Fitting Force Field Parameters to NMR Relaxation Data

Coil-Library-Derived Amino-Acid-Specific Side-Chain χ1 Dihedral Angle Potentials for AMBER-Type Protein Force Field

The successful simulation of proteins by molecular dynamics (MD) critically depends on the accuracy of the applied force field. Here, we modify the AMBER-family ff99SBnmr2 force field through improvements to the side-chain χ1 dihedral angle potentials in a residue-specific manner using conformational dihedral angle distributions from an experimental coil library as targets. Based on significant deviations observed for the parent force field with respect to the coil library, the χ1 dihedral angle potentials of seven amino acids were modified, namely, Val, Ser, His, Asn, Trp, Tyr, and Phe. The new force field, named ff99SBnmr2Chi1, was benchmarked against NMR-derived χ1 rotamer populations of denatured proteins, overall resulting in much better agreement and without any noticeable adverse consequences on the quality of the simulation of folded proteins. The new force field should allow more realistic modeling of protein side-chain properties by MD of both folded and unfolded protein systems, such as for the better in-silico characterization of protein-protein and protein-ligand interactions.

Accuracy and Reproducibility of Lipari-Szabo Order Parameters From Molecular Dynamics

The Lipari-Szabo generalized order parameter probes the picosecond to nanosecond time scale motions of a protein and is useful for rationalizing a multitude of biological processes such as protein recognition and ligand binding. Although these fast motions are an important and intrinsic property of proteins, it remains unclear what simulation conditions are most suitable to reproduce methyl symmetry axis side chain order parameter data (Saxis2) from molecular dynamics simulations. In this study, we show that, while Saxis2 tends to converge within tens of nanoseconds, it is essential to run 10 to 20 replicas starting from configurations close to the experimental structure to obtain the best agreement with experimental Saxis2 values. Additionally, in a comparison of force fields, AMBER ff14SB outperforms CHARMM36m in accurately capturing these fast time scale motions, and we suggest that the origin of this performance gap is likely attributed to differences in side chain torsional parametrization and not due to differences in the global protein conformations sampled by the force fields. This study provides insight into obtaining accurate and reproducible Saxis2 values from molecular simulations and underscores the necessity of using replica simulations to compute equilibrium properties.

Molecular Simulations to Investigate the Impact of N6-Methylation in RNA Recognition: Improving Accuracy and Precision of Binding Free Energy Prediction

N6-Methyladenosine (m6A) is a prevalent RNA post-transcriptional modification that plays crucial roles in RNA stability, structural dynamics, and interactions with proteins. The YT521-B (YTH) family of proteins, which are notable m6A readers, functions through its highly conserved YTH domain. Recent structural investigations and molecular dynamics (MD) simulations have shed light on the mechanism of recognition of m6A by the YTHDC1 protein. Despite advancements, using MD to predict the stabilization induced by m6A on the free energy of binding between RNA and YTH proteins remains challenging due to inaccuracy of the employed force field and limited sampling. For instance, simulations often fail to sufficiently capture the hydration dynamics of the binding pocket. This study addresses these challenges through an innovative methodology that integrates metadynamics, alchemical simulations, and force-field refinement. Importantly, our research identifies hydration of the binding pocket as giving only a minor contribution to the binding free energy and emphasizes the critical importance of precisely tuning force-field parameters to experimental data. By employing a fitting strategy built on alchemical calculations, we refine the m6A partial charge parameters, thereby enabling the simultaneous reproduction of N6 methylation on both the protein binding free energy and the thermodynamic stability of nine RNA duplexes. Our findings underscore the sensitivity of binding free energies to partial charges, highlighting the necessity for thorough parametrization and validation against experimental observations across a range of structural contexts.

Parsing Dynamics of Protein Backbone NH and Side-Chain Methyl Groups using Molecular Dynamics Simulations

Experimental NMR spectroscopy and theoretical molecular dynamics (MD) simulations provide complementary insights into protein conformational dynamics and hence into biological function. The present work describes an extensive set of backbone NH and side-chain methyl group generalized order parameters for the Escherichia coli ribonuclease HI (RNH) enzyme derived from 2-μs microsecond MD simulations using the OPLS4 and AMBER-FF19SB force fields. The simulated generalized order parameters are compared with values derived from NMR 15N and 13CH2D spin relaxation measurements. The squares of the generalized order parameters, S2 for the N-H bond vector and Saxis2 for the methyl group symmetry axis, characterize the equilibrium distribution of vector orientations in a molecular frame of reference. Optimal agreement between simulated and experimental results was obtained by averaging S2 or Saxis2 calculated by dividing the simulated trajectories into 50 ns blocks (∼five times the rotational diffusion correlation time for RNH). With this procedure, the median absolute deviations (MAD) between experimental and simulated values of S2 and Saxis2 are 0.030 (NH) and 0.061 (CH3) for OPLS4 and 0.041 (NH) and 0.078 (CH3) for AMBER-FF19SB. The MAD between OPLS4 and AMBER-FF19SB are 0.021 (NH) and 0.072 (CH3). The generalized order parameters for the methyl group symmetry axis can be decomposed into contributions from backbone fluctuations, between-rotamer dihedral angle transitions, and within-rotamer dihedral angle fluctuations. Analysis of the simulation trajectories shows that (i) backbone and side chain conformational fluctuations exhibit little correlation and that (ii) fluctuations within rotamers are limited and highly uniform with values that depend on the number of dihedral angles considered. Low values of Saxis2, indicative of enhanced side-chain flexibility, result from between-rotamer transitions that can be enhanced by increased local backbone flexibility.

Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin

Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.

Boosting Ensemble Refinement with Transferable Force-Field Corrections: Synergistic Optimization for Molecular Simulations

A novel method combining the force-field fitting approach and ensemble refinement by the maximum entropy principle is presented. Its formulation allows us to continuously interpolate between these two methods, which can thus be interpreted as two limiting cases. A cross-validation procedure enables us to correctly assess the relative weight of both of them, distinguishing scenarios in which the combined approach is meaningful from those in which either ensemble refinement or force-field fitting separately prevails. The efficacy of their combination is examined for a realistic case study of RNA oligomers. Within the new scheme, molecular dynamics simulations are integrated with experimental data provided by nuclear magnetic resonance measures. We show that force-field corrections are in general superior when applied to the appropriate force-field terms but are automatically discarded by the method when applied to inappropriate force-field terms.

Combined NMR and molecular dynamics conformational filter identifies unambiguously dynamic ensembles of Dengue protease NS2B/NS3pro

The dengue protease NS2B/NS3pro has been reported to adopt either an 'open' or a 'closed' conformation. We have developed a conformational filter that combines NMR with MD simulations to identify conformational ensembles that dominate in solution. Experimental values derived from relaxation parameters for the backbone and methyl side chains were compared with the corresponding back-calculated relaxation parameters of different conformational ensembles obtained from free MD simulations. Our results demonstrate a high prevalence for the 'closed' conformational ensemble while the 'open' conformation is absent, indicating that the latter conformation is most probably due to crystal contacts. Conversely, conformational ensembles in which the positioning of the co-factor NS2B results in a 'partially' open conformation, previously described in both MD simulations and X-ray studies, were identified by our conformational filter. Altogether, we believe that our approach allows for unambiguous identification of true conformational ensembles, an essential step for reliable drug discovery.