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The Role of Hydrophobic/Aromatic Residues on the Stability of Double-Wall #-Sheet Structures Formed by a Triblock Peptide Beytullah Ozgur, and Mehmet Sayar J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.7b00650 • Publication Date (Web): 11 Apr 2017 Downloaded from http://pubs.acs.org on April 15, 2017

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The Journal of Physical Chemistry

The Role of Hydrophobic/Aromatic Residues on the Stability of Double-Wall β-Sheet Structures Formed by a Triblock Peptide Beytullah Ozgur∗,† and Mehmet Sayar†,‡ †College of Engineering, Koc University, Istanbul, Turkey ‡Chemical & Biological Engineering and Mechanical Engineering Departments, Koc University, Istanbul, Turkey E-mail: [email protected]

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Abstract Bioinspired self assembling peptides serve as powerful building blocks in the manufacturing of nanomaterials with tailored features. Due to their ease of synthesis, biocompatibility and tunable activity this emerging branch of biomolecules has become very popular. The triblock peptide architecture designed by the Hartgerink group is a versatile system that allows control over its assembly and has been shown to demonstrate tunable bioactivity. Three main forces, Coulomb repulsion, hydrogen bonding and hydrophobicity act together to guide the triblock peptides’ assembly into one dimensional objects and hydrogels. It was shown previously that both the nanofiber morphology (e.g. inter-sheet spacing, formation of antiparallel/parallel β-sheets) and hydrogel rheology strictly depend on the choice of the core residue where the triblock peptide fibers with aromatic cores in general form shorter fibers and yield poor hydrogels with respect to the ones with aliphatic cores. However, an elaborate understanding of the molecular reasons behind these changes remained unclear. In this study, by using carefully designed computer based free energy calculations, we analyzed the influence of the core residue on the formation of double-wall fibers and single-wall βsheets. Our results demonstrate that the aromatic substitution impairs the fiber cores and this impairment is mainly associated with a reduced hydrophobic character of the aromatic side chains. Such weakening is most obvious in tryptophan containing peptides where the fiber core absorbs a significant amount of water. We also show that the ability of tyrosine to form side chain hydrogen bonds plays an indispensable role in the fiber stability. As opposed to the impairment of the fiber cores, single-wall β-sheets with aromatic faces become more stable compared to the ones with aliphatic faces suggesting that the choice of the core residue can also affect the underlying assembly mechanism. We also provide an in-depth comparison of competing structures (zero-dimensional aggregates, short and long fibers) in the triblock peptides’ assembly and show that by adjusting the length of the terminal blocks, the fiber growth can be turned on or off while keeping the nanofiber morphology intact.

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Introduction Exploiting self assembling peptides for manufacturing of bioinspired nanomaterials is an emerging discipline owing to their widespread use in several fields such as materials science 1 and healthcare. 2–4 This class of biomolecules utilize a large spectrum of amino acids, both natural and synthetic, for guiding peptide assembly. Depending on the peptide sequence and molecular architecture, a plethora of nanostructures, e.g. micelles, 5 monolayers, 6,7 nanovesicles 8 and even networks of such nanostructures 9–11 are available. Thus, finding a suitable peptide sequence for the fabrication of nanostructures with the desired properties is a challenging task. To ease the burden, many research groups use structural motifs e.g. peptide amphiphiles, 12–14 β-sheet forming peptide amphiphiles, 15 coiled coil 16 and collagen triple helix 17,18 domains. A recent methodology developed by Ulijn and coworkers 19 is noteworthy as it utilizes enzymatic rearrangement of peptide sequence to create a dynamic combinatorial peptide library, where thermodynamic stabilization by self-assembly process gives rise to selective amplification of self assembling candidates. Along with its functionality in the fabrication of supramolecular assemblies, peptide/protein assembly is also thought to play important roles in the etiology of neurodegenerative disorders, e.g. Alzheimer’s, Huntington’s and Parkinson’s diseases. 20,21 Therefore, an in-depth understanding of the molecular factors and forces guiding peptide assembly is of particular importance. However, establishing an elaborate understanding of the relevant forces is challenging both due to the complex nature of protein/peptide aggregation in living organisms and the state-of-the-art experimental techniques. Compared to their biological counterparts, rather simple structure and tunable assembly behavior of synthetic peptides make them better equipped to face those challenges. The triblock peptide Kn (QX)m Kn (Figure 1), designed by the Hartgerink group, 22,23 is a versatile system that forms one-dimensional aggregates. The sequence of triblock peptide accommodates short repeats (n) of positively charged lysines on both N- and C-terminus whereas a longer amphiphilic segment is located at the center. This central block is com3



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A previous examination of triblock peptide fibers with aromatic cores 27 has shown that the microscopic and macroscopic features of fibers, as well as hydrogels strictly depend on the type of the hydrophobic/aromatic side chain. More specifically, the atomistic properties such as β-sheet registry and the fiber thickness, as well as macroscopic ones such as the fiber length and the hydrogel quality depend on the choice of the core residue. The most important finding of Bakota et. al. 27 is that the triblock peptides with aromatic amino acids (phenylalanine, tyrosine or tryptophan) in general form shorter fibers and poor hydrogels compared to the ones with aliphatic amino acids (leucine). Considering that the basic nanofibrous structure is retained for all cases, the different nanofiber morphologies (e.g. antiparallel/parallel hydrogen-bond orientation, inter-sheet spacing) alone cannot account for these findings. Apart from the π − π stacking observed in phenylalanine and tyrosine containing peptides, 27 aromatic substitution of the core residue mainly reduces the hydrophobic character of the fiber core. 28,29 A previous study 30 examining the importance of these two phenomena, hydrophobicity and aromaticity, on the assembly of an amphiphilic peptide demonstrated that aromatic interactions are not essential for peptide assembly. The same study concluded that the nucleation and elongation rates can be enhanced by increasing the peptide hydrophobicity. In the same spirit, here we examine the role of the hydrophobic/aromatic side chains on the assembly of triblock peptides via computer based free energy calculations. In a recent study, 31 by using coarse grained (CG) molecular dynamics (MD) simulations, we have shown that the triblock peptides first assembles into β-sheets and depending on the hydrophobic strength of the core residue, existing β-sheets either form double-wall fibers by burying their hydrophobic side chains in the middle or merge to form longer β-sheets. In this paper by using four different residue types that form the core (leucine, phenylalanine, tryptophan and tyrosine), we first calculated the relative free energies of forming double-wall fibers through carefully designed umbrella sampling simulations. Our findings demonstrate that the chemistry of the core forming side chains, (e.g. hydrogen bonding capacity, presence of

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polar groups) remarkably influence the strength of the core. Such features also determine if the fiber core is wet or completely dry. In the following parts, we discuss the implications of these findings on the nanofiber morphology and assembly mechanisms. The final part of this study is dedicated to understanding the molecular details of an alternative packing structure which was observed in our CG MD study 31 that gives rise to zero dimensional aggregates and we discuss its implications on the self-assembly of the triblock peptide.

Methods Five different molecules based on the triblock architecture were used in the current study for the calculations. Four of these are based on the optimal triblock architecture, K2 (QX)6 K2 , where X can be one of the amino acids leucine (L), phenyalanine (F), tyrosine (Y) or tryptophan (W). The fifth molecule utilizes an alternating sequence of leucine and phenyalanine residues in the core region (K2 (QF QL)3 K2 ). Instead of giving the full sequence, in the remainder of this paper we refer to each sequence by the repeating unit of the central segment, e.g. QL for K2 (QL)6 K2 . The preformed fibers, composed of sixteen peptides (eight on each wall) were used to test the relative stability of the triblock fibers. The box was set up with the fiber axis extending along the z direction (Fig. 2). In order to mimic an infinite fiber, the z dimension of the box was initially adjusted (and later equilibrated by pressure coupling) such that the molecules closest to the bottom of the box are within hydrogen bonding distance with the periodic images of the molecules at the top of the box. MD simulations on the preformed fibers were carried out using GROMOS53a6 32 and CHARMM36 33 force fields. GROMOS53a6 simulations were performed by using GROMACS 4.5.6. 34 Water was represented by the SPC-E 35 water model. The choice of SPC-E water model (even though the recommended one is SPC for GROMOS force fields) depends on the systematic study of Hess and van der Vegt, 36 which demonstrated that SPC-E performs best in reproducing the hydration properties of amino acid side chain analogues. Nonbonded 7



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interactions were calculated by the twin range cutoff approach with a value of 1 nm for neighbor list (rlist) and 1.4 nm cutoff distance for VdW interactions (rvdw). Long range dispersion corrections were applied for both energy and pressure. Coulomb interactions were calculated with particle mesh Ewald 37 (PME) method with a Coulomb real space cutoff distance of 1 nm (rcoulomb) and a Fourier grid spacing of 0.12 nm. The neighbor list was updated every ten steps. All-bonds were constrained throughout the simulation using the LINCS algorithm, 38 which enables a time step of 2 fs. The temperature was kept at 298 K by using the Berendsen thermostat with the time coupling constant tau t = 0.1 ps. Semiisotropic pressure coupling was used to maintain the pressure at 1 bar in the x-y plane and 0 bar along the z-direction (fiber axis) using the Berendsen barostat 39 (tau p = 1. ps and compressibility=4.5x10−5 in both x-y and z directions). CHARMM36 simulations were performed with GROMACS 5.1.4. 40 Water was represented by the TIP3P water model. 41 Verlet algorithm 42 was used as the cutoff-scheme. The cutoff for both neighbor lists (rlist) and VdW interactions (rvdw) was set equal to 1.2 nm with force switching to zero between 1.0 (rvdw − switch) and 1.2 nm. Long range dispersion correction was turned off. Coulomb interactions were calculated with PME with a Coulomb real space cutoff distance of 1.2 nm and a Fourier grid spacing of 0.1 nm. The neighbor list was updated every ten steps. The bonds that contain H atoms were constrained throughout the simulation using the LINCS algorithm. Velocity rescaling algorithm was adopted for temperature coupling with T = 298 K and tau t = 0.1 ps. For pressure coupling, ParinelloRahman algorithm with a time-constant of tau p = 2.5 ps was used. For both GROMOS53a6 and CHARMM36 simulations, equal number of CL ions were added to the simulation box to neutralize the net charge. Prior to the MD simulations, two consecutive 500 ps long equilibration simulations were conducted by using an NVT ensemble for GROMOS53a6 simulations. In the first equilibration simulation, the whole protein was restrained. In the second simulation only the CA atoms of the protein were restrained. For CHARMM36 simulations, only a single simulation was performed for equilibration, where

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the water molecules were restrained for 1 ns, relaxing the protein structure. The data for all the analysis was collected from 150 ns long trajectories for both force fields. In order to calculate the free energy cost of disassembling the fiber, two separate umbrella simulations were performed for each molecule. Simulations were performed with the GROMOS53A6 force field and SPC-E water model. The temperature was maintained at 298 K with the Velocity rescaling algorithm. 43 All other simulation parameters were kept identical to the standard MD simulations with GROMOS53A6 as described above. The first umbrella simulation was set up to calculate the free energy cost of exposing the hydrophobic/aromatic faces of the walls of the fiber to water. A fiber consisting of twenty four molecules (twelve in each wall) was set up with the fiber axis extending along the z-direction of the box. The separation of the walls was achieved by peeling the walls apart. To this aim the pull and reference groups are chosen as the Cα atoms of the last glutamine and hydrophobic/aromatic residues (on the right side of the fiber in Figure 6) of all molecules that form a wall. The reaction coordinate was defined as the distance in the x-y plane between the pull and reference groups. In our initial trials where the pull and reference groups were chosen as the center of mass of the first and second walls’ backbone atoms, we observed major sampling problems associated with the large forces involved. The resulting potential of mean force curves exhibited significant signs of hysteresis. The peeling mechanism, described above, does not suffer from such simulation artifacts. In order to generate the initial structures for the umbrella windows, a continuous pulling simulation was performed with a pull rate of 5 nm/ns and a spring constant of 1000 kJ/(mol× nm2 ). The pull force was applied in the x-y plane only. For each sequence the following number of umbrella windows were used to cover the entire reaction coordinate: 37 for QF, 43 for QL and QY, 41 for QW. For data collection a spring constant of 1000 kJ/(mol nm2 ) was adopted to restrain the distance between the pull and reference groups at the initial distance for any given window.

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In rare cases this value was increased up to 5000 kJ/(mol × nm2 ) to ensure sampling for a specific region of the reaction coordinate. Each umbrella window was simulated for at least 5 ns. Next, using the g wham 44 routine of GROMACS the potential of mean force curves were obtained. The PMF curves were shifted such that they go to zero when the hydrophobic/aromatic faces of two β-sheets interact no more. The second umbrella simulation was setup to calculate the free energy cost of breaking the backbone hydrogen bonds in a single wall. To this aim, a single wall composed of 6 molecules that form a β-sheet was constructed. For QL, QFQL, and QF antiparallel β-sheet arrangement, whereas for QW and QY parallel β-sheet arrangement was used, in line with the experimental evidence. 27 In order to focus only on the hydrogen bonding contributions, lysine residues on both ends were cleaved and the remaining amphiphilic core (QX)6 was capped with ACE and N H2 . The pull and reference groups were chosen as the CA atoms of the last glutamine and hydrophobic/aromatic residues of the third and fourth molecules in the β-sheet. As depicted in Fig. 9a with the red beads both pull and reference groups reside on the same side of the molecule. The reaction coordinate is chosen as the Euclidean distance between the pull and reference groups. As the reaction coordinate increases with the applied force, the hydrogen bonds connecting the third and fourth molecules are broken consecutively. Similar to the umbrella simulations performed for peeling the two walls, for this umbrella simulation we also tried using the distance between the center of mass of the third and fourth molecules as the reaction coordinate. However, for this case also, such a reaction coordinate resulted in significant sampling problems for the PMF calculation. Breaking all of the hydrogen bonds requires a simulation box so large that it is computationally not feasible. Hence, we limited the umbrella simulations to cover a range of the reaction coordinate that will result in breaking of exactly half of the hydrogen bonds between the third and fourth residues. Analogues to the first umbrella sampling simulation, a constant rate pulling simulation was performed to generate the initial structures for each

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umbrella window. For each sequence, at least twenty four umbrella windows were used to cover the entire range of the reaction coordinate and each umbrella window was simulated for at least 10 ns. Since the single wall β-sheet is not periodic, the umbrella simulations were performed with isotropic pressure coupling. All other simulation parameters were identical to the first umbrella sampling simulations described above. For both umbrella simulations the resulting histograms and error analysis are provided in Supporting Information Section I and II. The solvent accessible surface area (SASA) of the core forming residues of a triblock peptide was calculated in its monomeric form, within a single wall β-sheet and finally within a fiber. Windows from the umbrella simulations for the peeling of the wall were used for the calculations. Calculations were performed with the g sas tool of Gromacs with a probe size of 0.14 nm. In all three cases the surface and output groups for g sas tool are chosen as the triblock molecule(s) and the side chains of the core forming residues (any of L, F, W or Y), respectively. An umbrella window close to the PMF minimum was chosen for the SASA calculations within a fiber and also for the monomeric form. For the monomer calculation the surface and output groups were restricted to a randomly chosen molecule from the fiber. Finally, for the SASA calculation within a single wall an umbrella window was chosen such that the two walls were completely separated and hydrophobic/aromatic faces were fully exposed to water. For the single wall and fiber calculations obtained SASA values are divided by the total number of molecules to obtain per monomer SASA values. In order to compare the cross packed structure against the regular packing, two additional simulations (50 ns long) were performed with a sixteen molecule aggregate. In the first simulation, the cross packed structure was formed by rotating the two β-sheets forming the fiber 90◦ with respect to each other, while their hydrophobic/aromatic faces are still in contact. In the second simulation a finite length fiber of sixteen molecules, where the two ends of the fiber were exposed to water were created. The SASA of hydrophobic/aromatic side chains were calculated analogous to the method described above. In order to calculate

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the Coulomb repulsion between the lysine side chains, water was removed from the simulation box, dielectric constant was set to 80 and PME was replaced with the simple cutoff method (with a cutoff distance of 1 nm). Using these new parameters, the previously obtained trajectory was analyzed by the rerun option of mdrun tool in Gromacs to recalculate the energies of all frames in the trajectory with the simple cutoff for Coulomb interactions. Note that these calculations are merely used for comparing the distribution of the charged lysine side chains in the respective cases only. These calculations are not suitable for a direct comparison of the energetic contributions. Molecular graphics were produced with VMD, 45 and plots were produced with the Gnuplot 5.0 package (http://gnuplot.info).

Results and Discussion Coulomb repulsion, hydrogen bonding and sequence hydrophobicity are the three main factors that guide the assembly of triblock peptides. Systematic studies on triblock peptides demonstrate that the fiber formation strongly depend on the balance between these forces which can be controlled by adjusting the relative lengths of the central and terminal blocks. 22 Another important factor guiding the nanofiber morphology is the type of the core residue. 27 While the influence of relative block lengths is easier to anticipate and well documented, 22 the molecular reasons that leads to the changes in nanofiber morphology upon substituting the core residue from aliphatic to aromatic character is not well understood. In terms of the relevant forces guiding the triblock peptide assembly, the choice of the core residue mainly affects the sequence hydrophobicity and aromaticity. As noted earlier, commonly referred hydrophobicity scales indicate a lower hydrophobic character for aromatic side chains. Since the assembly of triblock peptides depend on a subtle balance between the competing forces, it is plausible that a reduced hydrophobic character will have adverse effects on the assembly of triblock peptides. A comprehensive inspection of triblock peptides’ self-assembly from a random initial 12


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state is computationally not feasible with an all atom representation. Instead, here, we first focus on the behavior of preformed fibers in an aqueous medium and examine their stability and structural features by using two commonly used force fields: GROMOS53a6 and CHARMM36. GROMOS53a6 was also used in our earlier study to analyze intra- and inter-sheet spacings, as well as residue-specific β-sheet orientations. 27 Hence, we will rely on these calculations mainly. Simulations with the CHARMM36 force field are mainly used to verify and check any force field dependency. Next, in order to understand the role of the hydrophobic/aromatic core residue on the assembly of the fiber, we perform two separate umbrella simulations with GROMOS53a6 force field. In the first simulation, we disassemble a double-wall fiber into single-wall β-sheets by gradually exposing its hydrophobic/aromatic core. Next, we break apart a single-wall βsheet, to determine the relation between the hydrophobic/aromatic core and the backbone hydrogen bonding. Finally, we analyze an alternative packing arrangement, which we refer to as cross-packed. MD simulations on preformed fibers In order to analyze the packing of the hydrophobic/aromatic residues inside the fiber core we performed 150 ns long MD simulations with both GROMOS53a6 and CHARMM36 force fields on a preformed fiber composed of sixteen peptides (eight in each β-sheet). The fiber is oriented along the z-direction of the box (Figure 3) and periodic boundary conditions are used to mimic an infinite fiber. Prior to the MD simulation all water molecules inside the fiber core were removed. Irrespective of the type of the core residue, the preformed fibers remain stable throughout the simulation with both force fields. The equilibration of the MD simulations were checked by monitoring the inter-wall spacing (Table 1 and Supporting Information Section III for the timeline analysis). The packing of the hydrophobic/aromatic residues inside the fiber core are shown with the snapshots in Figure 3. The QL fibers display the highest degree of

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packing among the five cases considered. With the relatively small size of the leucine side chains, the two walls interdigitate to yield a wall separation distance of 1.15 nm (peptide backbone distances between the walls) and the alternating arrangement of the leucines from opposite walls as shown in Figure 3. Among the remaining molecules QY also displays a strong degree of packing as well, whereas QF, QFQL and QW display increasing degrees of disorder. The wall separation distance for QFQL is slightly larger than QF, which suggests that the presence of leucines disrupt the packing of phenylalanine side chains. The difference between QF and QY is also interesting, since the only difference in their side chain is an additional -OH group for QY. QW, with its two aromatic rings, yields the largest inter-wall spacing. Table 1: Average inter-wall distances for the triblock fibers in GROMOS53a6 and CHARMM36 simulations. The average distance in the x-y plane between the backbone atoms (excluding lysine residues) of the two walls are used for the calculation. distance (nm) GROMOS53a6 CHARMM36

QL 1.15 1.12

QFQL 1.27 1.27

QF 1.25 1.22

QW 1.59 1.57

QY 1.40 1.37

In order to quantify the packing order within the core for aromatic side chain containing peptides, we also calculated the radial distribution function (RDF) for QF, QY and QW fibers. The RDF curves for GROMOS53a6 are shown in Figure 4, whereas CHARMM36 results are provided in Supporting Information Section IV. The first peak in RDF curves for all three molecules is located around 0.5 nm. This distance is relatively large compared to the typical π − π interaction distances. 46,47 The RDF curves for aromatic rings confirm our visual observation suggesting that QY fibers have a long range order. QF fibers do also display weak long range peaks, but for the case of QW no long range order is seen. The RDF curves can be decomposed into intra- and inter-wall contributions, which are provided in Supporting Information Section IV. The decomposition suggests that for QF both intraand inter-wall aromatic interactions contribute to the first peak. On the other hand for 15



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QY, the first peak is dominantly determined by intra-wall aromatic interactions. Whereas the inter-wall aromatic interactions for QY produce a shifted secondary peak, which is only visible as a shoulder in the combined RDF. Considering that the only difference between the phenylalanine and tyrosine side chains is the extra -OH group in the latter, this difference, which also leads to a larger inter-wall spacing (1.40 nm for QY compared to 1.25 nm for QF), is rather surprising. A close inspection of the fiber core for QY reveals the source of the discrepancy (Figure 4b and c). The -OH groups of tyrosine side chains from opposite walls stack up to form a chain of dipoles with head-to-tail orientation. Due to this strong dipolar interaction, the aromatic rings from opposite walls cannot interact, leaving only the intra-wall π − π interactions feasible. The absence of strong π − π interactions mainly stem from the geometric constraints imposed on the aromatic side chains by the fiber structure. The spacing between the molecules along the fiber axis is determined by the backbone hydrogen bonding distance (0.48 nm 27 ). On the other hand, along the β-strand axis (x-axis in Figure 2) the alternating sequence of QX repeats impose a distance constraint (the distance between two Cα atoms of consecutive hydrophobic/aromatic residues is 0.63 nm), which leaves only the inter-wall distance as a free parameter. In order to have strong π − π interactions, the aromatic side chains from opposite walls have to interdigitate. Such an interdigitation is only observed partially for QF, as seen in the RDF curves decomposition. For QY, as discussed above, the -OH dipoles interaction prevents interdigitation. Finally, for QW the size of the aromatic side chains is simply too large for such an interdigitation to be observed. A close up inspection of the fibers reveal another interesting feature of the QW fibers: a large amount of water can penetrate inside the fiber core as seen in Figure 3. In order to quantify the water inside the fiber cores, we counted the water molecules that are within 0.4 nm of the side chains of the core residues. The number of water molecules as a function of the simulation time for each sequence is shown in Figure 5. The choice for the cutoff distance (0.4 nm) is based on the RDF between the hydrophobic/aromatic side chains and

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a) GROMOS53a6 # of Water Molecules

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QL QFQL

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Figure 5: Water diffusion into the hydrophobic core of triblock peptide fibers. Oxygen atoms of water molecules within 0.4 nm of hydrophobic side chains (only heavy atoms considered) are counted. The calculations are normalized to yield per dimer results.

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water molecules and is chosen to include the first hydration shell of respective side chains (see Supporting Information Section V). Regardless of the force field used, QW fibers display a significant amount of water uptake during the 150 ns long simulations. In order to demonstrate the unique behavior of QW, we also analyzed the distribution of the water molecules with respect to the side chain position (see Supporting Information, Section VI). This residue specific analysis demonstrates the diffusion of water molecules deep inside the core of tryptophan containing fibers for both CHARMM36 and GROMOS53a6 simulations. Water uptake by QW stems from two main reasons. Among the five molecules considered, tryptophan is typically ranked as the least hydrophobic residue. This reduced hydrophobic character lowers the penalty for the water molecules to get trapped inside the core. In addition, as demonstrated earlier, the highly disordered structure inside the core and the very limited interaction between the two walls for tryptophan containing molecules also reduce the barriers against water penetration. Besides QW, QY can also absorb a few water molecules as seen in Figure 3e on the right hand side. However, the hydration of tyrosine is vastly different from QW. Instead of a lateral diffusion deep inside the fiber core, the absorbed water molecules tend to move along the fiber axis for QY. This is due to the presence of the hydrophilic channels inside the core region that form with the alignment of side chain -OH dipoles in a head to tail fashion as discussed earlier. On the contrary to QW and QY, for QL, QFQL and QF water molecules are seen only in the vicinity of the outer hydrophobic/core residues. The completely dehydrated nature of fiber cores in QL and QF resemble the case of Aβ16−22 protofibrils 48,49 in which the dehydration of inter-sheet region induces a hydrophobic collapse of adjacent β-sheets. In summary, our findings reported in this section clearly indicate the wetting of the fiber cores for tryptophan containing peptides. Next, we ask whether the wetting of the hydrophobic/aromatic side chains weakens the fiber core or not. To this aim, we compute the strength of fiber cores for each of the four residue types. Since the fibers behave sim-

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ilar in CHARMM36 and GROMOS53a6 simulations, the remainder of molecular dynamics simulations will be conducted with GROMOS53a6 force field only. Relative strengths of fiber cores In order to understand the influence of the hydrophobic/aromatic residues on the relative strength of the fiber cores, we have calculated the free energy cost of exposing the hydrophobic cores completely to water. The free energy estimation was based on umbrella sampling simulations for peeling the two walls of the fiber apart, and using WHAM analysis to obtain the potential of mean force curves for fully hydrating the hydrophobic/aromatic faces of the walls. For the umbrella sampling simulations a preformed fiber composed of 24 molecules (12 on each wall) were used. In each wall the Cα atoms of the last glutamine and leucine residues (on the right side of the fiber in Figure 6) were chosen as the pull and reference groups for the umbrella sampling simulations. The reaction coordinate, r, was defined as the distance in the x-y plane between the pull and reference groups. QFQL case was not taken into account for this part, since in general its strength was already shown to be right in between QL and QF. 27 Further details of the umbrella sampling simulations and the WHAM analysis are provided in the methods section. As the peeling advances, hydrophobic/aromatic side chains become more exposed to water as depicted in Figure 6. For QL, QF and QY, the hydrophobic faces of individual β-sheets become completely exposed to water at r ≈ 6 nm. QW once again behaves differently: the contacts between the two walls of tryptophan containing fibers disappear much earlier (r ≈ 4 nm). The weakened strength of QW stems from the same reasons discussed earlier. The fiber core, due to its reduced hydrophobicity and disordered packing with large cavities, cannot resist to water penetration. Furthermore, the lack of any significant interdigitation between the two walls, also reduces the strength of the QW fibers against the peeling deformation. During the peeling, for all sequences, both walls remain intact, i.e. backbone hydrogen

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Table 2: Free energies (kcal/mol) of transfer from dilute cyclohexane (cyc) to dilute water (wat) 28 (first column) versus our estimated energies based on the PMF calculations (second column) per side chain. Side chain Leucine Phenylalanine Tryptophan Tyrosine

cyc → − wat 4.92 2.98 2.33 -0.14

PMF estimate 2.49 1.99 0.7 1.89

due to the neighboring side chains. Based on the depth of the PMF curves presented in Figure 7, the free energy change per side chain upon core formation is given in Table 2. The experimental and estimated values are comparable for leucine and phenylalanine side chains. However, for both tryptophan and tyrosine our results differ significantly. For tryptophan, the most plausible explanation is that multiple interrelated factors such as the poor packing of tryptophan side chains and the wetting of inter-sheet region weaken its hydrophobic nature. The case of tyrosine is more intriguing as the experimental findings provided in Table 2 suggest that the tyrosine side chain is slightly polar. This means that the core formation in QY is unfavorable if the dehydration of tyrosine side chains govern the underlying process alone. On the other hand, the depth of the PMF curve for QY (Figure 7) suggests the opposite. The only difference between the phenylalanine and tyrosine side chains is an OH group attached to the phenyl ring in the latter one. Yet, this group has a dramatic influence on the fiber core as it allows QY to form side chain-side chain hydrogen bonds as depicted in Figure 4b and c. The side chain-side chain hydrogen bonding acts like a zipper, where alternating OH groups form a chain of hydrogen bonds along the fiber axis. Figure 8 shows the evolution of the number of side chain-side chain hydrogen bonds along the reaction coordinate (r) for QY. At r ≈ 6 nm, these hydrogen bonds are completely lost and at around the same distance the PMF curve of QY goes to zero which implies that the side chain-side chain hydrogen bonding is an important factor for the core strength. A greater stability of QY due to side chain hydrogen bonding resembles the case of Sup35 fragments 50 implying that molecular factors guiding the core formation is different for tyrosine containing 23



8 # of hydrogen bonds

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6 4 2 0

1

2

3

4 r (nm)

5

6

7

Figure 8: The average number of inter-wall side chain-side chain hydrogen bonds (per dimer) in QY (per dimer) as a function of the reaction coordinate. peptides. In order to further understand the benefit of burying hydrophobic/aromatic side chains in a fiber core, we calculated the solvent accessible side chain area (SASA) for a single peptide in extended β-sheet conformation in bulk water, within a β-sheet and within a fiber (Table 3). Surprisingly, the monomeric triblock peptide can decrease its SASA by approximately 60% when it resides inside a β-sheet. The pairing of single-wall β-sheets to form fibers decreases the amount of solvent exposed area below 10, 13 and 17% for leucine, phenylalanine and tyrosine side chains, respectively. The minimum gain upon fiber formation is measured for QW (22% of tryptophan side chains surface area is still exposed to water). Table 3: Solvent exposed side chain area (nm2 , per monomer) determined in the presence and absence of the fiber core. Side chain Leucine Phenylalanine Tryptophan Tyrosine

monomer 6.66 7.81 9.07 7.71

β-sheet 2.72 (40.8%) 3.14 (40.2%) 3.42 (37.7%) 3.27 (42.4%)

fiber 0.51 (7.7%) 1.01 (12.9%) 1.97 (21.7%) 1.32 (17.1%)

Notably, a significant portion of the SASA in fibers comes from the outer boundaries of the core. However, for QY and QW, there is also an inter-sheet component of SASA calculations. For QY, this corresponds to the regular channels inside the core which are formed due to the side chain hydrogen bonds. On the other hand, the exposed inter-sheet

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region is irregular in QW and it seems half of the core can be wetted. Relative strengths of β-sheets a) r=0.54

r=1.00

r=2.00

b)

PMF (kJ/mol)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


120

r=1.50

r=2.50

QL QF QFQL QY QW

100 80 60 40 20 0 0

0.5

1

1.5

2

2.5

r (nm)

Figure 9: a) Snapshots for sample set of reaction coordinates, r, from umbrella sampling simulations for the breaking apart of the β-sheet. Backbone hydrogen bonds between the third and the fourth peptides are broken as the distance between the pull and reference groups (depicted with the red beads on the right) increases. (b) PMF curves for all five systems for the corresponding umbrella sampling simulations. Our previous study 31 examining the peptide assembly demonstrates that, unless the core residue has a strong hydrophobic character, the propensity of growing single-wall β-sheets overwhelms the propensity of pairing existing β-sheets into a double-wall structure. Also, as noted earlier, single-wall β-sheets provide a significant shielding for hydrophobic/aromatic side chains. Therefore, depending on the choice of the core residue single-wall β-sheets can be an alternative to the double-wall fibers throughout the triblock peptides’ assembly. Due to such reasons, single-wall β-sheets require further attention. In order to examine the stability of single-wall β-sheets and determine the influence of hydrophobic/aromatic side chains, we calculated the potential of mean force for breaking apart a β-sheet. The β-sheet structure is composed of six triblock peptides. To reduce 25



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the box size and eliminate the influence of Coulomb interactions, the lysine blocks on both ends of the peptides are cleaved. Prior to free energy calculations, we tested the stability of this preformed β-sheet through 100 ns-long molecular dynamics simulations. Irrespective of the hydrophobic/aromatic residue type, the preformed β-sheet remains stable throughout the simulation time. To separate the respective partners, we setup the reaction coordinate as depicted in Figure 9a. The pull and reference groups reside on one side of the β-sheet (as depicted through red beads) and the hydrogen bonds connecting the third and fourth peptides are broken sequentially as the distance between the respective beads increases. Figure 9b shows the PMF curves for each peptide sequence calculated at the end of the umbrella simulations. Due to the computational limitations, the simulations are performed until half of the hydrogen bonds between the third and fourth peptides are broken while the other half remains intact. The positions of the energy minimums of QY and QW and of QL, QFQL and QF overlap at r ≈ 0.49 nm and at r ≈ 0.55 nm, respectively. The shift observed for the latter three is a result of antiparallel β-sheets favored by leucine and phenylalanine containing peptides. At r ≈ 2.5 nm the number of hydrogen bonds between the third and fourth peptides are halved in all five constructs. Since we halve the number of hydrogen bonds instead of completely removing them, we use the PMF values calculated exactly at r = 2.5 nm to obtain the relative energies of each system. Based on this scheme, the depth of PMF curves demonstrate that the tyrosine containing peptides form the most stable single-wall β-sheets (≈ 125 kJ/mol). This finding is consistent with the β-sheet forming propensities of these four amino acids where the ordering of respective propensities was found to be as follows: Y > F > W > L. 51 As the difference between QF (≈ 95kJ/mol) and QY demonstrates, the OH group attached to the phenyl ring in tyrosine makes a significant contribution to the overall stability of single-wall β-sheets. A close inspection of QY shows that a single tyrosine side chain can on average form 2.5 hydrogen bonds with water molecules. On the other hand, for tryptophan, which is also capable of forming hydrogen bonds with water, this value is 0.5. This difference between tryptophan

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and tyrosine is due to two reasons. First, the OH group in tyrosine acts both as an acceptor and donor, whereas the tryptophan side chain contains only an acceptor (N). Second, due to the positioning of acceptor at inner ring in tryptophan, its interaction with the surrounding water molecules is restricted. A smaller number of hydrogen bonds between the tryptophan side chains and water can explain the lower stability of QW. On the other hand, introducing more hydrophobic leucine side chain in the peptide sequence decreases the stability of single-wall β-sheets. Visual inspection of QL and QFQL reveal some interesting behaviors in terms of breaking of backbone hydrogen bonds. As depicted in Figure 10, the initial number of backbone hydrogen bonds are around twelve for aromatic side chains and as r increases, the hydrogen bonds are broken one by one. On the other hand, after breaking a few of them in QL and QFQL, the linear relation between r and the number of backbone hydrogen bonds disappear. A close inspection of respective umbrella windows in QL and QFQL reveals that, in addition to the hydrogen bonds that are broken at one end of the triblock peptides due to the pulling, unexpectedly, the hydrogen bonds on the opposite end are broken as well. We also discovered that once a few hydrogen bonds are broken, the third and fourth peptides in QL and QFQL start to twist (around their peptide axis), exerting a perturbation on the opposite end. This is probably the reason behind large fluctuations in the hydrogen bonding profiles of QL and QLQF. We do not observe such a twisting for the fibers of aromatic molecules. Due to this unexpected behavior of leucine containing β-sheets, the resulting PMF curves are relatively weaker compared to the other three. The observed twisting could potentially be associated with the particular choice of the reaction coordinate. However, since we only observe the twisting in leucine containing peptides, we cannot provide a conclusive explanation to this phenomenon. MD simulations of Cross-packed vs. Regular-packed aggregates Our PMF calculations discussed so far demonstrate that both backbone hydrogen bonding and hydrophobic interactions, guiding the triblock peptides’ assembly to single-wall β-sheets

27


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Backbone-Backbone H-Bonds


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12 10 8 6 QL QFQL QF QW QY

4 2 0 0

0.5

1

1.5

2

2.5

r (nm)

Figure 10: The number of backbone-backbone hydrogen bonds formed in-between the third and fourth triblock peptides as a function of r, the reaction coordinate in Figure 9. X-axis shows the time-averaged r value, while y-axis shows the number of backbone hydrogen bonds (time-averaged) for each umbrella window. and double-wall fibers are influenced by the choice of the core residue. Considering that these two complement each other to compensate the Coulomb repulsion arising due to the terminal lysine side chains, subtle changes in the balance of these forces can affect the triblock peptide’s assembly dramatically. In addition to proper balancing of opposing forces, the aggregates of triblock peptide can reduce the Coulomb repulsion through structural rearrangements, e.g. orienting two β-sheets orthogonal to each other. Such a configuration, which we refer to as a cross packed structure was first seen in our CG-MD simulations 31 (see Figure 11a) and is feasible for short β-sheets (< 10 peptides in each β-sheet). Recent efforts on the triblock peptide family focus on their use as therapeutic agents. 24–26 The relatively small size and soluble nature of the cross packed structure could play an important role in enabling the diffusion of the triblock molecules through the membrane. In order to gain further insight, we analyzed the backbone hydrogen bonding, SASA and Coulomb energies for each peptide sequence (Figure 12). The details of the calculation for Coulomb energies is provided in the methods section, and these should be regarded as a comparison of the distribution of the lysine side chains, rather than an accurate estimation of the Coulomb energy. We studied three different fiber structures where each is composed of sixteen peptides

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hydrogen bonds

a) Hydrogen Bonding 18 QL 16 14 12 10 18 QY 16 14 12 10 10 20

SASA

QF

QW

30

40

cross finite

50

Time (ns)

b) SASA 6 5 4 3 2 1

QL

QF

6 5 4 3 2 1

QY

QW

10

20

30

40

50

Time (ns)

cross finite

infinite

infinite

c) Coulomb energies 45

QL

QF

QY

QW

35

Coulomb energy

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

25 15 45 35 25 15 10

20

30

40

50

Time (ns)

cross finite

infinite

Figure 12: Comparison of cross-packed and regular forms for QL, QF, QW and QY. The number of backbone hydrogen bonds (a), Solvent exposed hydrophobic area (b) and Coulomb repulsion (c) are plotted for each peptide sequence. The calculations are normalized to give per dimer data.

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(eight in each β-sheet). The black lines denote the results of the cross packed (referred to as ”cross”) fiber (see Figure 11a), whereas the cyan and purple lines represent the results for the regular packed form (referred to as a ”finite” or ”infinite” fiber, respectively). These two differ in terms of the box lengths. In ”infinite”, the box length along the z-direction is adjusted to match the fiber length so that fiber can interact with its periodic image along the fiber axis. In contrast, in ”finite” the fiber is not allowed to interact with its periodic images (cyan line). As depicted in Figure 12a, the number of backbone hydrogen bonds are slightly higher for ”infinite” due to the periodic treatment of fibers for all triblock molecules. The exposed area of the core residues is similar for finite fibers irrespective of the packing geometry as black and cyan lines indicate. In contrast, the SASA values experience a drop for infinite (purple colored line). This drop can also be attributed to the periodic treatment of fiber as the peptides residing at each end are no more exposed to water. Hence, the infinite fiber is clearly more favorable compared to cross-packed and finite fibers in terms of hydrogen bonds and SASA. However, the arrangement of lysine side chains in cross-packed structure creates an important difference in the Coulomb repulsion (Figure 11c). The lowest Coulomb repulsion is observed for cross packed fibers irrespective of the type of the core residue. Based on these findings, it is very plausible that the triblock peptide can promote the cross packed configuration throughout its aggregation. However due to its small size, observation of cross packed structure could be very challenging experimentally. In TEM analysis, along with the fiber forms small circular objects were observed, 22,23 however the internal structure of these aggregates is still unknown. Such zero-dimensional aggregates could also be transitionary structures that form during the assembly, which are transformed into fibers in latter stages. It is important to note that, both cross and regular packed configurations of the fibers remain stable throughout the 50 ns-long simulations. In order to observe a rapid transition from regular to cross packed configuration, we found that the number of lysines on both ends

31



a) initial

b) 40 ns

4.4

70

SASA Coulomb

4

65

3.6 60 3.2 55

2.8 2.4

Coulomb repulsion

c)

SASA

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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50 0

5

10

15

20

25

30

35

40

Time (ns)

Figure 13: Transition from the regular (a) to cross-packed (b) arrangement for K4 (QL)6 K4 . The SASA and short range Coulomb energy as a function of the simulation time (c).

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should at least be doubled (in contrast to two lysines on each end) as depicted in Figure 13 for K4 (QL)6 K4 . The preformed finite fiber is composed of ten peptides (five on each β-sheet) and initially it is in regular packed configuration. However, the Coulomb repulsion in this configuration is unbearable and within 20 ns the fiber undergoes a transition from regular to cross packed configuration. Both SASA of leucine side chains (black line) and Coulomb repulsion arising due to lysine side chains (cyan line) become reduced in the cross packed structure. The high SASA values observed in regular packed configuration is due to the opening of fibers in each end in an attempt to reduce the Coulomb repulsion, which exposes the leucine side chains more. Such behavior disappears when the fiber adopts a cross packed structure.

Conclusion In this study, we performed an in-depth analysis of the molecular forces that govern the formation and stability of the β-sheets and fibers via free energy calculations. It was shown before that the choice of the core residue has profound effects on the nanofiber morphology e.g. fiber length, thickness and the registry of triblock peptides in β-sheets. 27 Here, we demonstrate that although the triblock peptide architecture can tolerate a variety of residues in its core, the energetics behind the fiber formation strictly depend on the type of the core residue. Among the four residue types chosen as the core residue, pheylalanine, tyrosine and tryptophan share an aromatic character. The fact that the aromatic residues have a high frequency in amyloid forming peptides/proteins constitutes an important motive to examine their role in protein aggregation. Nevertheless, whether the π − π interactions or generic hydrophobic considerations are of particular importance in peptide assembly is an ongoing debate. 15,30,52–56 A detailed analysis of residue specific packing arrangements in triblock fibers reveal that the geometric restraints imposed by the fiber structure prevent the aromatic side chains from establishing strong π − π interactions. QW suffers most from the lack of such interactions as implied by its highly disordered and relatively weak fiber core. Based on the 33



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potential of mean force calculations of hydrating the hydrophobic/aromatic side chains of preformed triblock fibers, we show that nonaromatic leucine residues which has a stronger hydrophobic character make the fibers more stable compared to the aromatic ones. On the other hand, hydrophobicity alone can not be accounted for the energetic differences between the aromatic cores. We demonstrate that other factors such as the dehydration of fiber cores and side chain hydrogen bonding also influence the fiber stability. By breaking apart a β-sheet, we analyzed the influence of the hydrophobic/aromatic amino acids on single-wall β-sheet structure. The importance of this structure comes from our previous study 31 which shows the formation of long single wall β-sheets when the hydrophobic interactions are weak compared to the backbone hydrogen bonding. A similar conclusion was reached here as the depth of PMF curves demonstrate an inverse correlation between the hydrophobic character and the β-sheet stability. On the other hand, underlying differences can be explained by the β-sheet propensity of the core residue. 51 Finally, a quantitative analysis of cross packing against the regular one demonstrates that for shorter fibers an orthogonal orientation of two β-sheets is more feasible. We have also showed that the emergence of cross packed configuration can be facilitated by elongating the terminal lysine blocks. Such a configuration reduces the Coulomb repulsion while leaving other factors, e.g. backbone hydrogen bonding, hydrophobic interactions, unchanged. In contrast to lower Coulomb repulsion in shorter fibers, the cross-packed structures are less favorable for aqueous media due to higher exposure of hydrophobic/aromatic side chains at the fiber ends. In this regard, the relatively shorter fibers in tyrosine and tryptophan containing peptides 27 can be explained by the reduced penalty of the open ends of the fiber due to the lower hydrophobic nature of these residues. Owing to its elegant design, the triblock peptide architecture bears a great potential in manufacturing of tailored nanomaterials. As noted earlier, it is already in use for various purposes including cell penetration and antimicrobial activity. In this regard, a better understanding of the key elements guiding its assembly can pave the way for the development

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of novel peptide-based nanomaterials and also can provide a higher control over the triblock peptides’ assembly. Our computational findings presented here both complements the existing literature and provides a molecular level understanding about the role of the core residue.

Associated Content Supporting Information Available Umbrella histograms of free energy calculations with error estimates, timeline analysis of inter-sheet spacings, RDF of aromatic side chains and RDF of water molecules around hydrophobic/aromatic side chains and per residue water counts for GROMOS and CHARMM simulations.

Acknowledgments ¨ ITAK ˙ ¨ M. S. thanks TUB (grant no. 112T496) and TUBA Distinguished Young Scientist Award (2012 awardee) for financial support. We would like to thank Prof. Jeffrey Hartgerink for fruitful scientific discussions and Zeynep Abalı for a critical reading of our manuscript.

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