Force-field dependence of chignolin folding and misfolding: comparison with experiment and redesign

Enhanced conformational sampling method for proteins based on the TaBoo SeArch algorithm: application to the folding of a mini-protein, chignolin

The conformational samplings are indispensible for obtaining reliable canonical ensembles, which provide statistical averages of physical quantities such as free energies. However, the samplings of vast conformational space of biomacromolecules by conventional molecular dynamics (MD) simulations might be insufficient, due to their inadequate accessible time-scales for investigating biological functions. Therefore, the development of methodologies for enhancing the conformational sampling of biomacromolecules still remains as a challenging issue in computational biology. To tackle this problem, we newly propose an efficient conformational search method, which is referred as TaBoo SeArch (TBSA) algorithm. In TBSA, an inverse energy histogram is used to select seeds for the conformational resampling so that states with high frequencies are inhibited, while states with low frequencies are efficiently sampled to explore the unvisited conformational space. As a demonstration, TBSA was applied to the folding of a mini-protein, chignolin, and automatically sampled the native structure (Cα root mean square deviation < 1.0 Å) with nanosecond order computational costs started from a completely extended structure, although a long-time 1-µs normal MD simulation failed to sample the native structure. Furthermore, a multiscale free energy landscape method based on the conformational sampling of TBSA were quantitatively evaluated through free energy calculations with both implicit and explicit solvent models, which enable us to find several metastable states on the folding landscape.

Important roles of hydrophobic interactions in folding and charge interactions in misfolding of α-helix bundle protein

An enhanced-sampling molecular dynamics simulation is presented to quantitatively demonstrate the important roles of hydrophobic and charge interactions in the folding and misfolding of α-helix bundle protein, respectively.

Balanced Protein-Water Interactions Improve Properties of Disordered Proteins and Non-Specific Protein Association

Some frequently encountered deficiencies in all-atom molecular simulations, such as nonspecific protein-protein interactions being too strong, and unfolded or disordered states being too collapsed, suggest that proteins are insufficiently well solvated in simulations using current state-of-the-art force fields. To address these issues, we make the simplest possible change, by modifying the short-range protein-water pair interactions, and leaving all the water-water and protein-protein parameters unchanged. We find that a modest strengthening of protein-water interactions is sufficient to recover the correct dimensions of intrinsically disordered or unfolded proteins, as determined by direct comparison with small-angle X-ray scattering (SAXS) and Förster resonance energy transfer (FRET) data. The modification also results in more realistic protein-protein affinities, and average solvation free energies of model compounds which are more consistent with experiment. Most importantly, we show that this scaling is small enough not to affect adversely the stability of the folded state, with only a modest effect on the stability of model peptides forming α-helix and β-sheet structures. The proposed adjustment opens the way to more accurate atomistic simulations of proteins, particularly for intrinsically disordered proteins, protein-protein association, and crowded cellular environments.

A study of the influence of charged residues on β-hairpin formation by nuclear magnetic resonance and molecular dynamics

Chain reversals are often nucleation sites in protein folding. The β-hairpins of FBP28 WW domain and IgG are stable and have been proved to initiate the folding and are, therefore, suitable for studying the influence of charged residues on β-hairpin conformation. In this paper, we carried out NMR examination of the conformations in solution of two fragments from the FPB28 protein (PDB code: 1E0L) (N-terminal part) namely KTADGKT-NH₂ (1E0L 12–18, D7) and YKTADGKTY-NH₂ (1E0L 11–19, D9), one from the B3 domain of the protein G (PDB code: 1IGD), namely DDATKT-NH₂ (1IGD 51–56) (Dag1), and three variants of Dag1 peptide: DVATKT-NH₂ (Dag2), OVATKT-NH₂ (Dag3) and KVATKT-NH₂ (Dag4), respectively, in which the original charged residue were replaced with non-polar residues or modified charged residues. It was found that both the D7 and D9 peptides form a large fraction bent conformations. However, no hydrophobic contacts between the terminal Tyr residues of D9 occur, which suggests that the presence of a pair of like-charged residues stabilizes chain reversal. Conversely, only the Dag1 and Dag2 peptides exhibit some chain reversal; replacing the second aspartic-acid residue with a valine and the first one with a basic residue results in a nearly extended conformation. These results suggest that basic residues farther away in sequence can result in stabilization of chain reversal owing to screening of the non-polar core. Conversely, smaller distance in sequence prohibits this screening, while the presence oppositely-charged residues can stabilize a turn because of salt-bridge formation.

Achieving Rigorous Accelerated Conformational Sampling in Explicit Solvent

Molecular dynamics simulations can provide valuable atomistic insights into biomolecular function. However, the accuracy of molecular simulations on general-purpose computers depends on the time scale of the events of interest. Advanced simulation methods, such as accelerated molecular dynamics, have shown tremendous promise in sampling the conformational dynamics of biomolecules, where standard molecular dynamics simulations are nonergodic. Here we present a sampling method based on accelerated molecular dynamics in which rotatable dihedral angles and nonbonded interactions are boosted separately. This method (RaMD-db) is a different implementation of the dual-boost accelerated molecular dynamics, introduced earlier. The advantage is that this method speeds up sampling of the conformational space of biomolecules in explicit solvent, as the degrees of freedom most relevant for conformational transitions are accelerated. We tested RaMD-db on one of the most difficult sampling problems - protein folding. Starting from fully extended polypeptide chains, two fast folding α-helical proteins (Trpcage and the double mutant of C-terminal fragment of Villin headpiece) and a designed β-hairpin (Chignolin) were completely folded to their native structures in very short simulation time. Multiple folding/unfolding transitions could be observed in a single trajectory. Our results show that RaMD-db is a promisingly fast and efficient sampling method for conformational transitions in explicit solvent. RaMD-db thus opens new avenues for understanding biomolecular self-assembly and functional dynamics occurring on long time and length scales.

Predicting the Thermodynamics and Kinetics of Helix Formation in a Cyclic Peptide Model

The peptide Ac-(cyclo-2,6)-R[KAAAD]-NH2 (cyc-RKAAAD) is a short cyclic peptide known to adopt a remarkably stable single turn α-helix in water. Due to its simplicity and the availability of thermodynamic and kinetic experimental data, cyc-RKAAAD poses as an ideal model for evaluating the aptness of current molecular dynamics (MD) simulation methodologies to accurately sample conformations that reproduce experimentally observed properties. In this work, we extensively sample the conformational space of cyc-RKAAAD using microsecond-timescale MD simulations. We characterize the peptide conformational preferences in terms of secondary structure propensities and, using Cartesian-coordinate principal component analysis (cPCA), construct its free energy landscape, thus obtaining a detailed weighted discrimination between the helical and nonhelical subensembles. The cPCA state discrimination, together with a Markov model built from it, allowed us to estimate the free energy of unfolding (-0.57 kJ/mol) and the relaxation time (∼0.435 μs) at 298.15 K, which are in excellent agreement with the experimentally reported values (-0.22 kJ/mol and 0.42 μs, Serrano, A. L.; Tucker, M. J.; Gai, F. J. Phys. Chem. B, 2011, 115, 7472-7478.). Additionally, we present simulations conducted using two enhanced sampling methods: replica-exchange molecular dynamics (REMD) and bias-exchange metadynamics (BE-MetaD). We compare the free energy landscape obtained by these two methods with the results from MD simulations and discuss the sampling and computational gains achieved. Overall, the results obtained attest to the suitability of modern simulation methods to explore the conformational behavior of peptide systems with a high level of realism.

Inclusion of many-body effects in the additive CHARMM protein CMAP potential results in enhanced cooperativity of α-helix and β-hairpin formation

Folding simulations on peptides and proteins using empirical force fields have demonstrated the sensitivity of the results to details of the backbone potential. A recently revised version of the additive CHARMM protein force field, which includes optimization of the backbone CMAP potential to achieve good balance between different types of secondary structure, correcting the α-helical bias present in the former CHARMM22/CMAP energy function, is shown to result in improved cooperativity for the helix-coil transition. This is due to retention of the empirical corrections introduced in the original CMAP to reproduce folded protein structures-corrections that capture many-body effects missing from an energy surface fitted to gas phase calculations on dipeptides. The experimental temperature dependence of helix formation in (AAQAA)(3) and parameters for helix nucleation and elongation are in much better agreement with experiment than those obtained with other recent force fields. In contrast, CMAP parameters derived by fitting to a vacuum quantum mechanical surface for the alanine dipeptide do not reproduce the enhanced cooperativity, showing that the empirical backbone corrections, and not some other feature of the force field, are responsible. We also find that the cooperativity of β-hairpin formation is much improved relative to other force fields we have studied. Comparison with (ϕ,ψ) distributions from the Protein Data Bank further justifies the inclusion of many-body effects in the CMAP. These results suggest that the revised energy function will be suitable for both simulations of unfolded or intrinsically disordered proteins and for investigating protein-folding mechanisms.

Starting-structure dependence of nanosecond timescale intersubstate transitions and reproducibility of MD-derived order parameters

Factors affecting the accuracy of molecular dynamics (MD) simulations are investigated by comparing generalized order parameters for backbone NH vectors of the B3 immunoglobulin-binding domain of streptococcal protein G (GB3) derived from simulations with values obtained from NMR spin relaxation (Yao L, Grishaev A, Cornilescu G, Bax A, J Am Chem Soc 2010;132:4295-4309.). Choices for many parameters of the simulations, such as buffer volume, water model, or salt concentration, have only minor influences on the resulting order parameters. In contrast, seemingly minor conformational differences in starting structures, such as orientations of sidechain hydroxyl groups, resulting from applying different protonation algorithms to the same structure, have major effects on backbone dynamics. Some, but not all, of these effects are mitigated by increased sampling in simulations. Most discrepancies between simulated and experimental results occur for residues located at the ends of secondary structures and involve large amplitude nanosecond timescale transitions between distinct conformational substates. These transitions result in autocorrelation functions for bond vector reorientation that do not converge when calculated over individual simulation blocks, typically of length similar to the overall rotational diffusion time. A test for convergence before averaging the order parameters from different blocks results in better agreement between order parameters calculated from different sets of simulations and with NMR-derived order parameters. Thus, MD-derived order parameters are more strongly affected by transitions between conformational substates than by fluctuations within individual substates themselves, while conformational differences in the starting structures affect the frequency and scale of such transitions.

Simple few-state models reveal hidden complexity in protein folding

Markov state models constructed from molecular dynamics simulations have recently shown success at modeling protein folding kinetics. Here we introduce two methods, flux PCCA+ (FPCCA+) and sliding constraint rate estimation (SCRE), that allow accurate rate models from protein folding simulations. We apply these techniques to fourteen massive simulation datasets generated by Anton and Folding@home. Our protocol quantitatively identifies the suitability of describing each system using two-state kinetics and predicts experimentally detectable deviations from two-state behavior. An analysis of the villin headpiece and FiP35 WW domain detects multiple native substates that are consistent with experimental data. Applying the same protocol to GTT, NTL9, and protein G suggests that some beta containing proteins can form long-lived native-like states with small register shifts. Even the simplest protein systems show folding and functional dynamics involving three or more states.