Peptide Sequence and Solvent as Levers to Control Disulfide

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B: Biophysics; Physical Chemistry of Biological Systems and Biomolecules

Peptide Sequence and Solvent as Levers to Control Disulfide Connectivity in Multiple Cysteine Containing Venom Toxins Karuna Anna Sajeevan, and Durba Roy J. Phys. Chem. B, Just Accepted Manuscript • DOI: 10.1021/acs.jpcb.8b01437 • Publication Date (Web): 14 May 2018 Downloaded from http://pubs.acs.org on May 15, 2018

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The Journal of Physical Chemistry

Peptide Sequence and Solvent as Levers to Control Disulfide Connectivity in Multiple Cysteine Containing Venom Toxins Karuna Anna Sajeevan and Durba Roy* Department of Chemistry, Birla Institute of Technology and Science-Pilani, Hyderabad Campus, Jawahar Nagar, Shameerpet Mandal, Hyderabad, Telangana 500078, India

*Corresponding Author. Electronic mail: [email protected]

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ABSTRACT Judicious choice of solvent, temperature and strategic mutations along a peptide backbone can minimize formation of non-native disulfide bond isoforms in chemical synthesis of multiple cysteine containing venom toxins. By exploiting these controls, one can drive the population distribution in favor of a particular isoform. Some chosen ionic liquids (ILs), like 1-ethyl-3-methyl-imidazolium acetate, [Im21][OAc], have proven efficient in favoring the native globular isoform in some conotoxins. To comprehend such a preference, we report an explicit solvent replica exchange molecular dynamics (REMD) study of two conotoxins, AuIB and GI, solvated in either neat water or ~50% (v/v) mixture of water-[Im21][OAc]. Our simulations indicate that compared to neat water, the probability of obtaining native globular isoform of AuIB significantly increases in water-IL mixture at 305 K. Strikingly, and aligned with experimental observations, peptide GI does not favor the native connectivity in water-IL mixture. In presence of IL, strong solvent mediated fluctuations of the GI backbone are observed in our simulations. Uneven ion accumulation along the backbone owing to strong Hbonding interactions of some GI residues with IL ions, especially the anion OAc-, restricts conformational freedom of the peptide. Estimation of backbone entropy and Helmholtz free energy corroborates the lack of conformational freedom in GI as compared to AuIB, especially in presence of IL. In line with prior experiments, simulations of GI mutants indicate that one could possibly force a given pair of Cys residues to come closer by strategically mutating GI residues with Glycine and /or Alanine, resulting in the breakage/formation of helix like motifs.

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I. INTRODUCTION Cysteine (Cys) residues and disulfide linkages are unequivocally important in maintaining the functional form and catalytic efficiency of numerous venom peptides.1 Contrary to an expected prevalence of 3.3%, presence of cysteine appears to be limited in all organisms.2-4 The reason behind this underrepresentation may be linked to the inherent tendency of Cys to get oxidized.5,

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Nevertheless, the occurrence of the reactive

sulfhydryl group makes cysteine unique for its catalytic efficiency and ability to form a disulfide bond, which often serves as a structural scaffold in proteins.7,

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Myriads of

natural and synthetic peptide toxins and cyclotides having therapeutic importance are found to possess multiple disulfide linkages and cystine knots/motifs.1, 9 However, two serious drawbacks from which peptides/proteins containing multiple cysteine residues suffer are (i) their vulnerability towards oxidative damage and (ii) the disadvantage of forming several disulfide bond isoforms.10, 11 In this work, we address some concerns related to the second disadvantage. The distinct disulfide bond isoforms have their own characteristic structural and functional properties involving differences in potency and other attributes. The present work is centered on two conotoxins, AuIB and GI, which are neurotoxic peptides produced by marine cone snails and are very aggressive as well as specific towards the human nicotinic acetylcholine receptors (nAChRs).12-19 Essentially, they belong to a class of compounds having huge potential to be developed as nonaddictive pain relievers.20 The cysteine linkages in such toxin peptides are often crucially related to their structural integrity and functional potency.21-23 The 15 residue conotoxin AuIB (GCCSYPPCFATNPDC), produced by the marine cone snail Conus aulicus belongs to the ‘A’ superfamily of conotoxins and is a

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selective inhibitor of α3-β4 subtype of the mammalian nAChRs.12, 13, 15, 16, 24-27 In native AuIB, the disulfide bridges connect the cysteine residues at positions 2-8; 3-15 and the peptide has a globular structure. The two disulfide bonds play a very crucial role in maintaining a robust -helix in the globular isoform.25 Two other possible combinations of disulfide crosslinks in AuIB lead to the non-native ‘beads’ (2-3; 8-15) and ‘ribbon’ (215; 3-8) isoforms, which do not possess any α-helical motif. Exceptionally, the nonnative ribbon isoform has been found to be a more potent competitive inhibitor of α3-β4 nAChRs than the native globular form.14, 15, 27 Conopeptide

GI,

a

13-residue

peptide

toxin

having

the

sequence

ECCNPACGRHYSC and isolated from Conus geographus, targets muscle subtype nAChRs causing postsynaptic inhibition in vertebrate neuromuscular junction.17,

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In

mammalian muscle nAChRs, GI most effectively inhibits the α/δ site and to a lesser extent blocks the α/γ site. The binding pattern of GI with its receptor was first modeled by Ghermann et al.19 It was shown that the residues Cys2, Asn4, Pro5, Ala6 and Cys7 constitute the α-subunit binding face, while Arg9 and His10 drive the toxin selectivity.19 The intriguing question that lies behind the complicated disulfide scrambling phenomenon is how to control outcome of the equilibrium that exists between different disulfide bond isoforms. Peptide sequence, especially the nature of intervening amino acids between cysteine residues play a pivotal role in guiding the connectivity pattern of the cysteine residues, as was shown by Zhang and Snyder in their seminal works on conotoxin GI and its synthetic mutants.28, 29 A series of recent works by Imhof and coworkers suggest that careful choice of solvent and temperature conditions can influence the complicated equilibrium in favor of a particular isoform.10,

4


11

They used aqueous

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solutions of room temperature ILs as their solvent of choice and showed that one biocompatible IL, 1-ethyl-3-methyl-imidazolium acetate, [Im21][OAc], particularly helped linear precursors of several conopeptides like µ-SlllA, µ-PlllA and δ-EVlA fold into the corresponding native isoform at room temperature even without any auxiliary redox agent and organic solvents.11 Contrary to this observation, in conopeptides like αGI and CCAP-vil, [Im21][OAc] actually disfavors the formation of native disulfide connectivity.11, 30, 31 It appears that the peptide sequence, the overall peptide secondary structure around disulfide bonds and specific interactions of the peptide with the IL ions are collectively responsible for the preferential outcome of the disulfide bond isoform equilibrium. The usefulness of room temperature ILs in chemical reactions as eco-friendly alternatives to conventional volatile organic compounds is well known. Being unique due to having host of interesting solvation characteristics, ILs are aptly suited to tackle some of the most difficult problems in chemical industry.32-35 Due to their highly charged structure and unique solvating power, ionic liquids are widely used for dissolution, processing and regeneration of otherwise tough bio-macromolecules like cellulose, utilizing rather benign reaction strategies.36-38 The domain encompassing the interaction of ionic liquids with proteins and peptides is extremely diverse.38-40 A nucleophilic anion in an ionic liquid can disintegrate the strong H-bonding networks of protein leading to dissolution and further chemical modification of the otherwise hydrophobic biomolecule.41, 42 Undoubtedly, it’s the nature of the solvent-peptide interface that strongly controls the distribution of IL ions around a peptide. Strong H-bonding between IL ions and peptide may result in large buildup of ions leading to dehydration and subsequent

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destabilization of the biomolecule.31, 40 Cone snail venoms are an assortment of several cysteine rich peptides. Ionic liquids are observed to be beneficial in handling such venom peptides in numerous ways. Ionic liquids proved very useful in dissolving hydrophobic peptides like δ-EVIA and δSVIE, which are otherwise sparingly soluble in buffer solutions.43 Reactions exploiting ionic liquids as medium could subside unwanted side reactions like dimerization or formation of misfolded products. Researchers have widely used the biocompatible and less viscous IL, [Im21][OAc], for effective oxidative folding reactions of hydrophobic conopeptides without the use of additional redox reagents (e.g. oxidized glutathione).11, 30, 43, 44

Being a special combination of a strong nucleophilic and kosmotropic anion, OAc-

and a chaotropic cation Im21+, [Im21][OAc] is well known for stabilizing the native folds of peptides/proteins against thermal degradation.10, 11, 41 Other important factors affecting the folding yield and the ease of formation of disulfide bonds in various conopeptides are the peptide sequence, position of the cysteine residues and the overall peptide hydrophobicity.30, 43 In their pioneering work with the wild type and mutated α-conotoxin GI, Zhang and Snyder showed that out of many influencing factors, peptide sequence and the characteristics of the intervening amino acids between Cys residues, play a pivotal role in regulating the relative ratios of the possible disulfide bond isoforms. Insertion or deletion of certain amino acid residues in GI mutants proved helpful in tempering the disulfide bond isoform population ratio.29 Solvent and temperature conditions also influence the isoform population distribution critically. Especially, if an ionic liquid is used as a solvent, the solvent exposed surface areas of the peptide is strongly affected by the first solvation shell,

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exhibiting the consequence of the ionic kosmotropicity / chaotropicity, which, essentially fades away with increasing distance from the peptide.45 Experiments suggest that ionic liquid anions usually have a longer residence time around peptides owing to strong specific interactions with positively charged amino acids like Arg, Lys and His. The negatively charged amino acids like Glu and Asp, on the other hand, interact strongly with IL cations.46 Peptide sequence and nature of the solvation shell regulate the exposed surface area of a peptide. A peptide is more prone to attack by IL ions in presence of coils rather than helices/strands, as the latter makes the structure compact and less solvent exposed.46 In this work, AuIB and GI are solvated in either water or water-[Im21][OAc] mixture (50% v/v) and the accompanying solvent and temperature induced bias in the population distribution of the different disulfide bond isoforms is studied under various combinations of peptide and solvent conditions. Mutated GI peptides are also studied in these two solvent systems to assess the importance of peptide sequence in recognizing a given disulfide connectivity. II. METHODS A. Modeling of the starting peptide configurations The starting coordinates of the ribbon isoform of AuIB (PDB ID: 1MXP) and the beads isoform of GI (PDB ID: 1XGC) are obtained from solution phase NMR structures of the respective peptides deposited in RCSB Protein Data Bank.14, 19, 47 These starting structures are further altered by breaking the cystin linkages and adding two H atoms instead, using VMD psfgen plugin,48 an act similar to the experimental condition of complete reduction of disulfide bonds in the peptides. This step removed the initial 7



bias from the starting peptide configuration and helped us to follow the structural evolution of a given disulfide bond isoform into another, along the course of the MD simulation. Starting guess structures of the reduced GI mutants are generated using online PEP-FOLD server.49, 50 B. Modeling of the simulation box For neat water simulations, the reduced peptides are solvated in a cubic box of TIP3P water containing ~2850 water molecules and subjected to an initial conjugate gradient minimization of 5000 steps. This is followed by equilibrium MD simulations for 40 ns in NPT ensemble at 305 K and 1 atm. The final equilibrated cubical box is ~ 44 Å along each axis. The center of the box is then moved to the center of mass of the peptide and all waters are wrapped. From this equilibrated box, a smaller cube of edge length 26 Å containing the peptide and the first hydration shell of ~570 water molecules is scooped out for further REMD simulations. For the simulations of peptides in water-IL mixture, 460 water and 52 IL molecules are equilibrated for 40 ns in NPT ensemble at 305 K. The equilibrated cubical box has edge length of ~ 30 Å. Thus the water-IL mixtures contained ~ 50% IL (v/v). It is worth noting here, that water-IL mixtures containing < 50% water are significantly sluggish, which is detrimental to having a good REMD sampling of the peptide conformation space. C. Simulation software, parameters and force field All MD simulations employed NAMD as the molecular dynamics software.51, 52 The AMBER all atom force field developed by Cornel et. al., is used to describe the bonding and non-bonding potentials of AuIB, wild type GI and its mutants.53 As mentioned in our previous works on AuIB,54, 55 AMBER force field could parameterize

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the terminal as well as the non-terminal cysteine residues, either disulfide bonded or reduced, in AuIB and GI. The water molecules are explicitly modeled by TIP3P force field as incorporated in CHARMM.56, 57 The force field for the ionic liquid cation of 1ethyl-3-methylimidazolium Acetate, [Im21][OAc], is adapted from the work of Chaban et. al.,58 while the parameters for the anion OAc- are taken from CHARMM General Force Field, CGenFF.59 A time step of 2 fs is used for the equilibrium simulations. The non-iterative SETTLE algorithm is used to keep waters and all bonds involving hydrogen rigid.60 Langevin dynamics is used for both temperature and pressure control. For the Langevin temperature coupling, a damping coefficient of 5 ps-1 is employed to all atoms except hydrogen. In the equilibrium simulations, a modified Nosé-Hoover method controlled the barostatic fluctuations, where the pressure control is realized through isotropic fluctuation of the simulation cell and coupling to a piston of oscillation period 200 fs and a damping time scale of 100 fs. A cutoff at 12 Å (or 10 Å for REMD) are used for the non-bonded VDW interactions. Smoothing functions are applied to both VDW and electrostatic forces with a switch distance of 10 Å (or 8 Å for REMD). A pair list distance of 14 Å (or 12 Å for REMD) is used for VDW and electrostatic calculations. Coulomb interactions are calculated through the particle mesh Ewald method. Intramolecular non-bonded interactions between atoms separated by three bonds (1-4 interaction) are excluded. Full electrostatics is evaluated at intervals of 4 fs, while the non-bonded interactions are calculated every 2 fs. Periodic boundary conditions are applied along the three directions of the orthogonal simulation box. The REMD simulations (NVT) for peptide/water system consisting of 26 replicas are run between temperatures 279-415 K with an

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exchange probability of ~ 0.5. For peptide/water-IL system, 30 replicas are simulated between 305-600 K with an exchange probability of ~ 0.3. REMD simulations are carried out with a timestep of 1 fs and swap interval of 1 ps. Coordinate frames are saved for further analysis after every 10 swapping attempts. The total simulation length per replica for water and water-IL simulations is 50 ns and 85 ns. To ensure proper equilibration under NVT conditions for all the replicas involved, we have only considered the last 40 and 50 ns of the REMD trajectories respectively for peptide/water and peptide/water-IL systems, for further analysis. REMD simulations for the GI mutants are run for 50 ns per replica. Visualization of the structure and analysis of the replica exchange data are done using VMD,48 PLUMED,61, 62 and MATLAB (R2015b, version 8.0). III. RESULTS AND DISCUSSION A. Choice parameters for REMD simulations During replica exchange in explicit solvent REMD simulations, the solventsolvent interaction energy dominates the total potential energy of the system.63 Thus, peptide energy may not always be the deciding factor in choosing a conformer during sampling, in presence of explicit solvent molecules. Thus it is vital to understand whether the peptide is able to exploit its conformational energy to scan the coordinate space effectively during a REMD simulation. Fig. 1 shows the internal energy distributions of the total system (peptide plus solvent) and only peptide for AuIB and GI solvated in aqueous-IL solution. A reasonable degree of overlap is observed between the peptide only energy distributions. The broadening/shifting of the distributions of the peptide potential energy (Fig. 1), as the temperature of the replica is increased indicates that the peptide conformations are filtered sensibly across the replicas.

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Figure 1. Internal energy distributions for AuIB and GI in water-IL system: total system (top); only peptide (bottom).

Following Abraham and Gready,64 the convergence of our simulations is assessed in terms of the transit number and the potential energy autocorrelation times. The average exchange probabilities are 0.5 and 0.3 for peptide/water simulations and peptide/water-IL simulations respectively. Using these values for exchange probability, the recommended

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transit number for both peptide/water and peptide/water-IL systems, with respectively 26 and 30 replicas is ~ 1000. For a sensible REMD run, it is necessary to have the number of exchange attempts considerably larger than the transit number. In our case, for respectively peptide/water and peptide/water-IL systems, the number of exchange attempts are 50,000 and 85,000, the swap interval is 1 ps and the total simulation length per replica are 50 ns and 85 ns. Further, to ensure that our swap interval is not too fast, we calculated the potential energy autocorrelation function for both peptide-water and peptide/water-IL systems. The average decay time for potential energy autocorrelation for both peptide-water and peptide/water-IL systems at 305 K is ~ 1.0 ps, with an ultrafast component of ~ 125 fs contributing to 34% of the decay, followed by a long component of 1.5 ps. Hence, the swap interval of 1 ps should work reasonably. B. Scanning of peptide conformation space in water and water-IL mixture Recent experiments have shown that [Im21][OAc] promotes native folding in certain cysteine rich conopeptides. However, an exception to the aforesaid preference of [Im21][OAc] towards the native disulfide bond isoform is noted very strongly in the case of conopeptide α-GI. To understand this discrepancy better, we have scanned the conformation space of the peptides AuIB and GI in water and water-IL mixture in detail. The purpose is to find the relative probability of obtaining the three disulfide bond isoforms of the respective peptides and to understand the solvent influence on the process of disulfide scrambling. The limitation of studying bond formation or cleavage in molecular systems using classical molecular dynamical force fields is averted by following the event of formation of a given disulfide bond from the proximity of the sulfur atoms (S) of the two Cys residues under consideration, within a cutoff distance of 5

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Å. Breaking the disulfide bonds in the starting structure through modeling of reduced peptides is thus a necessary step in this study as it attributes maximum freedom to the peptide to explore the conformation space and overcome the bias of the initial conformation. Fig. 2 and Fig. 3 represent respectively the sampled conformation space for the different isoforms of AuIB and GI in water-IL mixture.

Figure 2. S-S distance (Å) distributions for the three disulfide bond isoforms of AuIB in water-IL mixture. The right panel shows distribution of snapshots sampled from the last 50 ns replica exchange trajectory across all temperatures. The left panel indicates the snapshots falling within 5 Å only, along chosen combination of each S-S coordinate, as indicated by the small black rectangle in the right panel plots.

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The right panel shows the S-S distance distributions corresponding to the three disulfide bond isoforms of AuIB considering all the snapshots obtained from the last 1.5 µs of the 2.55 µs REMD trajectory (85 ns x 30 replicas), and the left panel shows the same when both the S-S distances are ≤ 5 Å.

Figure 3. S-S distance (Å) distributions for the three disulfide bond isoforms of GI in water-IL mixture. The right panel shows distribution of snapshots sampled from the last 50 ns replica exchange trajectory across all temperatures. The left panel indicates the snapshots falling within 5 Å only, along chosen combination of each S-S coordinate, as indicated by the small black rectangle in the right panel plots.

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From Fig. 2 it is evident that in AuIB/water-IL mixture, the hits within 25 Å2 are highest for the globular combination of disulfide bonds, followed by the beads combination. For GI however, the native globular isoform seems not to be preferred in water-IL.

Figure 4. A comparison of the number of hits in the S-S distance distributions for only the globular isoform of AuIB and GI in pure water and water-IL mixture. The snapshots are collected from the last 40 or 50 ns replica exchange trajectory of the respective systems across all temperatures.

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Despite starting the simulations from the modified NMR solution phase structure of the ribbon isoform of AuIB (PDB: 1MXP), at the end of the REMD simulation, the probability of observing the ribbon isoform is significantly reduced as compared to other isoforms. This shows that the bias of the initial structure could be successfully overcome in our simulations. In case of GI however (Fig. 3), the globular isoform population is extremely low in water-IL mixture. This observation is supported by experimental results and will be discussed later. The relative proportions of the different isoforms of AuIB and GI in water and water-IL mixture are tabulated in Table 1. Fig. 4 shows the comparison of the S-S distance distributions of the globular isoform of AuIB and GI solvated in either water or water-IL mixture. The density of folded forms as evident from the number of hits within the red rectangle in Fig. 4 is much higher in AuIB as compared to GI in both the solvents. For AuIB, in water, the native globular isoform dominates ~61% of the population at 279 K (Fig 4, Table 1). In AuIB/water-IL mixture, the native isoform population significantly increases to ~83 % while the ribbon isoform reduces to zero at the temperature of 305 K. In GI on the other hand, neat water seems to be favoring all the isoforms equally (Table 1). However, strikingly, in the water-IL mixture at 305 K, we hardly find any native isoform population of GI. This observation is qualitatively corroborating the experimental report by Imhof and co-workers,11 who observed that when α-GI is subjected to oxidative folding in neat [Im21][OAc], its yield noticeably decreases (~50%) as compared to aqueous buffer (80%). This is contrary to expectation as for all the other conotoxins studied by the Imhof group in that report, namely, µ-SIIIA, µ-PIIIA and δ-EVIA, the highest yield and quality of the oxidized product is observed in [Im21][OAc].11 The Imhof group also studied the effect of

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water concentration in aqueous [Im21][OAc] solution, on the oxidative folding of conopeptide µ-SIIIA. The yield of the oxidized product dropped from 70% to 30%, when water concentration is raised from ~ 3% to 10%. B. Backbone entropy and Helmholtz free energy from REMD trajectories To understand why GI shows differential behavior in water-[Im21][OAc] mixture as compared to AuIB, we focused on the calculation of some thermodynamic properties of the system at constant volume, like internal energy (U), entropy (S) and Helmholtz free energy (A) from the different conformers sampled throughout the trajectory. The internal energy considered here is the sum of all bonding and non-bonding interactions for the backbone atoms of the peptide. To find out how much conformational freedom is attributed to AuIB and GI in the two solvents, we calculated the absolute conformational entropy of the polypeptide backbone for the peptides in water and water-IL mixture. This analysis is particularly significant as AuIB and GI differ in their amino acid sequence. It is well known that a change in amino acid sequence can interfere with the flexibility of the peptide backbone, thereby altering the range and distribution of the Ramachandran angles.65 Backbone conformational entropy is evaluated from the probability distribution of the ϕ - ψ dihedral angles of the main chain of polypeptides.66 In this report we employ the methodology of Stites et.al.65 to calculate the backbone entropy. From the conformations of the peptide sampled throughout the REMD trajectory for all replicas, all possible values of the Ramachandran ϕ - ψ angles exhibited by a given amino acid in the peptide sequence are collected. Next, for each amino acid in the peptide sequence, we binned the Ramachandran angles into 30 × 30 grids of width 12o (the dihedral angle values range between 0 and 360o). Each amino acid in a given snapshot of the peptide is

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then categorized in a specific bin depending on the values of its ϕ - ψ angles. Following this, we calculated the absolute entropy contribution ( ) from the amino acid residue in the peptide chain, for a particular snapshot in the REMD trajectory, from equation (1).

= −

(1)

where, ′′, is the index of the bin which houses the particular ϕ - ψ

dihedral pair

observed in the snapshot under consideration. ′ ′ is the number of snapshots belonging to the ith bin, is the total number of snapshots sampled and is the area of each square bin of edge 120. The ratio ⁄ gives an estimate of the probability (Pi) of finding a particular ϕ - ψ angle pair for a given amino acid residue in the ith bin in the ensemble of conformers collected from the REMD trajectory. This procedure is repeated for all amino acids by considering the distribution of its dihedral angles obtained from the REMD sampled conformations. Lastly, the total backbone entropy for the peptide in a particular snapshot ( ) is obtained by summing over all the residue-wise entropies as given by equation (2). = ∑

(2)

Since every snapshot is associated with a given replica having an average temperature of T K, we further used the internal energy and entropy of each snapshot to estimate its Helmholtz free energy, A, given by the following expression: = −

(3)

In order to understand how the thermodynamic parameters and structure of each snapshot are correlated to the deviation of the snapshots from the native conformation of AuIB and GI, we calculated the backbone RMSD for each of these snapshots from their

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respective native globular isoform crystal structures (1DG2 for AuIB and 1XGA for GI). We also calculated end-to-end distance of the peptide backbone in a snapshot to correlate with its entropy. The end-to-end distance is a measure of the compactness of the peptide. Fig. 5 and 6 show respectively, the contour plots of RMSD vs. entropy and Helmholtz free energy with the color bar describing the changes in backbone end-to-end distance of the peptide. For both AuIB and GI, snapshots in water have higher spread in entropy than those in water-IL mixture (Fig. 5), despite the fact that water-IL replicas reach a higher temperature of 600 K as compared to 400 K in water. Specific H-bonding interactions of the peptides with IL play an important role in constraining the backbone of the peptide, which diminishes its conformational freedom and exploration of different Ramachandran angles. The backbone free energies of the peptide on the other hand show larger variance in water-IL mixture than in water alone (Fig. 6), possibly due to the presence of a wide range of conformers differing in internal energy and entropy. Some of the snapshots in water-IL mixture reach extended backbone end-to-end distance and hence higher RMSDs, not seen in water, most probably due to higher temperatures reached in water-IL mixture, which helps in overcoming the barriers. Apart from these general observations, the entropy range exhibited by the two peptides AuIB and GI are quite distinct in both water and water-IL mixture. The maximum backbone entropy reached by peptide GI is less than that observed in case of AuIB and the effect is more pronounced in water-IL mixture than in neat water. This points to the fact that GI is significantly interacting with water-IL mixture leading to lack of conformational freedom.

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Figure 5. Contour plots of RMSD vs. entropy of each snapshot, sampled from the last 40 or 50 ns of the REMD trajectory across all temperatures for the different peptide-solvent combinations. The regions are colored based on their peptide backbone end-to-end distance value. The RMSD of each snapshot is calculated with the native globular isoform crystal structures (1DG2 for AuIB and 1XGA for GI) of the peptides as a reference. The end-to-end distance is calculated between the Cα atoms of the first and last residues in the respective peptides. All the conformers that satisfy the S-S distance criteria for the native isoform of AuIB in either water or water-IL mixture are encompassed within the red oval. Same for GI are depicted by the pink triangles. Representative conformers for both AuIB and GI from each region are shown for comparison. The respective native globular isoform crystal structures for the two peptides are shown on the left panels.

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Figure 6. Contour plots of RMSD vs. Helmholtz free energy of each snapshot, sampled from the last 40 or 50 ns of the REMD trajectory across all temperatures for the different peptide-solvent combinations. The regions are colored based on their backbone end-to-end distance value. All the conformers that satisfy the S-S distance criteria for the native isoform of AuIB in either water or water-IL mixture are encompassed within the red oval. Same for GI are depicted by the pink triangles.

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C. Residue wise H-bonding in AuIB and GI in water and water-IL mixture To probe the differences in H-bonding interactions in AuIB and GI in the two solvents, we calculated the distributions of H-bond per residue in the two peptides. Figures 7 and 8 show the residue-wise comparison in H-bond distributions/efficiency of the two peptides in water and water-IL mixture respectively.

Figure 7. Residue wise peptide-solvent H-bond distributions in AuIB and GI, solvated in pure water: AuIB (solid black line) and GI (red dashed line). The analysis is done over all snapshots sampled from the last 40 ns of the REMD trajectory across all temperatures.

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Figure 8. Residue wise peptide-solvent H-bond distributions in AuIB and GI solvated in water-IL mixture: AuIB (solid black line) and GI (red dashed line). The analysis is done over all snapshots sampled from the last 50 ns of the REMD trajectory across all temperatures.

It is notable that in GI, the N-terminal residue, Glu is much strongly H-bonded to the cation in water-IL mixture as compared to its counterpart Gly in AuIB. The Im21+ cation has a large occupancy value near the glutamic acid residue in GI. In dipolar water however, the H-bond efficiency of Glu and Gly are similar (Figs. 7 and 8). This is a clear

23



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dominance of ion-ion interaction as opposed to ion-dipole interaction. Apart from the Nterminal residue, other notable hydrogen bonding residues in GI are Arg9 and His10 (deprotonated) showing significant enhancement in H-bonding in water-IL mixtures. D. Radial distribution functions and occupancy maps of IL ions around the peptide Fig. 9 shows the radial distribution function, g(r), of the IL ions and water in the first solvation shell of ~ 5 Å around the peptides AuIB and GI. The g(r) plots show that GI interacts particularly strongly with the anion OAc-. Even with the cation and water molecules, the overall interaction of GI

seems

higher

than

AuIB.

This

phenomenon would put restrain on the local movement of GI leading to distortion and lack of choice for the peptide to choose the most favorable structure otherwise. Figure 9. Radial distribution functions of the peptides AuIB (solid black line) and GI (dashed red line) in water-IL mixture. All distributions are measured within 5 Å of the peptide. (A) peptide-[Im21+]; (B) peptide-[OAc-] and (C) Peptide-water. The analysis is an average of the snapshots from the last 50 ns of the lowest temperature replica (305 K) in peptide/water-IL simulations.

24


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The authors believe that it is due to these factors that GI is not able to fold to the native conformation with high yield in water-IL mixture. It is noteworthy here that though neat water favors the relative population of the native isoform of GI, the absolute number of snapshots within the 5x5 Å2 of the S-S distance correlation map for the native combination is very small as compared to AuIB (Fig. 3 and 4). Fig. 10 shows the occupancy maps of the IL cation and anion around the notably interacting amino acid residues in AuIB and GI. The especially robust ionic cloud around

Figure 10. Occupancy maps of the IL-ions within a solvation shell of 5 Å from AuIB and GI in water-IL mixture at 305 K. The peptide is depicted as purple ribbon. For both the peptides, the yellow [OAc-] cloud has an isovalue of 0.035, while the ochre [Im21+] cloud has an isovalue of 0.85. The amino acid residues interacting most with the IL ions in AuIB (Gly1, Tyr5, Asn12, Asp14) and GI (Glu1, Arg9, Hid10) are highlighted.

25



Arg9 and His10 in GI is reducing the peptide’s flexibility in a pivotal backbone position, thereby preventing the Cys2-Cys7 and Cys3-Cys13 residues from coming close to each other and forming the desired native disulfide linkage. This is one of the reasons why our simulations indicate very less number of snapshots falling within the 5x5 Å2 of the S-S distance correlation map for the native combination, when GI is solvated in water-IL mixture. Our results are in qualitative agreement with experimental observation of low oxidative folding yield of GI in presence of [Im21][OAc].11, 43 Fig. S1 shows the RMSF values of the two peptides in water and water-IL mixture for the replica at 306 K and 305 K respectively. While for AuIB, the fluctuations are roughly close in both the solvents, for GI, the RMSF values are considerably higher in water-IL mixture. GI interacts with IL fairly strongly, and being relatively less structured as compared to AuIB, correlates strongly with the motion of the IL ions. Experiments and simulations investigating the role of ionic liquids in altering the structure and dynamics of biomolecules reveal that ionic liquids indeed interfere not only with the structure but also with the dynamics of the biomolecule. A molecular dynamics study of the enzyme xylanase in aqueous [Im21][OAc] solution by Jaeger et. al. shows that the binary mixture of [Im21][OAc] and water is capable of significantly altering the characteristics of the main modes of enzyme motion, leading to creation of newer correlated motions, otherwise absent in neat water as solvent.67 The slow modes of peptide/protein motion may couple with the cation and anion motion of the ionic liquid aided by the stable H-bonds as observed previously in several experimental and simulation studies.67, 68

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E. Disulfide bond isoform populations in GI mutants In order to verify, if one can control the disulfide connectivity pattern by playing with the peptide sequence and solvents as switches, we modeled two mutants of GI: a double mutant (N4G/G8A) and a penta mutant (A6G/G8A/H10A/Y11A/S12A) with the thought of introducing organized structural patterns in certain regions of the peptide, facilitating selective formation of a particular pair of disulfide bridges and hence a specific isoform (Fig. S2). Pace et. al. categorized amino acids into a ‘helix propensity’ scale based on their frequency of occurrence in α-helices.69 According to Pace et. al., Alanine has helix propensity (in kcal mol-1) of zero, implying it is a very efficient α-helix builder, whereas Glycine has a propensity index of 1, implying that it is a helix breaker.69 In this work, we have used the idea of insertion/deletion of Glycine and Alanine to break/extend a helical motif in the peptide GI. In the double mutant (ECCGPACARHYSC; N4G/G8A), the replacement of Asn4 (helix propensity of 0.65) by Glycine prevented Cys3 to be part of any helix like motif and away from Cys13, alternatively forcing the sulfur atoms of Cys7 and Cys13 within 5 Å. This imposition increased the probability of a disulfide linkage between Cys7 and Cys13, which along with further squeezing of the peptide in presence of water-IL mixture as solvent, lead to almost 100% population of beads isoform for this mutant at 305 K (Fig. S2 B, Table 1). Similarly, in the pentamutant (ECCNPGCARAAAC; A6G/G8A/H10A/Y11A/S12A), the replacement of Gly8, His10, Tyr11 and Ser12 by Alanine, helped extend the helix like motif from residue 8 to 12, preventing the proximity of Cys7 and Cys13. Additionally, the new motif helped the sulfur atoms of Cys3 and Cys13 to be close to each other so as to form a linkage. Similarly Cys2 and Cys7 are brought close to each other by this modification.

27



Finally, in the REMD simulations of the penta-mutant in water-IL mixture, we are successful in observing 100% population for the native disulfide connectivity at 305 K (Fig. S2 C, Table 1). When all replicas are considered, that is essentially at high temperatures, the yield of the native isoform in the penta-mutant decreases, as the helical motif unfolds, removing the constraint on the Cys residues. It is noteworthy here that the solvent influence is equally important along with the mutation of the residues in biasing the equilibrium. From the REMD simulations of the double- or penta-mutant of GI in neat water, we have not observed any snapshot falling within the required 5x5 Å2 cutoff for any of the isoforms at 279 K. However at high temperature, considering all the replicas, we observed the different isoforms building up for these mutants (Table 1). The above series of simulations with wild type GI and two mutants is in qualitative agreement with the experimental observations of Zhang and Snyder.29 Zhang and Snyder in one of their early works studied the factors that could dictate selective formation of specific disulfides in synthetic variants of conotoxin GI. In a denaturing buffer, the wild type GI showed ~ 47 % globular, 31% beads and 22% ribbon isoforms, displaying no particular preference to any specific isoform. This observation is reciprocated in our REMD simulations of wild type GI in neat water (Table 1). For the GI synthetic mutant P5A/G8A, (no. 9 in Table 1 of ref. 22), highest percentages of the globular isoform (63-77%) is observed, qualitatively in line with our observations. Thus it is evident that crucial handles like peptide sequence along with proper choice of solvent and temperature can help control the disulfide scrambling phenomenon by forcing the isoform equilibrium preferentially towards a specific isoform.

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IV. SUMMARY AND CONCLUSIONS Disulfide scrambling and production of isoforms with non-native disulfide linkage is a major hurdle in dealing with synthetic variants of multiple cysteine containing venom peptides like conotoxins. Experiments and our simulations indicate that the peptide sequence itself plays a major role in picking up the native disulfide connectivity pattern. In nature, the biological solvent water and physiological temperature play decisive roles in choosing the native connectivity. However, in laboratories one could possibly exploit different solvent and temperature conditions along with strategic mutation of the peptide sequence to carefully isolate a particular disulfide bond isoform while eliminating others. In this report we compare the contrasting disulfide bond isoform population distributions of two α-conotoxins AuIB and GI in water and water-[Im21][OAc] mixture with an aim to understand the background of natural selection for a particular pattern of cystin connectivity. All the three isoforms of GI appear structurally less organized than those of AuIB, and hence are equally preferred in neat water. Additionally, GI is easily deformed by strongly interacting water-[Im21][OAc] solvation shell leading to a very low folding yield for the globular isoform. The native globular isoform of AuIB on the other hand possesses a very robust α-helix, which ascribes structural stability to the peptide, thereby propelling the equilibrium towards this form in both neat water and water-[Im21][OAc] mixture. GI is found to interact strongly with the IL through H-bonds, accumulating large ionic atmospheres almost at the middle of the backbone thereby restricting/modulating its degrees of freedom. All these accounts for the experimental differences between the folding propensities of AuIB and GI in water-[Im21][OAc] mixture. Our simulation results further reciprocate experimental observations on GI synthetic mutants, whereby

29



strategically

mutating

GI

residues

with

Glycine/Alanine

Page 30 of 39

resulted

in

the

breaking/formation of helix like motifs, forcing a given pair of Cys residues to come close to each other thereby forming the desired disulfide bond. Using this strategy, our simulations indicate that the yield of the isoform possessing native disulfide connectivity (Cys2-Cys7; Cys3-Cys13) could be increased to 100 % at 305 K in water-[Im21][OAc] mixture for the penta-mutant of GI. However, mutation of peptide sequence may interfere with its biological activity and interaction with the nAChR receptors, which need to be addressed carefully. This work further gives insight to the possible reasons, as to why in case of some peptides like AuIB, nature predominantly picks up one of the disulfide bond isoforms as its native variety of the peptide. ACKNOWLEDGEMENTS The authors are indebted to Professor Mark Maroncelli, The Pennsylvania State University for his endless support and encouragement. The authors are also grateful to Dr. Debashis Barik, University of Hyderabad, India, for his kind help in providing computation time. KAS and DR are obliged to the Science and Engineering Research Board, India (SERB, YSS/2014/000301) for funding. Authors also appreciate support from Department of Science and Technology, India for the FIST grant SR/FST/CSI240/2012.

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Page 38 of 39

Table 1. Relative probabilities of formation of a disulfide bond isoform in AuIB and GI solvated in either water or water-IL mixture. Data from either lowest temperature replica or all-replicas are used for the analysis. Peptide

Solvent

AuIB Water (GCCSYPPCFATNPDC) Water-IL GI (ECCNPACGRHYSC)

Water Water-IL

GI-double mutant (ECCGPACARHYSC)

Water Water-IL

GI-penta mutant (ECCNPGCARAAAC)

Water Water-IL

Replica Considered* 279 K All 305 K All 279 K All 305 K All 279 K All 305 K All 279 K All 305 K All

Globular (%) 60.9 53.2 83.3 57.6 38.3 36.4 1.9 2.9 0 19.6 0 5.3 0 10.0 100 35.1

Ribbon (%) 31.3 34.3 0 5.8 32.9 37.2 20.3 20.1 0 19.6 0 2.0 0 16.6 0 4.2

* For peptide/water simulations, 279 K is the lowest temperature replica. The same for peptide/water-IL system is 305 K.

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Beads (%) 7.8 12.3 16.6 36.5 28.7 26.4 77.7 77.0 0 60.8 100 92.7 0 73.4 0 60.7

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Table of Contents Graphic

39


Peptide Sequence and Solvent as Levers to Control Disulfide

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