Melittin Aggregation in Aqueous Solutions: Insight ... - ACS Publications

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The Journal of Physical Chemistry

Melittin Aggregation in Aqueous Solutions: Insight from Molecular Dynamics Simulations Chenyi Liao,† Myvizhi Esai Selvan,†† Jun Zhao,§ Jonathan L. Slimovitch,† Severin T. ∥

∥

Schneebeli,† Mee Shelley, John C. Shelley, Jianing Li†* †

Department of Chemistry, the University of Vermont, Burlington, VT 05405

††

Schrödinger, Inc., 120 West 45th Street, 17th Floor, New York, NY 10036

§

National Institute of Deafness and Other Communication Disorders, Bethesda, MD 20892

∥

Schrödinger, Inc., 101 SW Main Street, Suite 1300, Portland, OR 97204

*Corresponding author: Jianing Li. Email: [email protected]. Phone: (802) 656-0251. Department of Chemistry, the University of Vermont, Burlington, VT 05405

Abstract Melittin is a natural peptide that aggregates in aqueous solutions with paradigmatic monomer-to-tetramer and coil-to-helix transitions. Since little is known about the molecular mechanisms of melittin aggregation in solution, we simulated its self-aggregation process under various conditions. After confirming the stability of a melittin tetramer in solution, we observed — for the first time in atomistic detail — that four separated melittin monomers aggregate into a tetramer. Our simulated dependence of melittin aggregation on peptide concentration, temperature, and ionic strength is in good agreement with prior experiments. We propose that melittin mainly self-aggregates via a mechanism involving the sequential addition of monomers, which is supported by both qualitative and quantitative evidence obtained from unbiased and metadynamics simulations. Moreover, by combining computer simulations and a theory of the electrical double layer, we provide evidence to suggest why melittin aggregation in solution likely stops at the tetramer, rather than forming higher-order oligomers. Overall, our study not only explains prior experimental results at the molecular level, but also provides quantitative mechanistic information that may guide the engineering of melittin for higher efficacy and safety. Keywords antimicrobial peptide, self-assembly, mechanism, metadynamics, electrical double layer

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Introduction Melittin, a 26-residue cationic peptide from honeybee venom (Fig. 1A),1 serves as a prototypical model for protein folding and aggregation. Experimental studies involving a combination of circular dichroism (CD),2-3 nuclear magnetic resonance (NMR),4-8 X-ray crystallography,9-10 and fluorescence spectroscopies11-15 have established that melittin can dissolve in water and aggregate inside membranes to induce cell lysis. However, it is not yet clear how melittin self-aggregates at the molecular level in different environments. Part of this challenge arises from the scarce information about the molecular mechanism of melittin aggregation in aqueous solutions. Nevertheless, to understand melittin’s biological functions and enable medical applications, we need to gain a detailed mechanistic insight into melittin aggregation in solution.7 Melittin, for example, has been investigated extensively as a potential antimicrobial peptide, but its toxicity to human red blood cells has precluded its feasibility for treating infections.16 A promising solution to this dilemma is to introduce cell selectivity by modulating melittin assembly and its inherent secondary structure in the aqueous environment of the bloodstream.17-18 Moreover, recent findings suggest that melittin displays anticancer activity, driving new research that aims to safely deliver sufficient melittin to target cancer cells.19 In order to design effective approaches for targeted melittin delivery, it is critical to first foster a sound understanding of how melittin peptides aggregate in aqueous solution, under the influence of environmental factors such as heat and salt. In this work, we are therefore trying to elucidate which microscopic aggregation states of melittin coexist in aqueous environments, as well as the detailed molecular aggregation mechanism. While several experimental studies have laid the foundation to understand melittin aggregation in solution,4,

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computational analyses are necessary to provide

mechanistic details at the molecular level. At equilibrium, melittin in aqueous solution is generally believed to have significantly populated helical (ordered) and random-coiled (disordered) conformations15 and to be present as monomers and tetrameric aggregates.1, 4, 22

As has been observed experimentally,2, 6-7 the conformation and aggregation states of

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melittin can be varied by adjusting peptide concentration, temperature, ionic strength, and buffer pH. At low ionic strength and a melittin concentration below 1.0 mM, melittin exists predominantly in the monomeric form as a random coil.4-5,

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As the salt

concentration increases to 2.0 M, melittin can aggregate into tetramers and fold into a structure with up to 65% helicity.4-5,

12, 22

Further progress has been made toward

elucidating the dependence of melittin’s aggregation states on experimental conditions.2, 7 These studies indicate that tetramer formation is favored by increasing ionic strength and melittin concentration,2 while maintaining the temperature within a certain range. However, the reported temperature range — suitable for stable tetramer formation — varies among different experimental studies, namely, 269–298 K,11 291–295 K,7 308.5– 316 K,2 and 303–343 K.6

Figure 1. Structures of the melittin monomer and tetramer. (A) Graphical illustration of the tertiary structure, the solvent-accessible surface (SAS) and the primary sequence of a melittin monomer in the crystal (PDB ID: 2MLT, chain A). The basic and polar residues are shown in blue and green, respectively in the SAS and the sequence. The letter X in the sequence represents the C-terminal NH2-group. Arrows mark the helical orientations of residues 2–11 and 13–23,6 and the angle between them defines the interhelix angle, which is 48.3° for this monomer. The average interhelix angle of the four chains is 50.6 ± 2.8° in the crystal tetramer. (B and C) The superimposed conformations of a melittin tetramer before (cartoon) and after (grey loop) a 100-ns unbiased simulation (10 mM melittin, 0.15 M NaCl, and 310 K). C-termini are displayed as spheres. The average interhelix angle from the simulation (45.5 ± 16.9°) is comparable to that from NMR (46.4 ± 12.6°).6 The simulated backbone RMSD increases up to 3.7 Å, consistent with the NMR observations.6

In order to obtain mechanistic insight into the melittin aggregation process at the molecular level, we have performed and carefully analyzed all-atom molecular dynamics (MD) and metadynamics simulations of melittins in aqueous solutions. The total duration of our production simulations adds up to 3.9 µs. Prior simulation efforts have focused almost exclusively on melittin interactions with solvents or lipid membranes. Early picosecond-scale all-atom simulations provided valuable hydrodynamic insight to 3



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understand hydrogen bonding,24 water orientations,25 and dewetting transitions26 at the melittin-solvent interface. More recent simulations of melittin aggregation — conducted up to microsecond timescales — have been focused on elucidating melittin-lipid interactions,27-29 as well as on the mechanism of melittin-induced pore formation in membranes.30-32 A wide variety of conformational states have been observed in all-atom or coarse-grained simulations: the helical monomer absorbed at the membrane surface,2829, 33-35

the “U-shaped” monomer inserted into the lipid head-tail interface,29 the helical

monomer extended through the membrane,29, 36-37 and the melittin tetramer embedded into a toroidal pore.30-32, 38 While most prior simulations had to assume a single helix or tetrameric helices bound to the membrane as initial structures, the possible aggregation states adopted by melittin in solution before membrane association still remain controversial. Therefore, we systematically investigated the initial stage of melittin aggregation in solution under various conditions. Our study aims to provide both qualitative and quantitative evidence, which could be helpful to guide the modulation of melittin aggregation. For the first time, we have shown how melittin monomers aggregate into a loose tetramer at the molecular level, providing a description of the underlying physical and chemical reasons for the observed aggregation. The rest of this paper is organized as follows. First, along with the results of our MD simulations, we discuss how melittin monomers aggregate under various conditions. Next, metadynamics simulations39 are presented to explain the energetics involved in melittin aggregation. Thereafter, we provide a rationalization based on the electrical double-layer theory to explain why higher-order oligomeric assemblies of melittin may not form in solution. In the last section, with both qualitative and quantitative evidence in hand, we propose the most likely mechanistic pathway for melittin aggregation.

Results and Discussions In this study, we have constructed 8 systems and performed 21 unbiased MD and metadynamics simulations (Table S1), totaling 3.9 µs in length. Before simulating melittin aggregation, we tested the stability of a melittin tetramer with MD simulations. Overall, four 100 ns simulations starting from the X-ray crystal tetramer structure9-10 4


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under different solution conditions remain stable. Consistent with NMR data,6 the tetramer structure is slightly altered in aqueous solutions compared to the crystal structure (Fig. 1B and 1C). In the rest of our simulations we investigated the mechanism by which melittin monomers aggregate into a tetramer in aqueous solution. Effects of peptide concentration on melittin self-aggregation Given the high stability of the melittin tetramers, we anticipated that melittin would likely aggregate within the timescale of our MD simulations. Since aggregation is sensitive to different conditions, we initially varied the peptide concentration in an effort to find an optimal concentration range for investigating tetramer formation in silico. We simulated four initially separated monomers in periodic cubic boxes of 6, 9, and 12 nm in length in the presence of 0.15 M NaCl at 310 K. These box dimensions correspond to peptide concentrations of 36, 10, and 4 mM, respectively. To describe the pathways of self-aggregation, we mainly analyzed the average separation of monomer pairs and the average helicity (see SI for detailed definitions). Our simulations indicate that the peptide concentration indeed plays a key role in determining the microscopic rate of melittin self-aggregation and helix formation (Fig. 2A). At the highest concentration (36 mM), melittin aggregates very quickly, with the process almost completing by the end of the equilibration run. The average separation stabilizes around a value of 19.4 ± 2.4 Å in the last 50 ns, suggesting that the aggregated melittin persists as a loose tetramer. Similar aggregation behavior was also observed in another simulation of the same construct within 165 ns (Fig. S2A). On the other hand, we did not observe any melittin aggregation at a low peptide concentration of 4 mM within the timescale of our simulations. At a concentration of 10 mM melittin with 0.15 M NaCl at 310 K, the aggregation process takes roughly 300 ns, suggesting that this is a good concentration for us to study a relatively prolonged aggregation process. At 10 mM melittin, we find that melittin aggregation takes place in three stages, which correspond to the formation of a dimer, trimer, and tetramer, respectively. Dimer formation occurs at roughly 60 ns, with the average separation dropping from over

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45.0 Å to 40.7 ± 7.5 Å (the average inter-peptide distance in the formed dimer is 11.6 ± 1.2 Å). This step is followed by trimer formation, at 123 ns and is characterized by a drop in the average separation to 30.9 ± 3.9 Å (the average inter-peptide distance in the formed trimer is 14.4 ± 1.8 Å). A tetramer forms with the association of the remaining monomer at 231 ns. The average separation drops to a value of 17.4 ± 1.6 Å, which is reasonably close to that of the crystal structure (Fig. 2A).

Figure 2. Plots of average separation and helicity regarding all peptides over time. Pale lines show raw data, while solid lines represent smoothed quantities. The average separation from a simulation of a tetramer starting from the crystal structure geometry after a 100 ns long simulation is shown as a horizontal grey-dashed line (12.4 Å). The average monomer helicity of the crystal structure is 95.2% and the average starting helicity of the production runs is 29.5 ± 6.4%.

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In addition, we also observed an overall increase of helicity in the simulations with melittin concentrations of 36, 10, and 4 mM, but to slightly different extents. In our 36 and 10 mM simulations, one of the four monomers adopts random-coiled conformations throughout the simulations, while the other three are partially folded. In contrast, at the end of the simulation with 4 mM melittin, all the monomers are partially folded. Moreover, peptide concentration also affects the helix formation rate of melittin within our 300-ns long simulations. Starting from an initial level of helicity near 30% after equilibrium, our simulations show the helicity stabilizing at 36 ± 4, 47 ± 2, and 50 ± 3% in the last 50 ns of the 36, 10, and 4 mM melittin simulations, respectively. This indicates a possible anti-correlation between melittin helicity and the peptide concentration. Although a significantly longer time scale than 300 ns is required to reach macroscopic equilibrium, our observation is in line with the experimentally measured helicity (46% with 3 mM melittin and no salt4-5; 58% with 1 mM melittin and 0.5 M NaCl15; 65% with 0.2 mM melittin and up to 2.0 M NaCl12, 22). Hence, regarding the transient period to initiate melittin aggregation, it is likely that a lower melittin concentration encourages a faster helical formation with slower peptide aggregation. Effects of temperature and ionic strength on melittin self-aggregation To understand the effects of thermal energy on melittin self-aggregation, we carried out simulations at 283 and 333K as well, with the melittin and salt concentrations fixed at 10 mM and 0.15 M. Given the large monomer separation observed (Fig. 2B) at the end of these simulations, we found that melittin only successfully aggregates in silico at 310 K within 300 ns. While this observation differs from prior experiments that are salt-free7 or have low salt concentrations,6 it is in good agreement with the 308–316.5 K temperature range of maximum stability for tetramer formation reported by Wilcox and Eisenberg using a similar salt concentration.2 In addition, our simulations also show that melittin’s helix formation is sensitive to temperature. Although the average helicity converges to near 47% after 250 ns at all three temperatures, it actually increases faster at both 283 and 333 K than at 310 K.

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Further, we have analyzed the intramolecular and intermolecular hydrogen bonds in the melittin conformations over each simulation. Compared to 310 K, melittin forms 37% and 12% more intramolecular hydrogen bonds at 283 and 333 K, respectively, which likely indicates faster helix formation at these two temperatures. However, melittin has 70% fewer intermolecular hydrogen bonds at 283 K and 58% fewer at 333 K than at 310 K, suggesting stronger interactions for aggregation at 310 K. Therefore, temperature changes impact the competition between helix formation and aggregation through the relative rates of forming intermolecular and intramolecular hydrogen bonds. On a time scale of 100 ps, prior experiments using a denaturant found competition present between melittin intramolecular and melittin-solvent intermolecular hydrogen bonds.15 Our results, which agree with those experiments, not only confirm such competition within 300 ns, but also show the underlying temperature dependence of helix formation and aggregation of melittin. To test the influence of salt concentration, we simulated 10 mM melittin in 0.5 M NaCl solution at 310 and 333 K, in comparison to the cases with 0.15 M NaCl. Although we did not observe the formation of stable tetramers with 0.5 M NaCl at 310 K, we found that self-aggregation occurs at a much faster microscopic rate when both the ionic strength and the temperature are increased. With 0.5 M NaCl at 333K, the total separation quickly drops to near 17 Å within 100 ns, and then slowly decreases to near 12 Å within the remaining 200 ns (Fig. 2C). During this timeframe the average helicity follows a similar trend as with 0.15 M NaCl at 310K (Fig. 2C). Another simulation of the same construct also displays melittin aggregation within 100 ns (Fig. S2G). In further analysis, we found that this joint heat and salt effect might arise from (i) the suppressed electrostatic repulsion by Cl- counterions around the basic residues at the short ranges (Fig. S3A), (ii) the unaltered Pro14 solvent exposure to maintain extended melittin conformations (Fig. S3B), and (iii) the significantly reduced Trp19 solvent exposure for more monomer-monomer contacts (Fig. S3C). The detailed analysis is included in the SI. In general, the physiological salt concentration at near the body temperature seems to be optimal for melittin self-aggregation. Our simulations suggest that faster helix formation

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delays melittin aggregation, at a lower or higher temperature. These results therefore forecast how melittin folding and aggregation can be tuned precisely by adjusting environmental factors such as heat and salt. Effects of key residues on melittin self-aggregation With the atomistic details provided by our simulations, we have identified a number of hydrophobic residues that might be key for melittin aggregation. First, in our simulations solvent exposure of Pro14 and nearby residues including Leu13, Ala15, and Leu16 often induces U-shaped conformations, and further hinders aggregation. Although Pro14 seems to be necessary for melittin’s lytic activity,40 increasing the polarity of the nearby residues may stabilize the U-shaped conformations and affects melittin aggregation. Second, our simulations show a strong tendency to bury Leu9 and Trp19. We found that Trp19 reduces side-chain flexibility along with melittin helix formation, which might help to anchor the monomers together during aggregation. Leu9 along with Val5 and Val8 can form a hydrophobic patch when a helical region is formed, which could further facilitate melittin aggregation and probably even membrane association. This observation is in accordance with a prior study to increase cell selectivity using a Leu9Ala mutation.18

Figure 3. Initial stages of melittin aggregation (data obtained from the simulation of 10 mM melittin and 0.15 M NaCl at 310 K). Top panel: Snapshots taken at 0, 100, 175, and 300 ns to illustrate the typical conformations during melittin self-aggregation. C-termini are displayed as spheres. Bottom panel: Plot of average separation over time with stages highlighted with color spans. Pale lines show raw data, while solid lines represent smoothed quantities.

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Qualitative and quantitative analyses of melittin aggregation Prior experimental studies, based on two-state models, have proposed simple mechanisms for melittin aggregation: one through dimerization of dimers41 and the other one through simultaneous association of four monomers to form a tetramer.2 The two-state mechanisms, however, have long been doubted.15

Figure 4. Free-energy surface of melittin tetramer formation, calculated with a 200-ns long metadynamics simulation with 10 mM melittin and 0.15 M NaCl at 310 K. The conformational representatives shown include (A) a crystal-like tetramer, (B) a conformation between a tetramer and a trimer, (C) a trimer with a free monomer, (D) a dimer with two free monomers, (E) a stretched tetramer, (F) two close dimers, and (G) two separated dimers. The conformations obtained from the unbiased simulation (10 mM melittin and 0.15 M NaCl at 310 K) at the snapshot of 100, 175, and 300 ns are labeled in the RMSD vs. Rg space.

We analyzed the sequence of key aggregation events from the simulations with 10 mM melittin and 0.15 M NaCl at 310 K. Our analysis (Fig. 3) shows that under these conditions, two melittin monomers first quickly form a dimer that later accepts another monomer. After that, the last monomer is added to form a loose melittin tetramer. All our MD simulations, in which monomers aggregate to form a tetramer, show a similar sequence of monomer addition during tetramer formation. Thus, these results do not support a simple two-state model for melittin aggregation, where melittin tetramers form

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by dimerization of dimers.41 To obtain quantitative evidence for our proposed mechanism, we further explored the free-energy landscape of melittin aggregation using metadynamics simulations. To the best of our knowledge, this is the first metadynamics study of melittin aggregation in solution. We have performed two equivalent metadynamics simulations39 starting with the crystal tetramer, assuming that dissociation and aggregation are reversible processes.4-5 With enhanced sampling in metadynamics, one can obtain conformational states and their relative free energies that would require prohibitively long unbiased simulations.39 In our metadynamics simulations, the bias was applied to two collective variables (CVs) — the backbone RMSD compared to the crystal structure and the radius of gyration (Rg) of the peptide complex. This choice of CVs allows sampling of tetramer dissociation within 200 ns, while the tetramer is insensitive to other CVs we tested — including monomer/dimer separations and centers of mass — even on a time scale longer than 500 ns. Table 1. Melittin monomer and oligomer charge densities. Net charge (a.u.)

Average surface area Spherical radius Charge density σ (µC/cm2) (Å2) (Å)

Surface potential ψ 0 (mV)

Monomer

6

2845 ± 218

15.0 ± 1.6

3.4 ± 0.3

39 ± 3

Dimer

12

5235 ± 421

20.4 ± 2.3

3.7± 0.3

42 ± 3

Trimer

18

7062 ± 451

23.7 ± 2.1

4.1± 0.3

47 ± 3

Tetramer

24

8535 ± 545

26.1 ± 2.4

4.5± 0.3

52 ± 3

Note: Here we used the solvent accessible surface model with a probe of radius 1.4 Å to estimate all the surface areas. The spherical radii were calculated by approximating the melittin monomer and oligomers as spheres.

The two 200-ns long metadynamics simulations yield similar results. The free-energy analysis from one of the simulations is presented in Fig. 4, while details about the identified states are provided in the SI. Overall, the tetrameric state is located at the global free-energy minimum (A in Fig. 4), which is consistent with our unbiased simulations. It is also shown that the conformations with two dimers are in the 11



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high-energy region (D, F and G in Fig. 4), which is 40–48 kcal/mol higher than the tetrameric states. In contrast, the trimeric state has a free energy only 16–32 kcal/mol higher and thus is more likely to represent a stable intermediate for tetramer formation (B and C in Fig. 4). DLVO Theory to explain melittin aggregation Although prior experiments suggest that the tetramer could be the highest order of oligomer formed in melittin aggregation,1, 9, 42 it remains unclear why melittin may not form higher-order oligomers. To look for an answer, we first calculated the surface charge density of melittin dimer, trimer, and tetramer. Based on simulated conformations, the average surface charge density for melittin monomers, dimers, trimers, and tetramers are 3.4 ± 0.3, 3.7 ± 0.3, 4.1 ± 0.3, and 4.5 ± 0.3 µC/cm2 (Table 1). Obviously high-order oligomers need to afford much denser surface charges, which might exceed some limit of capacity.

Figure 5. Plot of the DLVO interaction energy over particle surface distance D (calculated with Eq. S2) and the zoom-in version for D between 13 and 20 Å. The Hamaker constant was approximated as 10-10 J. The value of 𝜀 is 7.0×10-10 F/m, and the density of water 1.005×103 kg/m.43 The dash-dot and dot lines depict the attraction and repulsion energies as functions of D, respectively. The cyan region highlights the metadynamics estimated energy of adding a monomer, the absolute value of which falls in the range of 8 to 16 kcal/mol.

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To look for a semi-qualitative explanation, we employed the Derjaguin-Landau-VerveyOverbeek (DLVO) theory to evaluate the attractive van der Waals potential versus the repulsive double-layer potential.44 According to our metadynamics simulations, adding a monomer lowers the free energy by 8 to 16 kcal/mol under our simulation conditions, which might account for the non-DLVO interactions such as hydration and hydrophobicity at short particle separations. The Debye length (𝜅 !! ) of a melittin tetramer is calculated to be on the order of 8.0 Å (Eq. S1). If we consider the interaction energy at 16.0 Å — twice of the Debye length, the repulsive DLVO energy costs for adding one more monomer to the dimer, trimer, and tetramer are around 12, 15, and 17 kcal/mol (Fig. 5). This suggests that the non-DLVO energy is insufficient to overcome the repulsive DLVO energy cost for adding one more monomer to the tetramer when they are separated by 16.0 Å. For shorter separations, the DLVO theory might no longer be a good approximation since κ D ~ 1; however it is likely that the monomer cannot get closer to the tetramer due to the dramatically increased double-layer electrostatic repulsion energy (>> 17 kcal/mol). Thus it is difficult to form melittin higher-order oligomers in solution. Although the stability evaluation of melittin aggregates with more than four monomers is out of the topic of this work, we have simulated the melittin crystal tetramer together with a free helical monomer (36 mM melittin, 0.15 M NaCl at 310 K) — a test for the stability of the tetramer under a perturbing condition — to examine our prediction from the DLVO theory. While the tetramer remains stable within 150 ns, the monomer stays 30 to 50 Å away (Fig. S4), which is in accordance with the dominant double-layer electrostatic repulsion calculated from the DLVO theory. However, the DLVO theory might not fully explain the salt and thermal impacts on melittin aggregation, although the ionic strength leads to the decrease of repulsive force (Eqs. S1 and S2). It is our hypothesis that the influences of salt and temperature increase impact on melittin aggregation might be on the DLVO interactions as well as the non-DLVO ones, such as hydrophobic interactions, hydration, and hydrogen bonds. Thus a more elaborate theory might be needed to provide a precise quantitative explanation.

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Melittin aggregation pathways and mechanisms Using both unbiased and metadynamics simulations, we have obtained qualitative and quantitative evidence regarding melittin aggregation, which allows us to propose the aggregation pathways (Fig. 6). The major pathway shows a stepwise addition of monomers, resulting in tetramer formation which is consistent with the step-growth model of melittin aggregation in lipid bilayers.45 Since melittin aggregation occurs faster than helix formation in solution, unfolded or partially folded monomers aggregate through dimeric and trimeric states before forming loose tetramers, gaining about 8–16 kcal/mol of free energy in each step. The loose tetramers might eventually fold into conformations that resemble the crystal structure, given its high stability shown in our simulations. Because of the strong electrostatic repulsion, melittin oligomers most likely stop at the tetramer on experimental timescales. The other pathway, which requires joining two melittin dimers to form a tetramer41 does not occur in our unbiased simulations. Consistent with these findings, our metadynamics simulations indicate that the merging of two dimers represents an unstable pathway with a high activation free energy (Fig. 6). Therefore, the additive mechanism — rather than a mechanism involving merging of dimers — should be dominant for melittin aggregation under the physiological condition with near 10 mM melittin.

Figure 6. Proposed melittin aggregation pathways in solution. The free-energy change for each step was estimated with a melittin concentration of 10 mM.

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The stability of each melittin aggregation state strongly depends, however, on environmental factors including peptide and salt concentrations as well as temperature. It is therefore possible to selectively favor some states by changing the conditions. In addition, we have to point out that the proposed mechanism for the tetramer formation is more applicable to low melittin concentrations, but could be affected by a high melittin concentration with a greater number of surrounding peptides during the aggregate formation. To further investigate this impact, we are simulating more than four melittin monomers at an affordable computational cost with a mixed-resolution model. Conclusions The present study strives to address the fundamental questions about how and why melittin aggregates to form tetramers in aqueous solution, focusing on the initial period of melittin aggregation at a time scale of 300 ns. We have examined the stability of melittin tetramers in solution as well as the self-aggregation dynamics of four melittin monomers under a number of conditions that mimic experiments. We simulated how the separated melittin monomers interact at different melittin (36, 10, and 4 mM) and salt concentrations (0.15 and 0.50 M), as well as at various temperatures (283, 310, and 333 K). Overall, in solution melittin is likely to aggregate into the tetrameric state via addition of monomers involving dimeric and trimeric intermediates. Despite the melittininduced membrane damaging mechanisms remaining controversial, our study suggests that formation of melittin aggregates might increase the local concentration during interactions with membrane and facilitate melittin’s disruption of the lipid bilayer. Through thermal and/or ion strength modulation, one could, presumably, favor melittin helix formation or aggregation at a short time scale, and probably to enable delicate control of melittin activity. While the mechanistic insight gained in the present study could assist the design of melittin-based anti-infection and anticancer treatments, the methodology presented in this study can likely be generalized to melittin analogues as well as other peptides and proteins for higher efficacy and safety. In general, understanding the selectivity for mammalian and bacterial membranes is of interest in the engineering of melittin. Although most melittin simulations in the literature

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use a pre-folded helix as the initial structure in either the monomeric or tetrameric state, our study suggests that melittin can form partially folded, amorphous aggregates before association with membranes. In future simulation studies of melittin insertion into a membrane, the implications of these results should be considered. Models and Methods All the simulations were performed with the CHARMM27-cmap force field using the scalable MD software program Desmond v3.0.46 Both equilibration and production runs were performed in the NPT ensemble (1 bar, Martyna-Tuckerman-Klein coupling scheme) with a time step of 2 fs. The particle mesh Ewald technique was used for the electrostatic calculations. The van der Waals and short-range electrostatics were cut off at 9.0 Å. The long-range electrostatics was updated every third time step. Each construct of the aggregation simulations has two replicas: a longer one lasting 300 ns and a shorter one lasting 100-170 ns depending on the system. Each well-tempered metadynamics simulation is 200 ns long. Data analysis is performed with Maestro v9.3 [MaestroDesmond Interoperability Tools, version 3.8, Schrödinger, New York, NY, 2014] and VMD.47 Melittin secondary structures are assigned with Stride.48 Details of the simulations and analysis are provided in the SI. Acknowledgements This work used computational resources provided by Vermont Advanced Computing Core (VACC), as well as Blacklight from the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation grant number ACI-1053575. Supporting Information Summary of unbiased MD and metadynamics simulations (Table S1); model preparation; simulation setup; data analysis tools; confirmation of melittin tetramer stability in solution; melittin aggregation analysis; analysis of heat and salt impacts; distribution of melittin monomer and oligomers (Table S2); identification of regions on the melittin freeenergy surface; calculation of DLVO energies; simulation to test further melittin

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