Improving Computational Predictions of Single-Stranded RNA Tetramers with Revised α/γ Torsional Parameters for the Amber Force Field.
With current advancements in RNA based therapeutics, it is becoming crucial to utilize theoretical and computational methods to describe properly the physical properties of RNA molecules. NMR and X-ray crystallography are two powerful techniques for investigating structural properties. However, if the RNA molecules are complex or dynamic, these methods might not be adequate. For computational approaches, the quality of the force field will determine accuracy of our predictions. In this contribution, we revise the α/γ torsional parameters of RNA for amber force field using a model system representing an RNA dimer backbone. Combined with revised χ torsional parameters, previously shown to improve computational predictions, we benchmarked the revised force field on five single-stranded RNA (ssRNA) tetramers, three RNA dodecamer duplexes, and an RNA hairpin. A total of 60 μs of molecular dynamics (MD) simulations were run. We also employ the discrete path sampling (DPS) approach to compare the predictions for the revised amber force field with those for amber10. Our results indicate that the unphysical states observed with amber10 in ssRNA MD simulations are suppressed for the revised amber force field. In line with NMR experimental observations, incorporation of the revised α/γ and χ torsional parameters leads to A-form-like conformational states as the most favorable ssRNA tetramer conformations. Furthermore, the revised force field maintains the A-form geometry in regular RNA duplexes. Our revised amber force field for RNA should therefore improve structural and thermodynamic predictions for challenging RNA systems.
Department of Chemistry, University of Cambridge , Cambridge, Cambridgeshire CB2 1EW, United Kingdom.
David J
DJ
Wales
Department of Chemistry and Biochemistry, Florida Atlantic University , Jupiter, Florida 33458, United States.|Scripps Research Institute , Jupiter, Florida 33458, United States.
Ilyas
0000-0001-8357-1922
I
Yildirim
D018360:Crystallography, X-Ray; D009682:Magnetic Resonance Spectroscopy; D056004:Molecular Dynamics Simulation; D012313:RNA / Q000737:chemistry*
D012313:RNA