from the last 10ns simulation. B. Sample snapshots of different protein structures in explicit water. β -sheets and random coils are colored in blue and white, respectively. Histidine, Arginine (in silk block), Arginine (in R5 bonding peptide) and Lysine are charged residues of the proteins which are color coded in yellow, red, orange and green, respectively.


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A

B

C

Figure 3. Convergence during equilibration of structures with explicit solvent. The decreasing rate of change in (A) root-mean-square deviation (RMSD), (B) solvent accessible surface area (SASA), and (C) total β-sheet content indicate sufficient convergence of the structures for each case. Further equilibration is not considered essential. The properties are reported by averaging over the last 10 ns of simulation in each case.



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Figure 4. The influence of recombinant silk and silk-silica sequence on β-sheet content determined by FTIR (orange line) and modeling (blue bars). The effect of the presence of the R5 domain on β-sheet content was analyzed for nh-15mer and nh-15mer-R5; the effect of the position of R5 was analyzed on nh-15mer-R5 and R5-15mer-ch; the effect of the number of R5 repeats on β-sheet content was analyzed for nh-15mer, nh-15mer-R5 and nh-15mer-silaffin. Films were prepared in water and β-sheet formation induced via water annealing at room temperature for 24 h (n=3, p

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