Improving the Performance of the Amber RNA Force Field by Tuning the Hydrogen-Bonding Interactions

• Published in: Journal of chemical theory and computation Vol. 15; no. 5; pp. 3288 - 3305
• Main Authors: Kührová, Petra, Mlýnský, Vojtěch, Zgarbová, Marie, Krepl, Miroslav, Bussi, Giovanni, Best, Robert B, Otyepka, Michal, Šponer, Jiří, Banáš, Pavel
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 14.05.2019
• Subjects: Chemical bonds; Computer simulation; Destabilization; Dynamic structural analysis; Hydrogen Bonding; Molecular dynamics; Molecular Dynamics Simulation; Nucleic acids; Parameter modification; Parameterization; Ribonucleic acid; RNA; RNA - chemistry; Side effects; Simulation
• ISSN: 1549-9618; 1549-9626
• DOI: 10.1021/acs.jctc.8b00955

Molecular dynamics (MD) simulations became a leading tool for investigation of structural dynamics of nucleic acids. Despite recent efforts to improve the empirical potentials (force fields, ffs), RNA ffs have persisting deficiencies, which hamper their utilization in quantitatively accurate simulations. Previous studies have shown that at least two salient problems contribute to difficulties in the description of free-energy landscapes of small RNA motifs: (i) excessive stabilization of the unfolded single-stranded RNA ensemble by intramolecular base–phosphate and sugar–phosphate interactions and (ii) destabilization of the native folded state by underestimation of stability of base pairing. Here, we introduce a general ff term (gHBfix) that can selectively fine-tune nonbonding interaction terms in RNA ffs, in particular, the H bonds. The gHBfix potential affects the pairwise interactions between all possible pairs of the specific atom types, while all other interactions remain intact; i.e., it is not a structure-based model. In order to probe the ability of the gHBfix potential to refine the ff nonbonded terms, we performed an extensive set of folding simulations of RNA tetranucleotides and tetraloops. On the basis of these data, we propose particular gHBfix parameters to modify the AMBER RNA ff. The suggested parametrization significantly improves the agreement between experimental data and the simulation conformational ensembles, although our current ff version still remains far from being flawless. While attempts to tune the RNA ffs by conventional reparametrizations of dihedral potentials or nonbonded terms can lead to major undesired side effects, as we demonstrate for some recently published ffs, gHBfix has a clear promising potential to improve the ff performance while avoiding introduction of major new imbalances.