J Mol Model (2015): DOI 10.1007/s00894-015-2645-x

ORIGINAL PAPER

Molecular dynamics simulation and conformational analysis of some catalytically active peptides Bahareh Honarparvar 1 & Adam A. Skelton 1

Received: 29 August 2014 / Accepted: 9 March 2015 # Springer-Verlag Berlin Heidelberg 2015

Abstract The design of stable and inexpensive artificial enzymes with potent catalytic activity is a growing field in peptide science. The first step in this design process is to understand the key factors that can affect the conformational preference of an enzyme and correlate them with its catalytic activity. In this work, molecular dynamics simulations in explicit water of two catalytically active peptides (peptide 1: FmocPhe1-Phe2-His-CONH2; peptide 2: Fmoc-Phe1-Phe2-ArgCONH2) were performed at temperatures of 300, 400, and 500 K. Conformational analysis of these peptides using Ramachandran plots identified the secondary structures of the amino acid residues involved (Phe1, Phe2, His, Arg) and confirmed their conformational flexibility in solution. Furthermore, Ramachandran maps revealed the intrinsic preference of the constituent residues of these compounds for a helical conformation. Long-range interaction distances and radius of gyration (Rg) values obtained during 20 ns MD simulations confirmed their tendency to form folded conformations. Results showed a decrease in side-chain (Phe1, Phe2, His ring, and Arg) contacts as the temperature was raised from 300 to 400 K and then to 500 K. Finally, the radial distribution functions (RDF) of the water molecules around the nitrogen atoms in the catalytically active His and Arg residues of peptide 1

Electronic supplementary material The online version of this article (doi:10.1007/s00894-015-2645-x) contains supplementary material, which is available to authorized users. * Bahareh Honarparvar [email protected] 1

School of Pharmacy and Pharmacology, University of KwaZuluNatal, Durban 4001, South Africa

and peptide 2 revealed that the strongest water–peptide interaction occurred with the arginine nitrogen atoms in peptide 2. Our results highlight differences in the secondary structures of the two peptides that can be explained by the different arrangement of water molecules around the nitrogen atoms of Arg in peptide 2 as compared to the arrangement of water molecules around the nitrogen atoms of His in peptide 1. The results of this work thus provide detailed insight into peptide conformations which can be exploited in the future design of peptide analogs. Keywords Catalytic peptides . Molecular dynamics (MD) . Ramachandran plots . Radius of gyration (Rg) . Radial distribution function (RDF)

Introduction Natural enzymes that could potentially be used as biocatalysts are expensive, difficult to acquire, and easily denatured and deactivated under various physical or chemical conditions. Hence, it would be helpful to find a suitable procedure to design and model easily prepared, stable, and inexpensive artificial enzymes with similar or higher catalytic activities than natural enzymes [1]. The rational design of artificial enzymes is an ongoing area of research that could impact medicine, industrial chemistry, and energy production. Originally, the main aim of de novo design was to model enzymes using an amphipathic α-helix peptide as a fundamental unit. The polar/nonpolar sequence of the helix plays an essential role in the assembly of active-site residues [2]. The secondary structure of a polypeptide is represented by ordered conformations of a periodic (α-helix/β-sheet) or nonperiodic (turn) nature [3], and secondary structural conformations such as an α-helix and a β-sheet can be determined by

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peptides are dynamic, and interconversion between conformers is feasible. Furthermore, there was found to be a significant impact of neighboring groups on the intrinsic conformational preferences of amino acids in proteins [27, 28]. Molecular dynamics (MD) simulations of the Ala dipeptide revealed a preference for non-α-helical structures, and were used to estimate the probabilities of α-helix and β-sheet structures [29]. To explore potentially effective strategies for mimicking natural enzymes [30–34], Huang and co-workers [1] studied the self-assembly of a synthetic amphiphilic short peptide, Bpeptide 1^ (Fmoc-Phe-Phe-His-CONH2), into peptide nanotubes. The imidazolyl group of the histidine was found to act as a catalyst for the hydrolysis of p-nitrophenyl acetate (PNPA) with high catalytic activity, thereby mimicking the action of native hydrolase enzymes [35–37]. When the histidine of Fmoc-Phe-Phe-His-CONH2 was substituted with arginine (Fmoc-Phe1-Phe2-Arg-CONH2), the resulting peptide (Bpeptide 2^) showed considerably higher catalytic activity than peptide 1. These two peptides each adopt a particular conformation (secondary structure)—shown by CD and FTIR spectra to be a β-strand conformation—when self-assembled into the peptide nanotube. This conformation depends on the innate conformational preference of the peptide itself, namely its conformation in bulk water. Bearing in mind the considerable interest in exploring the intrinsic conformational preferences (i.e., those adopted in bulk water) of amino acid residues on the basis of their Ramachandran plots, the conformations of peptide 1 (Fmoc-Phe1-Phe2-His-CONH2) and peptide 2 (Fmoc-Phe1 -Phe 2-Arg-CONH 2) were explored in this study (Fig. 1). Since the catalytic activities of these peptides are of interest, it would be useful to understand the mechanism of this action. However, it is essential for us to identify the conformational preferences of these peptides when free or bound to a surface [38–40], since these will affect the catalytic mechanism; that is, the catalytic residue must be in a particular orientation to perform its catalytic function. Information about free peptides (i.e.,

experimental techniques such as circular dichroism (CD) and [4] Fourier transform infrared (FTIR) spectroscopy [5]. Molecular dynamics (MD) simulation is often used to supplement these experimental results [6–8]. The preferred conformation of the peptide chain is affected by the energetic favorability of the dihedral angles, together with additional stabilizing features such as hydrogen bonds, hydrophobic contacts, aromatic π–π stacking, and van der Waals interactions [9, 10]; these are key factors in the formation of secondary structures (helices and sheets) of peptides and proteins [3, 11–13]. The hydrophobicity of the amino acids present in a peptide or protein and the amphiphilicity of the peptide or protein in aqueous solution play essential roles in the stabilization of peptide and protein secondary structures and folding [14, 15]. In this context, hydrophobic residues cluster into the solvent-inaccessible interiors of globular proteins whilst hydrophilic residues orient themselves outward and are more solvated [16]. Moreover, each amino acid has unique conformational preferences that are influenced by hydrophobic effects and short-range interactions, meaning that these are key factors in the formation of secondary structures [17]. The conformational preferences of residues can also be characterized by the Ramachandran plot, a tool that was first used in 1963 [18, 19]. The majority of the amino acids available in the Protein Data Bank (PDB) [20] that are associated with secondary structures have backbone dihedral angles in the regions assigned by Ramachandran and coworkers [21, 22]. Despite the regular distribution of dihedral angles in proteins, short peptides generally do not maintain a specific conformational state over time in solution; rather, they appear as a dynamic ensemble of equilibrated conformers [23]. The literature contains several studies that employ MD simulation to map out conformational preferences as a function of temperature as well as residue type and arrangement [24–26]. The distributions of chain dihedral angles (Ramachandran plots) for the 20 naturally occurring amino acids of Gly-Gly-X-Gly-Gly pentapeptides (where X is an amino acid) in water were explored via MD simulation. Each residue appeared as its preferred conformation, but such

Fig. 1 Structures of the selected peptides 1 and 2

H2N O O

N H

H N O

N1

3

NH2

1NH

O N H

Fmoc-Phe1-Phe2-His-CONH2 Peptide 1

H2N

O

NH2 O

O

N H

H N

O

O

N H

NH2 O

Fmoc-Phe1-Phe2-Arg-CONH2 Peptide 2

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those that are not part of a peptide nanotube) can be gained from a molecular dynamics study, as performed in this work. In this work, the intrinsic conformational preferences of the amino acids in each peptide were identified by performing 20 ns MD simulations of peptides 1 and 2 at different temperatures in explicit water. The starting and final conformations in the simulations performed for peptides 1 and 2 (α-sheet and β-helix) are given in Fig. 2. Fig. 2 Starting (left-hand diagrams) and final (right-hand diagrams) solvated conformations in the simulations of peptides 1 and 2 (in both helix and sheet conformations)

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Here, we report the backbone conformational preference, the structural compactness (i.e., the radius of gyration, Rg), and the intramolecular residue interaction distances for both peptides to provide insight into their structures, which may aid the design of improved catalytic peptides. In addition, the radial distribution functions (RDF) of the water oxygen atoms around the nitrogen atoms in the catalytically active His and Arg residues in peptides 1 and 2 (in their extended structures) at 300 K were elucidated across full MD trajectories.

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Material and methods

obtained at three different temperatures (300, 400, and 500 K) for each snapshot within each trajectory. In addition, to gain further insight into the energetic features of the conformational landscape, all peptide/solute configurations were ranked based on the total energy (potential+kinetic energy); these are denoted B100 LE^ (100 lowest-energy) conformations below, whereas the full trajectory results are denoted Bfull traj.^ To gain insight into the folding dynamics of the peptide conformations, the radius of gyration as well as the sidechain contacts of each peptide were measured during the molecular dynamics simulations at 300, 400, and 500 K to find the molecular-level explanation for the compactness of the folded peptide conformation observed in the MD trajectory. Moreover, the radial distribution functions (RDF) of the water molecules around the nitrogen atoms in the catalytically active residues His and Arg in peptides 1 and 2 (in their extended forms) at 300 K were compared. This comparison highlighted the water–peptide interactions and their effect on the conformational differences between the two peptides.

Force field Partial charges and the force field parameters for the selected compounds were generated using the Antechamber program [41]. These were described by the general AMBER force field (GAFF) [41]. The standard AMBER force field for bioorganic systems (ff03) [42] was used to describe the parameters of the considered compounds. DFT study To check the accuracy of the force field for the non-standard Fmoc segment, the structure of Fmoc in each peptide with one water molecule present was fully optimized by applying the B3LYP method and the 6-31G+(d,p) basis set [43–45] in the Gaussian 09 program [46]. The optimized geometry was characterized as a true relative energy minimum by a frequency calculation. The obtained geometry was compared with that obtained from a classical molecular mechanics calculation using the aforementioned force field.

Results

Molecular dynamics simulation

DFT study for force field validation

The MD simulations were performed using the AMBER 12 program [47]. Each simulation focused on a peptide molecule inside a TIP3P [48] cubic water box with a distance of 5.00 Å from the solvated complex to the sides of the box. Periodic boundary conditions were applied, and the long-range electrostatic interactions were treated using the particle-mesh Ewald method [49]. The number of water molecules around each peptide of interest was found to be as follows: peptide 1 helix: 427; peptide 1 strand: 360; peptide 2 helix: 450; peptide 2 strand: 541. The peptide must first be placed into water before it can be added to a peptide nanotube. A non-bonding cutoff of 8 Å was used to truncate the intermolecular interactions. Energy minimization of the total system using the steepest descent method was performed for 1000 iterations. A canonical ensemble (NVT) MD simulation was carried out for 70 ps, during which the system was gradually heated from 0 to 300, 400, and 500 K using a Langevin thermostat [50, 51]. A time step of 1 fs was used and a snapshot of the trajectory was obtained every 1000 time steps. The trajectory was analyzed using the Ptraj module [52] implemented in AMBER 12. Different temperatures were considered for the catalytic peptides (Fmoc-Phe1-Phe2-His-CONH2 and Fmoc-Phe1-Phe2-ArgCONH2) to explore their conformational profiles. MD simulations were executed for both of the considered peptides with two different starting conformations (for each peptide, all three residues were considered as both a strand and a helix) at 300, 400, and 500 K in solution. Ramachandran plots of the backbone dihedral angles φ and ψ of the title peptides were

It was important to check that the force field generated by Antechamber for the Fmoc part of the peptide was compatible with those generated by quantum mechanical calculations. To do so, a comparison was performed between the results of density functional calculations (using the B3LYP functional) and those calculated with the force field used in this study. Since the main interaction in water–peptide simulations should be the interaction between the peptide and water—or, to be specific, between the Fmoc fragment of the peptide and water—geometry optimization of the water molecule and the Fmoc segment was performed using DFT with the B3LYP functional and the 6-31G+(d,p) basis set, and the resulting geometry and interaction energy were compared with those obtained using the force field (see Fig. 3a for the optimized structure from MM calculations and Fig. 3b for the optimized structure from DFT using the B3LYP functional). It is apparent that the geometries obtained using the two methods are qualitatively the same in terms of where the water molecule sits with its hydrogen atoms facing Fmoc. The distances obtained with the two methods are slightly different, however. The interaction energy (Eint) is calculated using the following equation: E int ¼ E Fmocþwater ‐Ewater ‐E Fmoc ; where EFmoc+water is the potential energy of the cluster in Fig. 3, Ewater is the energy of water, and EFmoc is the energy of Fmoc. Eint is −2.41 kcal/mol when calculated using MM and

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Fig. 3a–b Optimized structure of the Fmoc segment of the peptides along with a water molecule, as obtained using a the classical MM calculation and b the B3LYP method with the 6-31G+(d,p) basis set

−2.53 kcal/mol when calculated with DFT using B3LYP. These energies are very similar, indicating that the force field interacts with the water molecule in a similar fashion.

In fact, apart from peptide 2 (α-helix), all of the conformational preferences were similar at all temperatures. Analysis of the radius of gyration (Rg)

Molecular dynamics simulations To gain new insight into the factors that contribute to the underlying conformational ensembles, the possible conformations of the selected peptides were analyzed using their Ramachandran plots, their radius of gyration (Rg) values, and their intramolecular long-range interaction distances and radial distribution functions (RDFs). Conformational analysis Ramachandran plots are reported here for both of the peptides considered in this study (Fmoc-Phe1-Phe2-His-CONH2 and Fmoc-Phe1-Phe2-Arg-CONH2), with initial β-strand and α-helix conformations, at three different temperatures: plots for simulations performed at 300 K are presented in Fig. 4, and plots for simulations performed at 400 and 500 K are provided in Figs. S1 and S2 of the BElectronic supplementary material^ (ESM). The plots for the 100 LE conformational ensembles and the full trajectory are presented in black and red bold circles, respectively. At 300 K, all three residues in peptides 1 and 2 (in β-strand form) predominately maintained α-helical conformations (Fig. 4), and since the Phe2 dihedrals are adjacent to the catalytic residues (His or Arg), the presence of a difference between the preferred dihedrals of peptide 1 and peptide 2 is important. These dihedrals are indeed observed to be different, particularly when the residues initially adopt an α-helix conformation. During the simulations, the conformational ensembles of Phe2 in peptide 1 (α-helix) shifted into the β-sheet region, whilst those for peptide 2 (α-helix) stayed in the α-helical region. However, peptide 2 (α-helix) also appears in the β-sheet region at 500 K, as shown in Fig. S2 of the ESM. This indicates some affinity for the β-sheet region, but also the presence of an energy barrier that requires a higher temperature to access. For peptides 1 and 2 (in β-strand form), the conformers of Phe1 and Phe2 appeared in the β-sheet region as well as the αhelix region. The same β-sheet preference of Phe2 in both peptide 1 (α-helix) and peptide 2 (β-strand) was observed at 400 K (Fig. S1 of the ESM) and 500 K (Fig. S2 of the ESM).

The radius of gyration of a peptide describes its dimensions; it is indicative of the compactness of the packing of amino acid residues in peptides and reveals how folded or unfolded the polypeptide chain is [53, 54]. This parameter is calculated as the root mean square distance between the center of mass of the peptide and the positions of its constituent atoms when the system is in its equilibrium conformation, as follows [55, 56]: . R2 g ¼ ∑ mi ðri −Rc Þ2 M ; where mi is the mass of the ith atom and r is its position in 3D space, Rc is the position of the center of mass, and M is the mass of the atoms in the peptide [57]. In this work, the distribution of the radius of gyration values obtained during a 20 ns MD simulation of each peptide in explicit water at 300, 400, and 500 K was derived (Fig. 5). Comparison of the Rg distributions obtained using different initial conformations of the two peptides (Fig. 5) revealed that the gyration radius was independent of the initial secondary structure adopted (β-sheet or α-helix). However, when the His in peptide 1 was replaced with the Arg in peptide 2, it was noticed that the Rg values were 0.5 Å greater at all applied temperatures (300, 400, and 500 K). This can be attributed to the contribution of Arg (a long-chain residue) to the conformational pattern of peptide 2 and the enhanced interaction of water with this charged residue, as discussed below. Analysis of the long-range intramolecular interactions To gain further insight into the influence of the intramolecular side-chain interactions on the backbone conformation, the distances between the centers of mass of the side-chain groups (Phe1, Phe2, the His ring, Fmoc, and Arg) were plotted for both peptides, with both β-sheet and α-helix starting conformations, at 300 K (Fig. 6), 400 K (Fig. 7), and 500 K (see Fig. S3 in the ESM).

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Fig. 4 Ramachandran plots of the backbone torsion angles φ and ψ for the three amino acids Phe1 (left-hand plots), Phe2 (middle plots), and His/ Arg (right-hand plots) in the peptides 1 (Fmoc-Phe1-Phe2-His-CONH2; first and third rows of plots) and 2 (Fmoc-Phe1-Phe2-Arg-CONH2;

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second and fourth rows of plots) at 300 K (all three residues in the peptides were also considered in both sheet and helical conformations). Data from full trajectories and the 100 lowest-energy conformers were considered

Fig. 5a–c Histograms of radius of gyration (Rg) values obtained during simulations of the peptides Fmoc-Phe1-Phe2-His-CONH2 and Fmoc-Phe1-Phe2Arg-CONH2 (where all three residues were considered in both their sheet and helix forms) at a 300 K, b 400 K, and c 500 K

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Fig. 6a–h Distances associated with long-range interactions of different amino acids in the peptides 1 (Fmoc-Phe1-Phe2-HisCONH2; a, c, e, g) and 2 (FmocPhe1-Phe2-Arg-CONH2; b, d, f, h) at 300 K (both sheet and helical starting conformations of all three residues were used)

At 300 K, there was a sharp peak at approximately 10 Å in the histograms for the distances Fmoc–Phe1, Fmoc–Phe2, and Phe1–Phe2 (β-sheet) in peptide 1 (β-sheet) (Fig. 6a), while the histograms were more spread out for peptide 2 (β-sheet) (Fig. 6b). It is worth noting that the peak distances dFmocPhe1 and dFmoc-Phe2 for peptide 2(12 Å) are greater than

those for peptide 1 (β-sheet) (10 Å). The scattered conformational ensembles that cause the broad peak were also observed for dPhe1-Phe2 in Fig. 6b at approximately 12–16 Å, which was accompanied by a shoulder region at around 8–10 Å. The difference in scattering between peptides 1 and 2 may be due to the change in water–

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Fig. 7a–h Distances associated with long-range interactions of different amino acids in the peptides 1 (Fmoc-Phe1-Phe2-HisCONH2; a, c, e, g) and 2 (FmocPhe1-Phe2-Arg-CONH2; b, d, f, h) at 400 K (both sheet and helical starting conformations of all three residues were used)

residue interactions that results when His is replaced with the long-chain, positively charged Arg residue; this will be addressed in the next section. In contrast to our previous observations for the results gained at 300 K (Fig. 6), at 400 K, peptide 2 (β-sheet) showed a sharp peak in the distance histograms of Fmoc–Phe1, Fmoc–

Phe2 (β-sheet), and Phe1–Phe2 at around 4 and 4.5 Å, respectively (Fig. 7a and b). The significant structural fluctuations indicated by this wide spread in the distribution of distances disappeared at higher temperatures. This was because the conformations are more restricted to local minima at lower temperatures; however, upon increasing the temperature, the

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ability of the peptide to explore more conformational space allows the peptide to adopt more favorable conformations. The distance histograms for Fmoc–Phe1 and Fmoc–Phe2 in peptide 1 (α-helix) (Fig. 7c) were close to the β-sheet (Fig. 7a), and these data were almost independent of the initial conformation (α-helix or β-sheet). In addition, the maxima in the histograms of the distance of the histidine ring from Fmoc, Phe1, and Phe2 in peptide 1 (Fig. 7a) appeared at 4.5 Å, whereas the maxima in the histograms of the distance of the arginine ring from Fmoc, Phe1, and Phe2 in peptide 2 (Fig. 7f) appeared as broader peaks at 6 Å. The conformational behavior of the selected peptides at 500 K (Fig. S3 in the ESM) was similar to that seen at 400 K. In order to check the sampling and assess whether the data actually achieved convergence, the simulation was extended for an additional 40 ns. The time evolution of the long-range interaction distances is provided in the ESM (Fig. S4). It is apparent that, in every case (peptides 1 and 2, initial β-sheet and α-helix conformations, all distances), there was a dramatic decrease in interaction distance at different points in the simulation. This decrease occurred at 38 ns for peptide 1 (βsheet), at 28 ns for peptide 2 (α-sheet), at 18 ns for peptide 1 (β-helix), and at 32 ns for peptide 2 (α-helix). Interestingly, all of the distances changed at exactly the same time in each simulation, indicating that there were two different conformational states during each MD trajectory. Regardless of the initial configuration, there was one state that was more extended and one where the conformation was folded in such a way that the catalytic residue (His/Arg) oriented itself closer to Fmoc. Analysis of interactions between water and the catalytic residues The results have shown that there are differences between peptide 1 and peptide 2 in terms of conformation. These differences can mainly be attributed to differences in interactions of the catalytic residues (Arg and His) with water [58, 59]. To probe these interactions, the radial distribution functions [RDF, g(r)] of the oxygen atoms in water molecules around nitrogen atoms in the active residues (His/Arg) in peptides 1 and 2 were derived (Fig. 8). Each value of gij(r) represents the probability of finding an atom of type i at a distance r from an atom of type j. The nitrogen atoms in question are labeled in Fig. 1 as N1, H2N of peptide 1, and 1NH, H2N, and 3NH2 of peptide 2. The distribution of water molecules around the nitrogen atoms in the arginine residue in peptide 2 show more structure than the distribution of water molecules around the nitrogen atoms of histidine in peptide 1 does. In particular, N3 of peptide 2 show the highest first peak in the RDF (at around 3 Å, containing an average of 1.5 water molecules, calculated by finding the integral of the RDF); this is because it has two hydrogen atoms with which to form hydrogen bonds with oxygen atoms in water. The next largest first peak (containing

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Fig. 8 Radial distribution functions for the oxygen atoms in water molecules around the nitrogen atoms in the catalytically active residues (His/Arg) in peptide 1 (Fmoc-Phe1-Phe2-His-CONH2) and peptide 2 (Fmoc-Phe1-Phe2-Arg-CONH2) at 300 K (note that all three residues in each peptide were considered to be in their sheet conformations)

about 1.2 water molecules) in the RDF is shown by N2 of peptide 2; this is a smaller peak than that for N3 of peptide 2 because it has only one hydrogen atom that can form hydrogen bonds with oxygen atoms in water, and because N1 is a secondary amine, meaning that it has restricted access to water molecules due to steric hindrance. Even smaller peaks are also observed at about 5 Å in the RDFs for N1 and N2 of peptide 2, which are due to the water oxygen atoms that lead to the large first RDF peak for N3. In addition, there is a small RDF peak for N3 of peptide 2 which corresponds to the second solvation shell around the N3 amine group. N1 and N2 of peptide 1 show no distinct RDF peaks, indicating a lower probability of water–residue interactions. The increased probability of water– peptide interactions involving the Arg group of peptide 2 than the His of peptide 1 has significant implications. It is likely that the water molecules strongly influence Arg by pulling it into a more extended structure, as implied by the greater Rg values (Fig. 5) seen for peptide 2 compared to peptide 1. To explore the effect of temperature on the RDF plot, the RDFs at 400 and 500 K were derived, and these are shown in the ESM (Fig. S5). The RDF barely changes as the temperature increases; however, the largest peaks for N2 and N3 of peptide 2 differ because of differences in the mobility of water molecules around these functional groups.

Discussion CD and FT-IR spectra showed that these peptides adopt β-sheet conformations when they are in a co-assembled nanopeptide [1]. However, our results showed that the peptides were predominantly in their α-helix conformations in solution. Therefore, we expect that the peptides

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adopt their β-sheet conformations upon the formation of the peptide nanotube. The larger Rg values seen for peptide 2 and the observation that the Arg–residue distances were greater than the His–residue distances (Figs. 5, 6, and S3 in the ESM) indicate that peptide 2 is more extended than peptide 1. Experimentally, peptide 2 is found to be more catalytically active than peptide 1 [1]. It has been suggested that the catalytic activity of peptides can be enhanced by reducing the entropic cost of forming the enzyme–substrate complex. This can be achieved by adsorbing and pre-organizing active-site residues, thus dictating the configuration of the complex [2]. Since the final adsorbed conformation is influenced by entropic factors associated with the nanotube state, it is conceivable that the differences noted in the present study are significant; however, further investigations involving MD simulations of the peptides when they are in a peptide nanotube should be carried out. Indeed, such simulations are being performed as part of our ongoing study.

Conclusions The mechanisms that lead to the formation of peptide and protein helices in water is an ongoing research field in peptide design. In the work reported in the present paper, MD simulations in water at 300, 400, and 500 K were used to explore the possible intrinsic conformations of two catalytically active peptides, peptide 1 (Fmoc-Phe1-Phe2-His-CONH2) and peptide 2 (Fmoc-Phe1-Phe2-Arg-CONH2). Ramachandran plots of the backbone torsion angles (φ and ψ) for the three amino acids in these peptides were employed to identify their secondary structures. It was shown that the backbone dihedrals adjacent to the catalytic region (His/Arg) appeared in different regions of the Ramachandran plots. The intramolecular longrange interaction distances together with the radius of gyration (Rg) values observed during 20 ns MD simulations confirmed the formation of folded conformations. This may indicate that intramolecular side-chain contacts between neighboring functional groups (Phe1, Phe2, His rings) are a crucial influence on the conformation adopted by the peptide. Furthermore, water– residue RDFs suggested that there are differences between the interactions of His side-chain atoms with water and the interactions of Arg side-chain atoms with water, and these differences may lead to the conformational disparity between peptides 1 and 2. A comparison of the radius of gyration values observed during the 20-ns MD simulations indicated that replacing the His in Fmoc-Phe1-Phe2-His-CONH2 with Arg (resulting in Fmoc-Phe1-Phe2-Arg-CONH2) caused the Rg values to increase by approximately 0.5 Å at all temperatures applied (300, 400, and 500 K). These differences between the two selected peptides could account for the observed variation in catalytic activity upon substituting Arg with His, and may

be important when these peptides are considered as components of an artificial enzyme. This study investigated the behavior of two catalytic peptides in water. However, from an experimental perspective, the peptides form part of a peptide nanotube. Therefore, exploring the behavior of the peptides as components of a peptide nanotube is an ongoing research objective, and the current work paves the way for such studies. Acknowledgments The support of both the CHPC (http://www.chpc. ac.za), in terms of providing computational resources, and KwaZuluNatal University is highly acknowledged. Conflict of interest The authors declare that they have no conflict of interest.

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