Molecular Design of a Minimal Peptide Nanoparticle - ACS Publications

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Molecular design of a minimal peptide nanoparticle Raja Dey, Yan Xia, Mu-Ping Nieh, and Peter Burkhard ACS Biomater. Sci. Eng., Just Accepted Manuscript • DOI: 10.1021/acsbiomaterials.6b00243 • Publication Date (Web): 25 Jul 2016 Downloaded from http://pubs.acs.org on July 25, 2016

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Molecular design of a minimal peptide nanoparticle Raja Deya, Yan Xiaa, Mu-Ping Nieha, and Peter Burkhard a,b,$ a

Institute of Materials Science, University of Connecticut, Storrs, CT 06269-3136, USA

b

Department of Molecular and Cell Biology, University of Connecticut, Storrs, CT 06269-3125,

USA $

To whom correspondence should be addressed

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Abstract Nanoparticles are getting a great deal of attention in the rapidly developing field of nanomedicine. For example they can be used as drug delivery systems, for imaging applications, or as carriers for synthetic vaccines. Protein-based nanoparticles offer the advantage of biocompatibility and biodegradability thus avoiding some of the major toxicity concerns with nanoparticle associated approaches. Our group has developed self-assembling peptide/protein nanopartices (SAPNs) that are built up from two coiled-coil oligomerization domains joined by a linker region and used them to design subunit vaccines. For drug delivery approaches the SAPNs need to be as small as possible to avoid strong immune responses that could possibly even lead to anaphylaxis. Here we used a computational and biophysical approach to minimize the size of the SAPNs for their use as drug delivery system. We were testing different charge distributions on the pentameric and trimeric coiled-coils in silico with molecular dynamics simulations to down-select an optimal design. This design was then investigated in vitro by biophysical methods and we were able to engineer a minimal SAPN of only 11 nm in diameter. Such minimal-sized SAPNs offer new avenues for a safer development as drug delivery systems or other biomedical applications. Keywords Peptide nanoparticle, protein design, drug delivery, molecular dynamics simulation, selfassembly

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INTRODUCTION Nanoparticular systems for therapy and diagnosis have been constructed using many different types of materials ranging from inorganic metals to organic polymers 1. Some of these approaches have yielded very promising and appealing results. However, biodegradability and biocompatibility represent major issues that could potentially prevent their in vivo application 2. Proteins, which are fully biodegradable and biocompatible, represent ideal materials for biomedical applications. Protein-based nanoparticles can be used for many diverse purposes, and - if bacterially expressed - they are easy and cost-effective to produce. For drug delivery larger structures than single proteins such as nanoparticles or nanocages might be ideal carriers. Viruses are natural delivery systems, so particles designed to mimic them are thought to be very effective for drug, gene, and antigen delivery 3. Virus-like particles are therefore a very attractive system for drug, gene, and antigen delivery 4. Bacterial microcompartments and eukaryotic vaults are other types of protein-based nanoshells that are being explored for the transport of biomedically active substances 5. Despite of these advantages of protein-based nanomaterials, they suffer from their own potential immunogenicity that might lead to host immune responses and potentially trigger anaphylaxis, thus potentially limiting their use for biomedical applications. Already several decades ago this has been shown to be related to the so-called immunon 6, in which particulate systems of the size of small viruses are much more immunogenic than smaller particles due to number of and the distances between antigens on the surface of the nanoparticles. This is also known as “repetitive antigen display” leading to a strong immune response 7. To design peptide/protein-based nanoparticles that can be used for drug delivery purposes it is therefore imperative to reduce the size of the particles below 20 nm, ideally even below 15 nm to reduce the risk of an anaphylactic shock.

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Over the last decade we developed Self-Assembling Protein Nanoparticles (SAPNs) 8. We have demonstrated their potential as a platform for vaccine design and successfully developed malaria 9, HIV

10

, influenza

11

, SARS

12

and toxoplasmosis

13

vaccine prototypes. These SAPNs

are built from a single peptide chain that comprises two α-helical coiled-coil segments connected by a short linker region. One coiled-coil helix forms a pentameric coiled coil while the 14

other forms a trimeric coiled coil (see Figure 1a & Figure 1b in reference highly versatile and ubiquitous protein folding and oligomerization motif

). Coiled coils are a

15

. Most of the α-helical

coiled coils are characterized by a heptad repeat pattern that contains mainly hydrophobic amino acids at the positions a and d in a seven amino acids long repeat-pattern denoted abcdefg, thus the main driving force for coiled-coil formation are the hydrophobic interactions between residues in positions a and d of the heptad repeat. Intra-helical and inter-helical ionic interactions between residues can further significantly stabilize coiled coil oligomers 16. Here, we describe how the charge distribution, the total charge within each oligomerization domain, and the overall charge of the whole peptide can control the formation of a functional nanoparticle. We have designed thirteen different, 36 amino acid residues long constructs with various charge distributions within the pentameric and trimeric coiled-coil domains. Initial threedimensional models were built in silico followed by molecular dynamics simulations to optimize their structure. The best two peptide constructs from the molecular dynamics study were selected to study its in-vitro behavior using different biophysical techniques.

For the best

peptide we found well-folded nanoparticles of about 11 nm in diameter, confirmed by dynamic light scattering, transmission electron microscopy imaging, and small angle X-ray scattering techniques.

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MATERIALS AND METHODS Model building An exhaustive search of RCSB protein database for structurally similar proteins with the helixturn-helix motif was carried out in identifying the linker region of our model peptide aimed at forming a mini-nanoparticle under physiological buffer conditions

14

. A three dimensional model

has computationally been built as described in our recent manuscript

14

. This is our starting 3D

model (parent): 36 residues long, with the linker region covalently connecting the N-terminal tryptophan zipper and C-terminal leucine zipper (see Figures 1a & 1b of reference

14

, Table 1).

This parent peptide was modified to contain only charged amino acids at the non-core positions (b, c, e, f and g) of the first two and last two heptad repeats, while the middle portion of the peptide joining the pentamer and trimer was left as in refs

14, 17

. Six peptides 1 to 6 have been

built from the parent peptide by N-terminal protonation and C-terminal deprotonation. The next six peptides 1a to 6a have the same sequences but carry no N-terminal protonation (Table 1), which is with respect to the charge comparable to N-terminal acetylation. Initial threedimensional models of these peptides are shown in Figure 1. Finally, another version of peptide 5 - called peptide 5b - has been designed with N-terminal acetylation and C-terminal amidation to test the behavior of the peptide without terminal charges. All the mutations, N-terminal acetylation/protonation, and C-terminal amidation/deprotonation were done using the graphics program ‘O’ version 12.0.1

18

and PyMOL version 1.6.0.0

19

. Amino acid sequences of these

peptides are given in Table 1, where the mutations with respect to the parent peptide are shown in red color and the changes of the charged residues between the six peptides in each set are highlighted in yellow. Molecular dynamics simulation These thirteen different, 36 amino acid residues long constructs were studied by molecular dynamics (MD) simulations with CHARMM 36b1

20

. Initial 3D model coordinates of all the 5

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thirteen constructs were fist converted into CHARMM formats using the web interface at ‘www.charmming.org/charmming/’. The pentameric and trimeric domains of the peptide chain were aligned along the 5-fold and 3-fold symmetry axes of an icosahedron, respectively. Simulating a complete icosahedral nanoparticle in solution within a spherical volume of 75 Å radius around it is computationally very time-consuming as the whole solvated system contains about half a million variables. In contrast, an wedge shaped asymmetric unit can be built by cutting the whole system along the four planes between the rotational axes, i.e. between the 5fold and 2-fold, 2-fold and 3-fold, 3-fold and 2-fold, and 2-fold and 5-fold axes (see Figure 6 of reference

14

). During MD simulations only the interactions within this wedge and its symmetry-

related neighbors have to be calculated, which makes the MD runs much less time consuming. To simulate one single peptide chain representing a whole particle, the peptide was projected as having mirror atoms along the relevant rotational axes of the icosahedron utilizing the IMAGE option within the program CHARMM. Thus, applying 59 transformation matrices to the initial model the entire particle with icosahedral symmetry was generated. Rotational symmetry boundary constraints (RSBC) were applied during the MD simulation. The whole MD simulation procedure is divided into five steps: vacuum minimization, solvation, energy minimization, heating and equilibration, and production dynamics (Figure 2). Vacuum minimization was performed to remove possible close steric contacts from the initial model. Then the peptide molecule was solvated and ions were added to achieve a 150mM salt concentration. The energy minimization was performed to optimize the whole system containing the peptide, water and ions. In the energy minimization step we used the steepest descent (SD) method for a shorter time period of 50 steps followed by the adopted basis Newton Raphson (ABNR) method for a longer time period of 50000 steps, where each step corresponding to 1 fs. The SD method is mainly used to remove the initial close contacts to rapidly improve the conformation if it is far from the minimum. ABNR is a more precise minimization algorithm that is able to detect at what time point the system has converged. The ABNR method exits automatically when the energy 6 ACS Paragon Plus Environment

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change in two consecutive steps is less than 0.01 kcal/mole. After the energy minimization of the whole system, the temperature was slowly raised at a rate of 10°/1000 steps from an initial temperature of 100 K to 300 K to relax the molecule and then to run the equilibration for a total time period of 100 ps including the time to raise the temperature. For initial screening production dynamics of 2 ns were run thereafter on the whole system. Long 10 ns production dynamics were then performed on the best models of the 2 ns runs. These computational steps calculate the time-dependent behavior of a molecular system. An MD simulation with a leap-frog verlet algorithm provides the detailed information of the fluctuations and conformational changes of peptide molecules. Given the atomic positions (x) at time step t and the velocities (V) at t - ∆t/2, the leapfrog verlet integrator computes the positions at t + ∆t and the velocity at t + ∆t/2. Thus, the velocities are computed at midpoints between the time steps. Peptide purification We ordered the synthetic peptides 5 and 5b (Table 1) from Biomatik (http://www.biomatik.com, Biomatik USA, LLC, 501 Silverside Road, Suite 105, Wilmington, Delaware, 19809, USA) for in vitro biophysical characterization. The peptides were dissolved in 50mM Tris, 8M Urea at pH 8.0 and purified under denaturing condition using HiTrap Q Sepharose High Performance anion exchange column with a Fast Protein Liquid Chromatography system. After equilibration of the column with this buffer, the peptides were eluted by a NaCl salt gradient using the same buffer with the addition of 1M NaCl. Peptide purity was verified by sodium dodecyl sulfate polyacrylamide gel electrophoresis. Refolding of the peptides Following purification the denatured monomeric polypeptide was stepwise refolded by dialysis from 8 M urea to 6 M urea, 4 M urea, 2 M urea and 0 M urea in a buffer containing 50 mM NaCl, 5% glycerol, 20 mM Hepes at pH 7.0. Finally, the peptide concentration was measured by UV absorption at 280 Å using a Nano Drop-2000 instrument in 50 mM NaCl, 5% glycerol, and 20 7 ACS Paragon Plus Environment

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mM Hepes at pH 7.0. We also dialyzed peptide 5b at different pH ranging from 7.0 to 8.5 and in varying salt concentration from 40mM to 300mM to study the change in particle size created by this construct. Dynamic light scattering The hydrodynamic diameter was determined with a Malvern Zetasizer Nano S equipped with a 633 nm laser using a 3 mm path length quartz suprasil cell. The measurements of the volumeaverage hydrodynamic sizes were performed with the Malvern DTS software, version 6.01 at 25°C using 60 µl samples at a concentration of 0.86mg/ml. For each sample five scans were collected and the average was calculated. Transmission electron microscopy imaging 3 µl of sample at a concentration of 60 µg/ml was placed on a 400 mesh copper grid coated with a formvar/carbon film (Electron Microscopy Sciences, PA, USA) for 1 min. The grid was washed by two to three drops of 5 µl distilled water. Excess water was removed with Whatman filter paper. The sample was negatively stained with 3 µl 0.5% uranyl acetate (SPI Supplies, PA, USA) for 30 sec. Excess stain solution was removed with Whatman filter paper, before the grid was slowly dried at room temperature. Electron micrographs were taken with an FEI Tecnai T12 transmission electron microscope at an accelerating voltage of 80 kV. Small angle X-ray scattering Small angle X-ray scattering (SAXS) measurements were conducted on a Bruker NanoSTAR instrument. X-rays were generated by a Turbo (rotating anode) X-ray source (TXS). A wavelength of 1.5418Å was chosen by Cukα using the Göble mirror. The beam was collimated by a pair of scatterless pinholes with the diameters of 500 (first) and 350 (second) µm, respectively. The 2-D intensity data of the sample (3 mg/mL protein solution) and buffer were collected individually by a MikroGap VÅNTEC-2000 detector with a sample-to-detector distance

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of 67 cm to cover a scattering vector, q [|| ≡

 sin , 

where θ is the scattering angle range

from 0.01 to 0.37 Å-1. The SAXS 2D scattering patterns of solutions and buffer were corrected by their transmissions. Afterwards, 1-D SAXS data of the protein solution were obtained by circularly averaging around the beam center after the subtraction of the solvent scattering background.

RESULTS AND DISCUSSION The peptide chain of the nanoparticle contains a pentameric and a trimeric coiled coil joined by a linker region that has previously been optimized by a structural approach

17

. The pentameric

domain contains tryptophan residues at the coiled-coil core positions a and d of the heptad repeat – a so-called tryptophan zipper

21

– and forms homo pentamers in solution largely driven

by hydrophobic interactions at the coiled-coil interface. On the other hand, the C-terminal trimeric domain consists of a leucine zipper peptide with leucine residues at the coiled-coil core positions a and d and forms trimers in solution driven by similar hydrophobic interactions. Assuming that this peptide forms a nanoparticle with icosahedral symmetry in solution, it will assemble 60 identical chains into a single particle (see Figures 1c and 1d of reference

14

). An

icosahedron has 2, 3 and 5-fold symmetry axes, and each of its 20 triangular faces has a 3-fold symmetry. Hence each triangle can be subdivided into 3 equal portions. If each portion contains one protein, a total of 60 peptides will form the icosahedron, in which each peptide chain is in exactly the same environment. We have recently shown in a biophysical and structural analysis and comparing with a tiling algorithm that these nanoparticles can also form higher order oligomeric structures with different multiples of 60 chains per particle, however, these larger particles will not have regular icosahedral symmetry of one single peptide chain 8a. In our previous work, we have also shown the importance of the linker region in the development of a functional nanoparticle in vitro

14, 17

. In continuation of this research, here we 9

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study the effect of charge modifications on the structure and functional behavior of the SAPNs. To design the smallest possible nanoparticle the peptide chain needs to be as short as possible. We have shown that highly charged coiled-coils stabilized by inter- and intra-helical salt bridges can be very stable 16a, 16b. Therefore we designed a series of highly charged peptides by keeping hydrophobic residues only at the core position of the pentameric and trimeric coiled coil (Table 1). We wanted to optimize the charge distribution in the pentamer, the trimer and the overall sequence. The overall charge of the peptide will govern the assembly behavior of the nanoparticles in solution. If nanoparticles are formed with a large negative overall charge the nanoparticles will repel each other in solution. Along with the reduction of the overall negative charge the repulsion between nanoparticles will be reduced possibly leading to aggregation of the nanoparticles. Also, if the peptide chains are too negatively charged, individual peptides will repel each other thus preventing peptides to self-assemble to nanoparticles in the first place. In our designs we varied to overall charge from 0 (peptide 1) to -7 (peptide 6a). The total charge of the individual oligomerization domains of the pentamer and the trimer will determine whether the trimer and pentamer will be attracted or repelled from each other. If both oligomers carry the same charge, then there will be a repulsion between the pentamer and the trimer. If they carry opposite charges, then the trimer and the pentamer will attract each other. In our designs we kept the trimer largely negative varying only between -3 and -5 overall negative charge. The pentamer though was designed to vary from largely positive charge (+5, peptide 1) to slightly negative charge (-1, peptide 6). Thus, in peptide 1 there will be a strong attraction between the pentamer and the trimer while in peptide 6 there will be a repulsion between these two different types of coiled coils. In the first set of peptides the termini of the peptides were considered to be free, i.e. both Nterminal protonation and C-terminal deprotonation have been used in the first set of 6 constructs (peptide 1 to 6 – Table 1). Initial models of these 6 peptides are shown in Figure 1, where the

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mutated residues relative to the parent peptide are colored in red. The difference within the six peptides are highlighted in yellow in Table 1. Initially, we performed a 2ns molecular dynamics (MD) simulation for the six constructs at 150 mM NaCl salt concentration. Final models of these peptides after 2ns MD simulation are shown in Figure 3. Two of these constructs, peptide 1 and peptide 4, have been found to deform at the N-terminal end of the pentameric helix, while in peptide 6, the C-terminal end of the trimeric helix has been distorted (Figure 3). Both intra and inter oligomeric domain ioinc interactions are responsible for the deformations observed in these three peptides. The remaining three peptides 2, 3 and 5 have been found to maintain their helical conformation for both oligomeric domains (Figures 3) and so they were retained for further analysis. The designs of the second set of 6 constructs, peptides 1a to peptide 6a, are identical to the peptides 1 to 6, respectively, except the N-terminal protonation is omitted in these six peptides leaving uncharged N-terminal ends. The molecular structures of these six peptides were also analyzed in silico after 2ns MD simulation. We found that the absence of N-terminal protonation causes an unstable conformation with some degree of deformation in each of these peptides (Figures 3) and so, we disregarded them for further analysis. RMS deviations and radii of gyrations for the three best constructs (peptides 2, 3, and 5) and nine bad constructs (peptides 1, 4, 6, 1a, 2a, 3a, 4a, 5a, and 6a) are plotted against the simulation time (Figure 4). While peptide 6a retains a largely α-helical structure (Figure 3n), the C-terminal helix deviates a little more from the original conformation, which is also apparent from its higher rms deviation during the molecular dynamics run (Figure 4c). Radii of gyrations shown in Figure 4d are more fluctuating in comparison to what was observed in Figure 4b and the RMSDs observed in Figure 4c have a diverging tendency while in Figure 4a it looks more stable in nature. Although graphical plots of RMSD and radii of gyrations alone could not bring the final conclusion of initial screening, the visual inspection of the simulated models in slico helped to 11 ACS Paragon Plus Environment

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make a final decision on selection of good constructs. Three best constructs (peptides 2, 3, and 5) were selected for longer MD simulation runs of 10ns. Variation of RMSD and radii of gyrations are plotted against the simulation time for these good constructs (Figure 5). Peptide 3 (in green) seems to diverge, whereas peptides 2 (in red) and 5 (in light blue) have converged after 8ns MD simulation (Figure 5a). Peptide 5 showed the lowest stable radii of gyrations up to 7ns and then it increases slightly, and finally returns to near the stable value after 10ns MD simulation. Three-dimensional structural analysis of peptides 2 and 5 showed that the Cterminus end of the trimeric domain in peptide 2 deformed after 10ns MD simulation (Figure 5c), while the helical structure of peptide 5 remained during the entire simulation period (Figure 5d). For this reason peptide 5 was preferred over peptide 2 as the integrity of the α-helical structure was deemed more important than the overall convergence of the radius of gyration and the rmsd compared to the parent structure. Both intra (E26-R30) and inter (K11-E27) helical saltbridge interactions (Figure 5d), observed in silico structural analysis, could be responsible for the stable helical conformation in peptide 5. Unmodified peptides carrying positive and negative charges at the N and C-terminal ends are prone to be modified in physiological condition. Modification by N-terminal acetylation and Cterminal amidation will make both termini uncharged and thus leave the overall charge of the peptide unchanged. These modifications are expected to increase the stability of the peptides and could eventually maintain a better overall conformation, and inter-helical angle after MD simulation. With this aim in mind, we ran an MD simulation for 10 ns with the best peptide that contains no extra charges at both ends - called peptide 5b (Table 1). A comparison between peptide 5b versus unmodified peptide 5 is shown in Figures 5e and 5f. Better stability of the modified peptide is clearly revealed in both the variations of RMSD and radii of gyration versus simulation time.

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After careful observation of the molecular structures in 3D and analysis of the data from 10ns MD simulation we finally selected the best-behaved peptides 5 and 5b for biophysical characterization. We further purified peptides 5 and 5b under denaturing conditions by HiTrap HP Q column using our FPLC system. We observed a sharp single peak in the chromatogram indicating monodispersity in solution for both peptides. After stepwise removal of urea the concentration of the peptide was 0.86 mg/ml. For peptide 5 a mixture of a larger size nanoparticle of 43.6 nm and an aggregate was observed by dynamic light scattering (data not shown), while for peptide 5b the presence of a single oligomeric species in solution was found (Figure 6b). The better biophysical and structural behavior of peptide 5b than peptide 5 can be explained by the better charge distribution within the peptide chain in peptide 5b. In this peptide the pentamer and trimer carry both on overall charge of -2 while in peptide 5 the charges are uneven (-1 versus -3 for pentamer and trimer, respectively). A series of DLS studies were performed with peptide 5b at different salt and pH conditions (Table 2, Supplemental Figure S2). At a constant salt concentration of 120mM the dimension of the assembled nanoparticle varies from 12.86 nm to 6.93 nm as the pH increases from 7.0 to 8.5. Most likely this is due to an increased overall negative charge of the peptide at higher pH values leading to increased charge repulsion between individual peptides. As a result fewer peptide chains will assemble into one single particle and vice versa for lower pH values more peptides chains can assemble into a single particle. Such particles will not have regular icosahedral symmetry anymore. This is in agreement with our recent study of the biophysical behavior of SAPNs 8a. Similar results were obtained at a salt concentration of 150mM. On the other side, the dimension of the nanoparticle only slightly increases with increasing salt concentration at constant pH of 8.5 (Table 2). For peptide 5b we found a reasonably good overall size peptide nanoparticle of about 11 nm in diameter at physiological conditions (Figure 6b). This is in good

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agreement with the predicted structure from the molecular dynamics studies of the nanoparticle constructs. A transmission electron microscopy imaging experiment was performed with peptide 5b (Supplemental Figure S1) under different pH and salt condition. The sizes of the majority of the spherical particles are in good agreement with the sizes observed in the DLS experiments at a particular buffer condition. From these in vitro studies we confirmed that the particle size is more sensitive to pH than to salt concentration. Finally, at physiological conditions a nanoparticle with a size of about 11 nm in diameter is measured by visual inspection of the EM image of peptide 5b (Figure 6a). Transmission electron microscopy imaging experiments with peptide 5 did not show any nanoparticulate structures. We then also ran SAXS experiments to further verify the size and shape of the mini-SAPNs formed by peptide 5b. Figure 6c shows the reduced SAXS 1D data of peptide 5b at a concentration of 3 mg/mL. ln(I) is linear with q2 in the low-q regime as shown in the inset of Figure 6(c), known as the Guinier plot. The slope of the line is –1/2/3 with being the square of radius of gyration of peptide 5b as described in Eq(1):  = ln  −

   , 

(1)

where I0 is the scattered intensity at q = 0. The Guinier analysis yields a 1/2 of 40.5 ± 0.9 Å, implying that the best fitting range was q(1/2) ≤ 1.3. Under the assumption of spheres, 

where  =   , the geometrical radius R can be calculated to be 52.3 Å, which agrees well with the hydrodynamic radius from the DLS measurements and the observed particles in the TEM analysis. Thus, the average size of the assembled mini-SAPNs obtained by DLS, EM imaging and SAXS techniques are in very good agreement with the predicted nanoparticle architecture from the molecular dynamics runs.

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CONCLUSIONS Peptide 5b forms a mini-SAPN of 11 nm in diameter. This size is expected to avoid the induction of a strong immune response related to the so-called immunon 6, i.e. is significantly smaller than the size of small viruses thus avoiding the immunogenicity due to the number of and the distances between antigens on the surface of the nanoparticles. With an overall charge of -4 per peptide, 60 identical chains accumulate a total charge of -240 per particle. Based on our computational and experimental studies it is more likely that the overall charge of -4 per peptide can form good mini-SAPNs. Presumably, these mini-SAPNs built from peptide 5b repel each other thus avoiding aggregation under physiological conditions. Therefore, our mini-SAPNs should be suitable for a variety of biomedical applications such as drug delivery systems or as bio-imaging tools as they have the ability to incorporate colloidal gold or quantum dots at the central cavity 22.

ASSOCIATED CONTENT *S Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: XXX. TEM and DLS data of peptide 5b at different buffer conditions.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]. Tel: 860-486-3830. Fax: 860-486-4745

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Author Contributions PB and RD contributed to the design of the experiments, RD (modeling, purification, TEM, DLS) and YX (SAXS), performed the experiments, RD and PB wrote the manuscript. All authors read and modified the text and were involved in interpretation of results and approved the final manuscript. Notes The authors declare the following competing financial interest(s): PB has an interest in the company Alpha-O Peptides that has patents or patents pending on the technology.

ACKNOWLEDGMENTS Support

by

the

NIH/NIDA

(award

1DP1DA033524)

and

the

NIH/NIGMS

(award

1P01GM096971) to PB for this work is gratefully acknowledged. M. - P. Nieh and Y. Xia would like to thank the NSF-MRI support for the acquisition of SAXS instrument (NSF DMR 1228817) enabling the structural characterization.

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REFERENCES 1. Doll, T. A.; Raman, S.; Dey, R.; Burkhard, P., Nanoscale assemblies and their biomedical applications. J R Soc Interface 2013, 10 (80), 20120740. 2. Sharifi, S.; Behzadi, S.; Laurent, S.; Forrest, M. L.; Stroeve, P.; Mahmoudi, M., Toxicity of nanomaterials. Chem Soc Rev 2012, 41 (6), 2323-43. 3. (a) Edelstein, M. L.; Abedi, M. R.; Wixon, J., Gene therapy clinical trials worldwide to 2007--an update. J Gene Med 2007, 9 (10), 833-42; (b) Giacca, M.; Zacchigna, S., Virus-mediated gene delivery for human gene therapy. J Control Release 2012, 161 (2), 377-88. 4. Ma, Y.; Nolte, R. J.; Cornelissen, J. J., Virus-based nanocarriers for drug delivery. Adv Drug Deliv Rev 2012, 64 (9), 811-25. 5. (a) Corchero, J. L.; Cedano, J., Self-assembling, protein-based intracellular bacterial organelles: emerging vehicles for encapsulating, targeting and delivering therapeutical cargoes. Microb Cell Fact 2011, 10, 92; (b) Rome, L. H.; Kickhoefer, V. A., Development of the vault particle as a platform technology. ACS Nano 2013, 7 (2), 889-902. 6. Dintzis, H. M.; Dintzis, R. Z.; Vogelstein, B., Molecular determinants of immunogenicity: the immunon model of immune response. Proc Natl Acad Sci U S A 1976, 73 (10), 3671-5. 7. (a) Baschong, W.; Hasler, L.; Haner, M.; Kistler, J.; Aebi, U., Repetitive versus monomeric antigen presentation: direct visualization of antibody affinity and specificity. J Struct Biol 2003, 143 (3), 25862; (b) Bachmann, M. F.; Kalinke, U.; Althage, A.; Freer, G.; Burkhart, C.; Roost, H.; Aguet, M.; Hengartner, H.; Zinkernagel, R. M., The role of antibody concentration and avidity in antiviral protection. Science 1997, 276 (5321), 2024-7; (c) Fehr, T.; Bachmann, M. F.; Bucher, E.; Kalinke, U.; Di Padova, F. E.; Lang, A. B.; Hengartner, H.; Zinkernagel, R. M., Role of repetitive antigen patterns for induction of antibodies against antibodies. J Exp Med 1997, 185 (10), 1785-92. 8. (a) Indelicato, G.; Wahome, N.; Ringler, P.; Muller, S. A.; Nieh, M. P.; Burkhard, P.; Twarock, R., Principles Governing the Self-Assembly of Coiled-Coil Protein Nanoparticles. Biophys J 2016, 110 (3), 646-60; (b) Raman, S.; Machaidze, G.; Lustig, A.; Aebi, U.; Burkhard, P., Structure-based design of peptides that self-assemble into regular polyhedral nanoparticles. Nanomedicine 2006, 2 (2), 95102. 9. (a) Kaba, S. A.; Brando, C.; Guo, Q.; Mittelholzer, C.; Raman, S.; Tropel, D.; Aebi, U.; Burkhard, P.; Lanar, D. E., A nonadjuvanted polypeptide nanoparticle vaccine confers long-lasting protection against rodent malaria. J Immunol 2009, 183 (11), 7268-77; (b) Kaba, S. A.; McCoy, M. E.; Doll, T. A.; Brando, C.; Guo, Q.; Dasgupta, D.; Yang, Y.; Mittelholzer, C.; Spaccapelo, R.; Crisanti, A.; Burkhard, P.; Lanar, D. E., Protective antibody and CD8+ T-cell responses to the Plasmodium falciparum circumsporozoite protein induced by a nanoparticle vaccine. PLoS One 2012, 7 (10), e48304. 10. Wahome, N.; Pfeiffer, T.; Ambiel, I.; Yang, Y.; Keppler, O. T.; Bosch, V.; Burkhard, P., Conformationspecific display of 4E10 and 2F5 epitopes on self-assembling protein nanoparticles as a potential HIV vaccine. Chem Biol Drug Des 2012, 80 (3), 349-57. 11. Babapoor, S.; Neef, T.; Mittelholzer, C.; Girshick, T.; Garmendia, A.; Shang, H.; Khan, M. I.; Burkhard, P., A Novel Vaccine Using Nanoparticle Platform to Present Immunogenic M2e against Avian Influenza Infection. Influenza Res Treat 2011, 2011, 126794. 12. Pimentel, T. A.; Yan, Z.; Jeffers, S. A.; Holmes, K. V.; Hodges, R. S.; Burkhard, P., Peptide nanoparticles as novel immunogens: design and analysis of a prototypic severe acute respiratory syndrome vaccine. Chem Biol Drug Des 2009, 73 (1), 53-61. 13. El Bissati, K.; Zhou, Y.; Dasgupta, D.; Cobb, D.; Dubey, J. P.; Burkhard, P.; Lanar, D. E.; McLeod, R., Effectiveness of a novel immunogenic nanoparticle platform for Toxoplasma peptide vaccine in HLA transgenic mice. Vaccine 2014, 32 (26), 3243-8. 17 ACS Paragon Plus Environment

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14. Doll, T. A.; Dey, R.; Burkhard, P., Design and optimization of peptide nanoparticles. J Nanobiotechnology 2015, 13, 73. 15. Burkhard, P.; Stetefeld, J.; Strelkov, S. V., Coiled coils: a highly versatile protein folding motif. Trends Cell Biol 2001, 11 (2), 82-8. 16. (a) Burkhard, P.; Ivaninskii, S.; Lustig, A., Improving coiled-coil stability by optimizing ionic interactions. J Mol Biol 2002, 318 (3), 901-10; (b) Burkhard, P.; Meier, M.; Lustig, A., Design of a minimal protein oligomerization domain by a structural approach. Protein Sci 2000, 9 (12), 2294301; (c) Meier, M.; Burkhard, P., Statistical analysis of intrahelical ionic interactions in alpha-helices and coiled coils. J Struct Biol 2006, 155 (2), 116-29; (d) Meier, M.; Stetefeld, J.; Burkhard, P., The many types of interhelical ionic interactions in coiled coils - an overview. J Struct Biol 2010, 170 (2), 192-201. 17. Doll, T. A.; Neef, T.; Duong, N.; Lanar, D. E.; Ringler, P.; Muller, S. A.; Burkhard, P., Optimizing the design of protein nanoparticles as carriers for vaccine applications. Nanomedicine 2015. 18. Jones, T. A.; Zou, J. Y.; Cowan, S. W.; Kjeldgaard, M., Improved methods for building protein models in electron density maps and the location of errors in these models. Acta Crystallogr A 1991, 47 ( Pt 2), 110-9. 19. DeLano, W. L.; Ultsch, M. H.; de Vos, A. M.; Wells, J. A., Convergent solutions to binding at a proteinprotein interface. Science 2000, 287 (5456), 1279-83. 20. Brooks, B. R.; Brooks, C. L., 3rd; Mackerell, A. D., Jr.; Nilsson, L.; Petrella, R. J.; Roux, B.; Won, Y.; Archontis, G.; Bartels, C.; Boresch, S.; Caflisch, A.; Caves, L.; Cui, Q.; Dinner, A. R.; Feig, M.; Fischer, S.; Gao, J.; Hodoscek, M.; Im, W.; Kuczera, K.; Lazaridis, T.; Ma, J.; Ovchinnikov, V.; Paci, E.; Pastor, R. W.; Post, C. B.; Pu, J. Z.; Schaefer, M.; Tidor, B.; Venable, R. M.; Woodcock, H. L.; Wu, X.; Yang, W.; York, D. M.; Karplus, M., CHARMM: the biomolecular simulation program. J Comput Chem 2009, 30 (10), 1545-614. 21. Liu, J.; Yong, W.; Deng, Y.; Kallenbach, N. R.; Lu, M., Atomic structure of a tryptophan-zipper pentamer. Proc Natl Acad Sci U S A 2004, 101 (46), 16156-61. 22. Yang, Y.; Burkhard, P., Encapsulation of gold nanoparticles into self-assembling protein nanoparticles. J Nanobiotechnology 2012, 10, 42.

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Table 1 Amino acid sequence of peptide constructs ID parent 1 2 3 4 5 6 1a 2a 3a 4a 5a 6a 5b

Amino acid sequence

Overall

a d a d a d a d a d 1-DWQAWKEEWAYWTLTWKYGELYSKLAELERRLEELR-36 + RWREWRERWRKWDLTWKYGELYSKLEELERELRELE-COO3HN+ EWREWRERWRKWDLTWKYGELYSKLEELERELRELE-COO3HN+ EWEEWRERWRKWDLTWKYGELYSKLEELERELRELE-COO3HN+ EWEEWRERWRKWDLTWKYGELYSKLEELERRLRELE-COO3HN+ EWEEWEERWRKWDLTWKYGELYSKLEELERRLRELE-COO3HN+ EWEEWEERWRKWDLTWKYGELYSKLEELERELRELE-COO3HNRWREWRERWRKWDLTWKYGELYSKLEELERELRELE-COOEWREWRERWRKWDLTWKYGELYSKLEELERELRELE-COOEWEEWRERWRKWDLTWKYGELYSKLEELERELRELE-COOEWEEWRERWRKWDLTWKYGELYSKLEELERRLRELE-COOEWEEWEERWRKWDLTWKYGELYSKLEELERRLRELE-COOEWEEWEERWRKWDLTWKYGELYSKLEELERELRELE-COOEWEEWEERWRKWDLTWKYGELYSKLEELERRLRELE-NH2 Ac-

Total Charge Pentamer Trimer

-2

-1

-1

0 -2 -4 -2 -4 -6 -1 -3 -5 -3 -5 -7 -4

+5 +3 +1 +1 -1 -1 +4 +2 0 0 -2 -2 -2

-5 -5 -5 -3 -3 -5 -5 -5 -5 -3 -3 -5 -2

Table 2 DLS analysis of peptide 5b NaCl (mM)

pH

Size (nm)

% volume

Width (nm)

40 50 80 120

8.5 8.5 8.5 8.5

6.35 5.61 6.71 6.93

99.8 99.5 99.7 99.8

2.55 2.94 2.47 2.49

120 120 120 120 150

7.0 7.5 8.0 8.5 7.0

12.86 10.99 7.37 6.93 40.92

99.8 98.2 99.8 99.8 100.0

9.68 4.13 3.97 2.49 48.24

150

7.5

10.60

99.2

4.13

150 150

8.0 8.5

8.85 8.28

98.9 99.3

2.58 2.95

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Figure Legends

Figure 1. Initial models of 7 peptide constructs. Parent and peptides 1 to 6 have been built by in silico mutation on the starting model (parent). Mutated residues are highlighted in red, while the rest is shown in green color. Initial models of the other six constructs, peptides 1a to 6a, are exactly identical with the corresponding peptides 1 to 6 but without N-terminal protonation.

Figure 2. Intermediate stages during the entire simulation process. (a) solvation, (b) minimization, (c) heating, and (d) equilibration

Figure 3. Computational models of nanoparticle peptide constructs after MD simulation. Peptide constructs shown in magenta color after 2ns of molecular dynamics simulation, superposed on their corresponding initial peptides (green colors) .

Figure 4. Molecular dynamics simulation of 13 peptides for 2ns. RMS deviations (a) and radius of gyrations (b) of three good constructs (peptides 2, 3, and 5 in addition to the parent peptide) relative to their corresponding energy minimized structures after 2ns MD simulation. RMS deviations (c) and radius of gyrations (d) of nine bad constructs (peptides 1, 4, 6, 7, 2a, 3a, 4a, 5a, and 6a) relative to their corresponding energy minimized structures after 2ns MD simulation. Colors of peptides in Figures b & d are in correspond with those depicted in Figures a & c respectively.

Figure 5. Molecular dynamics simulation of three best peptides 2, 3, and 5 for 10ns. RMS deviations (a) and radius of gyrations (b) of the four peptides relative to their corresponding energy minimized structures for 10ns MD simulation. Cartoon diagram of peptide 2 (c) in red 20 ACS Paragon Plus Environment

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color and peptide 5 (d) in light blue color after 10ns MD simulation. Comparison between unmodified peptide 5 and modified peptide 5b in regard to the variation of RMS deviation (e) and radius of gyration (f) during 10ns MD simulation.

Figure 6. Biophysical studies of peptide 5b. (a) Transmission electron micrograph for peptide 5b, Particle sizes are shown relative to 100 nm scale bar. (b) Dynamic light scattering curve for peptide 5b showing monodispersity in solution. Here volumic percentage has been plotted against the size of the particle in nm. (c) SAXS data for peptide solution with Guinier plot in the inset, the R2 for the fitting of Guinier plot is 0.8926.

Supplemental Material S1 Transmission electron micrograph for peptide 5b at different pH and salt concentration. S2 Dynamic light scattering curves for peptide 5b at different pH and salt concentration. Five observations along with the average have been plotted for each condition. S3 Supplemental Figure S3 presents an electron microscopy image of the unmodified peptide 5 and the corresponding DLS curve under the same near physiological condition (100mM NaCl at pH 7.0). The EM image in panel a) shows an aggregation and few larger size particles. The dynamic light scattering curve of this peptide in panel b) highlights a mixture of aggregates and larger particles of about 52nm in diameter.

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S4 Panel a) shows the processed electron microscopy image using ImageJ, and a size distribution histogram of peptide 5b under physiological conditions is shown in panel b). The preparation of the histogram was done according to Schneider, C. A. et al (2012), Nature methods 9(7): 671675, PMID 22930834)

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Initial models of 7 peptide constructs. Parent and peptides 1 to 6 have been built by in silico mutation on the starting model (parent). Mutated residues are highlighted in red, while the rest is shown in green color. Initial models of the other six constructs, peptides 1a to 6a, are exactly identical with the corresponding peptides 1 to 6 but without N-terminal protonation. 1057x793mm (72 x 72 DPI)

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Intermediate stages during the entire simulation process. (a) solvation, (b) minimization, (c) heating, and (d) equilibration. Figure 2 1057x793mm (72 x 72 DPI)

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Computational models of nanoparticle peptide constructs after MD simulation. Peptide constructs shown in magenta color after 2ns of molecular dynamics simulation, superposed on their corresponding initial peptides (green colors) . Figure 3 1057x793mm (72 x 72 DPI)

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Computational models of nanoparticle peptide constructs after MD simulation. Peptide constructs shown in magenta color after 2ns of molecular dynamics simulation, superposed on their corresponding initial peptides (green colors) . Figure 3a 1057x793mm (72 x 72 DPI)

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Molecular dynamics simulation of 13 peptides for 2ns. RMS deviations (a) and radius of gyrations (b) of three good constructs (peptides 2, 3, and 5 in addition to the parent peptide) relative to their corresponding energy minimized structures after 2ns MD simulation. RMS deviations (c) and radius of gyrations (d) of nine bad constructs (peptides 1, 4, 6, 7, 2a, 3a, 4a, 5a, and 6a) relative to their corresponding energy minimized structures after 2ns MD simulation. Colors of peptides in Figures b & d are in correspond with those depicted in Figures a & c respectively. Figure 4 1057x793mm (72 x 72 DPI)

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Molecular dynamics simulation of three best peptides 2, 3, and 5 for 10ns. RMS deviations (a) and radius of gyrations (b) of the four peptides relative to their corresponding energy minimized structures for 10ns MD simulation. Cartoon diagram of peptide 2 (c) in red color and peptide 5 (d) in light blue color after 10ns MD simulation. Comparison between unmodified peptide 5 and modified peptide 5b in regard to the variation of RMS deviation (e) and radius of gyration (f) during 10ns MD simulation. Figure 5 1057x793mm (72 x 72 DPI)

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Molecular dynamics simulation of three best peptides 2, 3, and 5 for 10ns. RMS deviations (a) and radius of gyrations (b) of the four peptides relative to their corresponding energy minimized structures for 10ns MD simulation. Cartoon diagram of peptide 2 (c) in red color and peptide 5 (d) in light blue color after 10ns MD simulation. Comparison between unmodified peptide 5 and modified peptide 5b in regard to the variation of RMS deviation (e) and radius of gyration (f) during 10ns MD simulation. Figure 5a 1057x793mm (72 x 72 DPI)

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Biophysical studies of peptide 5b. (a) Transmission electron micrograph for peptide 5b, Particle sizes are shown relative to 100 nm scale bar. (b) Dynamic light scattering curve for peptide 5b showing monodispersity in solution. Here volumic percentage has been plotted against the size of the particle in nm. (c) SAXS data for peptide solution with Guinier plot in the inset, the R2 for the fitting of Guinier plot is 0.8926. Figure 6 1057x793mm (72 x 72 DPI)

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TOC graphics Toc Graphic 352x264mm (72 x 72 DPI)

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