Article pubs.acs.org/Langmuir

Molecular Dynamics Simulations of Peptides at the Air−Water Interface: Influencing Factors on Peptide-Templated Mineralization Alok Jain,†,‡ Mara Jochum,† and Christine Peter*,†,‡ †

Max Planck Institute for Polymer Research, Ackermannweg 10, 55128 Mainz, Germany University of Konstanz, P.O. Box 718, 78547 Konstanz, Germany

‡

S Supporting Information *

ABSTRACT: Biomineralization is the intricate, biomedically highly relevant process by which living organisms deposit minerals on biological matrices to stiffen tissues and build skeletal structures and shells. Rapaport and coworkers (J. Am. Chem. Soc. 2000, 122, 12523; Adv. Funct. Mater. 2008, 18, 2889; Acta Biomater. 2012, 8, 2466) have designed a class of self-assembling amphiphilic peptides that are capable of forming hydrogels and attracting ions from the environment, generating structures akin to the extracellular matrix and promoting bone regeneration. The air−water interface serves both in experiment and in simulations as a model hydrophobic surface to mimic the cell’s organic−aqueous interface and to investigate the organization of the peptide matrix into ordered β-pleated monolayers and the subsequent onset of biomineral formation. To obtain insight into the underlying molecular mechanism, we have used molecular dynamics simulations to study the effect of peptide sequence on aggregate stability and ion−peptide interactions. We findin excellent agreement with experimental observationsthat the nature of the peptide termini (proline vs phenylalanine) affect the aggregate order, while the nature of the acidic side chains (aspartic vs glutamic acid) affect the aggregate’s stability in the presence of ions. These simulations provide valuable microscopic insight into the way ions and peptide templates mutually affect each other during the early stages of biomineralization preceding nucleation.

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light, temperature, ionic strength).10−13 In particular, amphiphilic peptides form hydrogels that manifest ECM-like characteristics,14 a property essential for tissue engineering. Zhang and coworkers15 were the first to develop such a peptide, which is β-sheet-promoting and contains a motif of alternative arrangements of hydrophobic and hydrophilic residues that induce hydrogelation via a change in pH or ionic strength.16,17 A particularly promising group of amphiphilic peptides that are rich in acidic residues were reported by Rapaport and coworkers.18,19 These peptides were designed in such a way that they self-assemble into ordered β-pleated monolayers at the air−water interface, an environment that can be considered analogous to the cell’s organic−aqueous interface.20 Fourier transform infrared spectroscopy (FTIR) and grazing-incidence X-ray diffraction (GIXD) studies suggested that the presence of proline residues at the peptide termini was crucial for inducing order in the monolayers.18 Further studies also demonstrated that these peptides form pH-sensitive hydrogels in bulk solution that can further serve as scaffolds for bone tissue cultures.19,21 In addition, upon the addition of ions, these act synergistically with the peptide hydrogels to enhance bone tissue regeneration.22 It could also be observed that peptides

INTRODUCTION Ubiquitous in nature, biomineralization is the process responsible for the formation of bone, dentin, enamel, and eggshells,1 all of which make up highly organized composite materials comprising multiple hierarchical levels.2 In bone, for example, the tissue consists of an organic phase (the extracellular matrix (ECM)) and a mineral phase (mainly hydroxyapatite crystals2). As such materials are very appealing for a number of industrial and medical applications, a variety of synthetic approaches have been launched in order to closely mimic their organic/mineral phases, including the development of ceramics, synthetic polymers, and natural biopolymers.3,4 However, each of these comes with its own drawbacks, ranging from poor mechanical properties and difficulties in controlling the degradation rate3,5 to possible rejection by the host due to immunogenic response. 3 In order to overcome these limitations, composite biomaterials have been developed that can account for many of such properties and provide a controlled environment while retaining the biomimetic morphology and structure to foster tissue regeneration.6,7 In the last two decades, much attention has been given to amphiphilic peptides that can self-assemble into nanostructures spontaneously.8,9 These also have the advantage of being tunable for a desired structure and material properties by adjustment of the peptides’ chemical groups and sequence length as well as their external environment (pH, sequence size, © 2014 American Chemical Society

Received: September 8, 2014 Revised: November 21, 2014 Published: December 3, 2014 15486

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peptides rapidly assembled into β-sheet-rich ordered aggregates within the first 10 ns of simulation time, and these aggregates remained stable over a time scale of 100 ns. However, to fully equilibrate the aggregates and possibly form fully ordered β-sheets, much longer time scales would have been required. For the data reported here, all of the simulations at the air−water interface were started from preassembled aggregates. i. Simulations without Ions. Each of the peptides ProAsp-2, ProGlu-2, and PheGlu-2 was simulated at the air−water interface starting with a system setup of nine strands preassembled into a perfectly ordered 3 × 3 aggregate (see Figure 1). In all cases, the peptide backbone was aligned parallel to the air−water interface. The side chains of all acidic residues were protonated while the termini were in zwitterionic form to best match the experimental conditions. To solvate the system, the SPC/E water model was employed.32 Final setups contained totals of 100 323, 100 317, and 115 905 atoms for the ProAsp-2, ProGlu-2, and PheGlu-2 systems, respectively. The solvated structures were first energy-minimized using the steepest descent algorithm. Next, the systems were subjected to a short 2 ns equilibration in which all of the heavy atoms of the peptides were position-restrained. Finally, a 100 ns production run was performed in the NVT ensemble at 300 K, coupled with the Berendsen or velocityrescale thermostat with a coupling constant of 0.1 ps.33,34 The LINCS algorithm35 was used to constrain the bonds involving hydrogen atoms, and the SETTLE36 algorithm was used solely for SPC/E water. Electrostatic interactions in the systems were evaluated using the particle mesh Ewald method37 with a real-space cutoff of 1 nm, while the van der Waals cutoff was set to 1.4 nm. Periodic boundary conditions were applied in all (x, y, z) directions. All of the simulations were performed with the GROMACS molecular modeling simulation package38,39 and employed the GROMOS 53A6 united-atom force field.40 ii. Simulations with Ions. Multiple simulations were set up that differed in the acidic side chains, length of peptides, and types of ions employed, the details of which are given in Table S1 in the Supporting Information. In these systems, the side chains were deprotonated and the termini were in zwitterionic form. Simulations were carried out with Na+, Ca2+, and PO43− ions or with Ca2+ and Cl− ions. Ion concentration was decided on the basis of the number of acidic groups present in the system. A more detailed discussion of the electrolyte concentration can also be found in the Supporting Information. For longer peptides (n = 5), six peptides were preassembled into a 3 × 2 array, while for shorter peptides (n = 2), the starting structures were similar to the setup used for systems without ions. The ions were added, and the system was equilibrated carefully to allow the charge distribution to readjust locally, preventing the structures from falling apart prematurely because of electrostatic repulsion due to the initial conditions. For PO43− ions, the force-field parameters were initially generated by the Automated Topology Builder (ATB) (http:// compbio.chemistry.uq.edu.au/atb/),41 with a slight modification of the O−P bond distance to 0.1535 nm and the force constant of the O−P− O angle to 900 kJ mol−1 nm−2 in order to maintain the tetrahedral geometry, both in full consistency with typical force-field parameters for phosphate groups. For the other ions, standard GROMOS 53A6 force-field parameters were used. All of the simulations were performed in the NVT ensemble with the same simulation parameters as discussed above for the systems without ions. System Analyses. i. Hydrogen-Bonding Analysis. Hydrogen bonds (H-bonds) were identified on the basis of geometrical criteria (donor−acceptor (D−A) distance ≤ 3.5 Å, D−H−A−angle ≥ 90°, H−A−AA angle ≥ 90°).42 In-house perl scripts (see ref 43 for details) were used to identify H-bonds in the starting structures as well as any newly formed H-bonds during the course of the simulation. The stabilities of these H-bonds were also monitored, and they were categorized as main-chain−main-chain (MC−MC) or side-chain− side-chain (SC−SC) interactions, depending on the types of atoms involved. ii. Ion-Bridging between β-Strands. The number of interstrand bridging interactions between Ca2+ ions and side chains were evaluated. A pair was considered as interacting if the distance between

with longer side chains exhibit higher crystalline stability during the course of the mineralization process.23 On the basis of in vivo and in vitro experiments, it has been proposed to use these peptides in local injections for the treatment of osteoporosis.22,24,25 Such experimental results clearly help us to discern the events occurring at the macroscopic level. However, an understanding of the underlying molecular-level origin leading to the observed system behavior still remains to be elucidated. To provide a quantitative description at this level in order to fine-tune the morphology of the designed structures, understanding the biomineralization process is imperative. Here, atomistic molecular dynamics (MD) simulations can shed light on the system with high resolution, which is often difficult or even inaccessible by existing experimental techniques. In the past, computational studies have been applied successfully to unravel the molecular mechanism of self-assembly of various nanostructures such as fibrils, nanotubes, and micelles.26−30 In this work, we investigated the behavior of amphiphilic β-sheetforming peptides (designed by Rapaport and co-workers) made up of repetitive sequences of hydrophobic/hydrophilic residues by varying the sequence length as well as the types of side-chain and terminal groups to study their effect on the aggregate’s stability at an air−water interface. On the basis of experimental findings that calcium phosphate mineralization is strongly affected by the nature of the acidic side chains, we carried out simulations of preassembled peptide aggregates at the air− water interface in close proximity to various ions. By varying the electrolyte composition and peptide sequence, we could thus identify the factors that dominate the aggregation of mineral-forming ions with the peptide aggregate. This leads to a better understanding of the mutual effects of ions on aggregate stability as well as a manifestation of the peptides’ role as templates in subsequent biomineralization processes.

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METHODS

Peptide Sequence and Nomenclature. Peptides with the general sequence X-Y-(Z-Y)n-X were selected, where X represents the termini and Y and Z denote residues with hydrophilic and hydrophobic side chains, respectively. The number of repetitive units of Z-Y is denoted by n (for chemical structures, see Figure S1 in the Supporting Information). In this study, we investigated peptides composed of the amino acids proline (Pro), glutamic acid (Glu), aspartic acid (Asp), and phenylalanine (Phe). Throughout the article, we have abbreviated the peptide names according to the type of terminal residue followed by the type of acidic side chain and finally the length of the peptide repeat unit, e.g., ProGlu-n, ProAsp-n, and PheGlu-n. In order to better understand the peptides’ assembly as well as the resulting aggregate’s structure and stability, simulations of systems of varying peptide concentration, sequence length (n = 2, 5), nature of the side chains (Glu/Asp), and type of termini (Pro/Phe) were carried out. System Setups. Initially, MD simulations were performed using different starting conformations (generated with the PyMOL Molecular Graphics System31). Single peptides were simulated either in aqueous solution or at the air−water interface. As these simulations consistently showed (under all conditions, i.e., different peptide types and protonation states) that the peptides readily diffused toward the air−water interface and remained there for the rest of the simulation (data not shown), simulations with multiple peptides were set up only at the air−water interface. Two peptide concentrations (9 vs 16 strands spread over the same surface area) were placed at the air− water interface, either in arrays with large spacings (no contact) between individual peptides, rotated randomly around their own axis, or as perfectly preassembled aggregates (with lattice spacings according to the experimental results). In all of the simulations, the 15487

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Figure 1. Cartoon representations of secondary structures at time intervals of 25 ns for the (A) ProGlu-2 and (B) PheGlu-2 peptide systems (top views of the aggregates at the air−water interface). The dots represent H-bonds (for a detailed molecular representation of the H-bonding, see Figure 3). Letters are assigned to the strands to follow the strand pairing. Secondary structure plots were generated with VMD,44 which uses the STRIDE45 package to assign secondary structures. Yellow, white, and cyan illustrate strand, coil, and turn structures. the oxygen of the carboxylic acid side chain and the Ca2+ ion was ≤5.5 Å. Only those ion/side-chain interactions that participate in two or more simultaneous contacts (with at least one contact to each strand) were considered.

process, interstrand conventional H-bonds involving mainchain atoms were identified and monitored (see Methods), and the results are shown in Figures 2 and S3. The MC−MC-type

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RESULTS AND DISCUSSION Fibril Formation and Fibril Order. To understand the effect of ions on aggregate stability as well as how the positions of the ions are dictated by these aggregates, it is necessary to understand the events leading up to aggregate formation in a nonionic environment. This allows us to have a control system and better comprehend any changes that occur in the aggregate’s structure and properties after the addition of ions. We started with a preassembled 3 × 3 array of peptides and observed the formation of a 9 × 1 aggregate. Monitoring of the aggregate formation for ProGlu-2 and PheGlu-2 peptide systems is shown in Figure 1 (for ProAsp-2, see Figure S2). Here it is evident that both peptide systems, which vary only in their terminal residues, organized themselves into differently ordered aggregates. In the case of ProGlu-2 (Figure 1a), the peptides reorganized into a perfect fibrillar arrangement within 50 ns of simulation time, and this arrangement stayed intact throughout the remainder of the simulation. In the case of PheGlu-2 (Figure 1b), however, the peptides rearranged relatively fast and settled into a less-perfect fibrillar arrangement with a defect (a vertical shift between strands C and F). This trend coincides with experimental observations.18 However, as a single simulation is clearly not enough to make mechanistic conclusions, we further analyzed the interactions in these fibrils to be able to draw more definite conclusions. Fibril Order and Main-Chain Hydrogen Bonding. Hbonds are among the most important non-covalent interactions that govern molecular self-assembly. To understand the distinct behavior of individual peptide strands during the assembly

Figure 2. Time evolution of MC−MC H-bonds for all strand pairs of the (A) ProGlu-2 and (B) PheGlu-2 peptide systems. The labeling of the strands follows the pattern depicted in Figure 1. Color codes for the strand pairs are shown at the top of the each panel. This figure and subsequent plots were created using Gnuplot.

H-bonding pattern for ProGlu-2 showed that some of the strand pairs exhibited six H-bonds, while others formed only four. On the basis of these numbers of stable interstrand Hbonds, “strong” and “weak” strand pairs were assigned, which were found to occur in an alternating arrangement in the fibrils. Apart from the six original strand pairs, two strand pairs (namely C−F and D−G) formed after 28 and 34 ns of simulation time, respectively, also following the alternating pattern of weak and strong pairs. In the case of PheGlu-2, however, the peptides always displayed six stable MC−MC H-bonds, and could not be further differentiated into strong and weak strand pairs. Very early in the simulation (4 ns), one of the packets rearranged and aligned with other packets to form the C−F strand pair, but not in a perfect alignment as in the case of ProGlu-2 (Figure 1a). Such an offset in the alignment leads to a disordered structure, and therefore, only four conventional MC−MC H15488

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it also inhibits the extension of β-sheets in an unordered manner because of its inability to form MC−MC H-bonds with neighboring strands. On the contrary, the Phe terminus can form interstrand MC−MC H-bonds, which make it more “sticky”, consequently causing unordered fibrillar formation, as shown in Figure 3. The system can “get stuck” in alignments with offsets since many H-bonds have already been formed (four or more). A more extensive evaluation of other aspects of the influence of the termini, for example on the interactions between two adjacent fibrils, would require the setup and equilibration of larger-scale multifibrillar aggregates, which was not the focus of the work presented here. Influence of Side Chains on Interactions within the Fibrils. In order to understand the influence of the different side-chain groups, simulation results for the ProAsp-2 and ProGlu-2 peptides, which differ only in the type of side-chain functional group, were compared. Their effect is not only relevant for fibril formation but will also help in understanding interactions with ions. To explore how side chains could impact the formation and stability of the assembly, interstrand Hbonds involving side-chain groups (SC−SC H-bonds) were evaluated. These SC−SC types of H-bonds were averaged over weak (B−C, E−F, and H−I) and strong (A−B, D−E, and G− H) strand pairs during a 100 ns simulation. Although these differ only by one methylene group, it significantly influences their ability to form SC−SC-type H-bonds (see Figure 4).

bonds were formed in this case. The other packets of PheGlu-2 rearranged later in the simulation (65 ns) and aligned perfectly with neighboring strands to form the A−G strand pair. For longer peptide chains (PheGlu-5), offsets in the strand pairing were observed as well (data not shown). In general, it should be noted that conclusions on equilibrium structures should not be made on the basis of these data. Because of the large number of MC−MC H-bonds between strands, once-formed strand pairings were found to be stable within the simulation time scale, indicating that healing of defects and reaching truly equilibrated structures are not within reach of this simulation approach. However, our results nicely corroborate the intention of the experimentalists when introducing Pro termini, which were supposed to expedite fibrillar arrangements (while Phe termini were found to lead to less-ordered fibrillar structures). Also, experimentally the Langmuir monolayers at the air−water interface as well as the fibrillar structures of the hydrogels in the bulk are not in thermodynamic equilibrium, and the Pro termini appear to act as factors that appear to (possibly only kinetically) favor the formation of more-ordered fibrils. The microscopic origin of this effect can be found in the simulation structures upon closer analysis of the differences resulting from Pro and Phe terminal groups. All of the possible conventional MC−MC interstrand Hbonds of the starting structures and during the system evolution were identified, and their stabilities during the simulation were monitored. The molecular structures for the two systems after 100 ns, along with the percentage stabilities of H-bonds, are shown in Figure 3. For the newly formed

Figure 4. Histograms showing the average numbers of interstrand SC−SC H-bonds between strong (red bars) and weak (green bars) strand pairs for the (A) ProAsp-2 and (B) ProGlu-2 peptide systems.

Overall, the two systems behave quite similarly in that on average they form one or two interstrand SC−SC H-bonds per strand pair. However, within the same system, remarkable differences can be observed. On the one hand, peptides with Asp side chains form a significantly higher number of SC−SC H-bonds between weak strand pairs compared with strong strand pairs (see Figure 4). We propose that these additional SC−SC interactions help to stabilize the weak strand pairs, which exhibit a smaller number of MC−MC H-bonds. Correspondingly, for the Asp peptides there is a large probability to find no SC−SC H-bonds between two (on the main-chain level) strongly bonded strands. On the other hand, Glu side chains do not exhibit any significant differences between weak and strong strand pairs with respect to SC−SC H-bonds. This suggests that Glu side chains do not influence the relative stability of the weak and strong strand pairings. Representative examples of the SC−SC H-bonding patterns are shown in Figure 5. The H-bonding patterns between side-chain atoms clearly illustrate that Asp and Glu residues interact differently for weak and strong strand pairings. To obtain an explanation for the observed differences on the atomic level, atomic pair distances were computed for all interstrand neighboring pairs of Cβ atoms and pairs of Cγ atoms of the Asp side chains as well as all

Figure 3. Final structures of (A) ProGlu-2 and (B) PheGlu-2 peptide systems, shown with percentage stabilities of MC−MC-type H-bonds. For clarity, only four (A, B, C, and F) out of the nine strands with only main-chain atoms and part of the terminal residues are displayed. Structures are shown in stick representation with C, N, O, and H atoms displayed in tan, blue, red, and white, respectively. H-bonds are shown as black solid lines. This figure and subsequent molecular plots were created using the UCSF Chimera package.46

strand pairs, the percentage of H-bonds was calculated only for those times in which the strands were paired (Figure 2). The presence of an alternate arrangement of weak and strong strand pairs for peptides was found when Pro was the terminal residue. In the weak strand pairs, two of the conventional MC−MC Hbonds are missing since the Pro termini do not have the proton on the amide nitrogen to donate. Hence, Pro acts as a β-sheet breaker and enforces perfect fibrillar arrangement. Furthermore, 15489

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interactions for weak and strong strand pairs (see the snapshot in Figure 5). In the following section, it will be shown that this difference in the SC behavior and the SC−SC interactions has an implication for the interaction between peptide aggregates at the air −water interface with ions. Fibril Stability and Structure in the Presence of Ions. As discussed above, some interesting trends were observed in the analysis of the preassembled monolayers for the three different types of peptides. First, the terminal residues play a crucial role in fibril formation. Importantly, even slight variations in the side chains lead to distinctive behavior in these peptide systems. This prompted us to compare the behaviors of different side chains in the presence and absence of ions. To rule out the influence of particular ions (or their specific force-field representations) in the final outcome, we performed multiple simulations of preassembled aggregates of ProAsp-n and ProGlu-n peptides (n = 2, 5), now in their deprotonated forms, with different ions. Details of the setups are given in Methods and summarized in Table S1. Snapshots depicting the secondary structure evolution of several representative systems are shown in Figures 7 and S4. As expected, peptides with Asp and Glu residues behave differently in the presence of ions. Contrary to the simulations without ions, peptides with Asp side chains started to lose their interstrand H-bonds after a few nanoseconds, and some of the strands started to disintegrate from the β-sheet. This effect was most prominent for the shorter peptides (see Figures 7 and S4). Nevertheless, it was found that the instability of peptide aggregates with Asp side chains does not depend upon the types of ions or length of the peptides, as was observed consistently in all of the five different system setups under investigation. In contrast, peptides with Glu side chains consistently maintained their secondary structures throughout the simulation. Although we observed the formation of Ca2+/PO43− clusters in the respective systems (see Figures 7 and S4), which are reversibly attached to the peptide monolayers (a behavior that is suggestively reminiscent of the experimental observations), we did not analyze these structures further. A conclusive interpretation of Ca2+/PO43− aggregation in the context of nucleation and mineral formation requires further testing and refining of the existing force-field parameters, in particular for the mineral phase and its corresponding solution components. Similar efforts to improve force-field parameters for other bioorganic/mineral systems have been very successfully carried out by different groups in the last years.47−52 Recently, the interaction of Ca2+ with acidic side chains in different force fields has been revisited.53 The necessary next step would be to refine PO43− model parameters and validate them according to the stability of the mineral phases and solution thermodynamics. Only then can a mechanistic interpretation of the next steps of prenucleation and cluster formation (with and without peptide templates) be made. As in the case of the systems without ions, the preassembled 3 × 3 aggregates of strands began to display early stages of fibril formation. However, because of the presence of the ions, this process became relatively slow and required more simulation time compared with the simulations without ions. Although we performed simulations with different ions and chain lengths (Table S1), all exhibited qualitatively similar trends. Hence, we will only discuss representative systems to explain specific phenomena, where we have made sure that qualitatively the

Figure 5. Representative examples of interstrand SC−SC H-bonding patterns for the (A) ProAsp-2 and (B) ProGlu-2 peptide systems. MC−MC and SC−SC H-bonds are displayed by solid black and dashed blue lines, respectively. For clarity, only three strands (A, B, and C) with their side-chain atoms of Asp and Glu residues are shown.

interstrand neighboring pairs of Cβ atoms and pairs of Cδ atoms of the Glu side chains. The average distance distributions show a distinct trend for weak and strong strand pairs across both peptide systems (see Figure 6). For Asp side chains, a larger

Figure 6. Interstrand side-chain distance distributions for (A) ProAsp2 peptide Cβ−Cβ atom pairs, (B) ProAsp-2 peptide Cγ−Cγ atom pairs, (C) ProGlu-2 peptide Cβ−Cβ atom pairs, and (D) ProGlu-2 peptide Cδ−Cδ atom pairs. Distributions for strong and weak strand pairs are shown in red and green, respectively.

separation of Cβ atoms between weak strand pairs compared with strong strand pairs was found. Consequently, more space is provided for Cγ−Cγ atom pairs to orient in a manner that allows carboxylic groups to come into close proximity and form interstrand SC−SC H-bonds for weak strand pairs (see Figures 5 and 6). For strong stand pairs, this would lead to steric clashes among carboxylic groups. Therefore, Cγ−Cγ atom pairs are oriented in opposite directions in the case of strong strand pairs and become unavailable for SC−SC H-bonding. For Cβ− Cβ atom-pair distances, one observes a similar behavior for Glu side chains compared with Asp side chains for both weak and strong strand pairs. However, because of the presence of the extra methylene group in the Glu side chains, the Cδ−Cδ pairs in Glu side chains behave differently from the Cγ−Cγ pairs in Asp side chains. Now the Cδ−Cδ distance distributions are very similar for weak and strong strand pairs. No preferential orientation of the carboxylic group of the Glu side chains is found, leading to no significant differences between SC−SC 15490

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Figure 7. Cartoon representations of the secondary structures observed at different time intervals for various peptide−ion combinations, viewed from the aqueous phase (the snapshot depicted as 0 ns corresponds to the structure after a very short equilibration period of up to 1000 ps to relax the ions that were added to the system). Selected instances that demonstrate the separation of β-strands in Asp-containing sheets are indicated by the black arrows. Blue and red represent the positively and negatively charged ions, respectively, while yellow, white, and cyan depict the strand, coil, and turn secondary structure elements, respectively. Black dotted lines indicate H-bonds.

other systems conform to the observations (the data are presented in the SI). A quick visual inspection indicates a more unstable nature of aggregates for peptides with Asp side chains. To analyze this effect more quantitatively, we monitored the time evolution of H-bonds between main-chain atoms (see Methods). The results for the ProAsp-n and ProGlu-n systems with different ions are displayed in Figures 8, 9a,b, and S5. As in the simulations without ions, these systems exhibit a pattern of alternating weak and strong strand pairs. Most of the weak strand pairs of ProAsp-n peptides started to lose interstrand Hbonds after a few nanoseconds of simulation time. Consequently, these strands disintegrated from the β-sheet organization (see Figure 7). In a few cases, however, the lost interstrand H-bonds were reformed through the course of the simulation and the strands reintegrated with the β-sheet, although these H-bonds remained fluctuating. Disintegration of strong strand pairs was never observed, and these pairs remained in stable β-sheet conformations. For ProGlu-n

peptides, no noticeable differences between the stabilities of the weak and strong strand pairs were observed (Figures 8 and 9), and interstrand H-bonds remained stable for both types of strand pairs such that the structural integrity of the β-sheets was maintained throughout the course of the simulation. We propose that such a disintegration/reintegration process can provide the chance of forming ordered aggregates from unordered structures, since imperfectly formed fibrils now have the possibility to reform. Side-Chain−Ion Interactions and Ion Bridges between β-Strands. A reason for the observed instability of those strand pairings that we previously labeled as “weak” (because of the smaller number of MC−MC H-bonds) up to the point of disintegration from the β-sheet organization lies in the SC−SC interactions. Previously, for the ProAsp-n systems without ions (i.e. with protonated Asp side chains), these strand pairs had been additionally stabilized by SC−SC H-bonds (Figure 4). In the following, we will demonstrate that the interaction of the 15491

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side chains, however, no preference in bridging of weak or strong strand pairs was observed, nor did any of the preformed β-strand pairs ever dissolve. Upon closer examination of the distinct molecular structures, this qualitatively different behavior could be attributed to the manner in which the ions interact with the peptide aggregates, which present a “carpet” of negatively charged carboxylate side chains to the electrolyte solution (for representative snapshots, see Figure 10). The upper panels of the figure show the situation for ProAsp-5 peptide aggregates in contact with Ca2+ ions. It was found that the side chains of the weak strand pairs are oriented toward each other and positioned optimally to form strong interactions with Ca2+ ions, which is not the case for strong strand pairs. This observation is similar to what was observed for the case of ProAsp-2 without ions (see Figure 5). However, because of the relatively short side-chain length of the Asp residues, the strands cannot accommodate Ca2+ without disturbing existing MC−MC H-bonds. Consequently, these ion-bridging interactions push apart the weak strand pairs to form the electrostatically favorable peptide−ion−peptide contacts. An event where several ions collectively push apart two strands is shown Figure 10. It should be noted that the event chosen corresponds to the contact loss of the E−F strand pair (see Figure 9a at 35−45 ns). During this process, almost all of the MC−MC H-bonds were disturbed, causing the β-sheet organization to (temporarily) disintegrate. Contrarily, for the case of ProGlu-5, the ion-bridging interactions between the β-strands do not affect the structural integrity on the MC−MC H-bonding level. The presence of the extra methylene group in the Glu side chains actually allows them to accommodate Ca2+ ion bridges without disturbing the MC−MC H-bonds. As was seen for the SC−SC H-bonds between protonated ProGlu-n peptides, the relative orientation of the side chains is similar for weak and strong strand pairs, and therefore, no significant differences could be observed for Ca2+ and side-chain interactions. The β-sheets formed by peptides with Glu side chains are more stable, and they retain a well-organized layer of carboxylate side chains directed toward the electrolyte solution where Ca2+ ions can be enriched and uniformly preassemble, thus possibly providing a scaffold at which the early stages of mineral nucleation can take place. This difference in behavior agrees with the observations of Segman-Magidovich and Rapaport,23 where Brewster angle microscopy (BAM) images showed that Asp-containing peptides adsorbed more ions in the mineralizing solution, a process which was relatively slow for Glu-containing peptides. They also hypothesized that flexible ProAsp-n templates may interact more favorably with Ca2+/PO43− clusters. Our results provide a molecular-level explanation for such behavior. Discussion and Comparison with Experimental Observations. Experimentally, it has been proposed that calcium phosphate mineralization that is induced or templated by peptide monolayers starts with the generation of calcium phosphate clusters that accumulate on the peptide aggregate’s surface. The structuring processes of these prenucleation clusters to arrive at amorphous calcium phosphate phases, which later undergo a transition to the stable mineral phase, are still very much under investigation. Segman-Magidovich and Rapaport23 conducted experiments to examine the effects of different anionic side chains in peptide templates on the early stages of calcium phosphate mineralization. According to their results, it was hypothesized that peptide aggregates with Asp side chains are held together by weaker intermolecular forces,

Figure 8. Time evolution of MC−MC H-bonds for each strand pair of the (A, C) ProAsp-2 and (B, D) ProGlu-2 peptide systems with (A, B) Ca2+ and Cl− ions and (C, D) PO43− and Ca2+ ions. Color codes for strand pairs are given at the top of each panel. Labeling of the strands follows the same pattern as in Figure 1.

Figure 9. Time evolution of interstrand H-bonds (upper panels) and average numbers of bridging events between carboxylic acid side chains and Ca2+ ions (lower panels) for the (A, C) ProAsp-5 and (B, D) ProGlu-5 peptide systems. The labeling of the strand pairs (upper panels) was done analogous to the labeling for the shorter peptides in Figure 1.

deprotonated side chains with ions essentially contributes to the stability of the strand pairs (or the lack thereof). To characterize the interactions of ions with the deprotonated Asp and Glu side chains, ion-bridging interactions between neighboring β-strands were investigated (see Methods). The average numbers of such contacts during the simulations were evaluated for weak and strong strand pairs separately (see Figure 9 for ProAsp-5- and ProGlu-5-type peptides with Ca2+ and Cl− ions in solution). Weak strand pairs of ProAsp-5 were involved in a substantially larger number of Ca2+ ion−carboxylic acid side chain contacts compared with the strong strand pairs. Contrarily, ProGlu-5 peptides did not exhibit any significant difference between weak and strong strand pairs for Ca2+ ion−side-chain interactions. For all of the systems shown in Table S1 (see Figure 7), the qualitative observation was the same, irrespective of the nature of the cations employed. For peptide aggregates with Asp side chains, bridging contacts were found predominantly between “weak” strand pairs orfor the shorter peptidesthe weak strand pairs were dissolved entirely. For peptide aggregates with Glu 15492

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Figure 10. Cartoon representations of the ion-induced separation of β-strands in Asp-containing sheets at the air−water interface and attachment of ion layers to Glu-containing β-sheets. For clarity, only three strands of each system with the Asp or Glu side-chain atoms and the ions in contact with those strands are shown. The peptides are located directly at the air−water interface, with the aqueous solution below the peptides in the side views. Snapshots in the top views are shown from the aqueous phase. Side chains and ions are displayed in ball-and-stick and sphere representations, respectively. Oxygen, calcium, and carbon atoms are shown in red, blue, and green, respectively. MC−MC H-bonds are shown as black solid lines. Simulation times are shown below the snapshots.

(Asp), where weak strand pairs are stabilized by additional sidechain−side-chain H-bonds. In the presence of cations, peptide aggregates with Asp side chains were found to be less structurally stable than peptide aggregates with Glu side chains. This effect is relevant for templating mineral nucleation and growth in two possible ways. The higher flexibility of the peptide aggregates with Asp side chains could be advantageous when the aim is to support the growing mineral while being able to adjust the template. Alternatively, if template rigidity is relevant for the mineralization process, peptides with Glu side chains seem to be more suitable since throughout the simulation they maintained their structure and interacted efficiently and uniformly with Ca2+ ions. Importantly, such a difference in behavior does not seem to be dependent upon the type of ions or the length of peptides employed. These peptide aggregates also started to display calcium phosphate aggregate formation, which is the early stage of hydroxyapatite crystallization and important for artificial bone tissue generation. Our results help explain the mechanism and potential ways to enhance the efficacy of a patented peptidebased injectable drug for osteoporosis that is currently under development.24,25 In general, our findings for a microscopiclevel description are highly relevant for the design of novel biomaterials as well as the fine-tuning of existing materials for various medical applications.

such that the adsorbed ions lead to the disruption of the aggregates. Peptide aggregates with Glu side chains, however, appear to be more stable upon ion adsorption, resulting in a higher crystalline stability during the ongoing mineralization process. Our simulations provide a molecular interpretation that is fully compatible with these observations. It should be noted that the Asp-containing aggregates are not thermodynamically weaker per se; it is only upon interaction with the ions that these aggregates disintegrate more readily. Although we carried out multiple simulations with Ca2+/ PO43− ions and observed early stages of an amorphous phase of crystal formation, we did not analyze these structures further because of known limitations in the force field, as mentioned previously. Instead, we have based our conclusions on systems with a variety of ion compositions. Nevertheless, on the basis of our preliminary results, we believe that simulations will be able to study these early stages in order to help understand how these peptides behave during apatite crystal formation, which is vital for advancing applications toward bone repair and regeneration.

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CONCLUSIONS

In the present work, we have performed a comparative MD simulation study of several amphiphilic peptides in order to better understand the influence of various factors influencing their self-assembly behavior at the air−water interface. Our results have helped unravel the probable reasons why proline as the terminal residues plays a crucial role in the formation of ordered aggregates. These findings can be important for the exact design of desired nanostructures. Furthermore, our results have identified and described the presence of alternative arrangements of weak and strong strand-pairing patterns in the peptides with proline terminal residues. This pattern is mirrored in the case of peptides with shorter side chains

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ASSOCIATED CONTENT

S Supporting Information *

Chemical structures, simulation details, secondary structure evolution, and H-bond profiles for selected systems. This material is available free of charge via the Internet at http:// pubs.acs.org. 15493

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AUTHOR INFORMATION

Corresponding Author

*Telephone: +49-(0)7531-88-3948. E-mail: christine.peter@ uni-konstanz.de. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Prof. Hanna Rapaport for many interesting discussions, valuable suggestions, and critical reading of the manuscript. We are grateful to Christoph Globisch for his help with the simulation setups and many fruitful discussions. We gratefully acknowledge financial support by the German Science Foundation within the Emmy Noether Programme (Grant PE 1625/1). Computer facilities were provided by the Rechenzentrum Garching of the Max Planck Society and the HPC cluster of Baden-Württemberg’s universities.

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