Journal of Chemical Theory and Computation · 2011 · 1.2K citations · 79 references
Natural SciencesBiochemistryBiophysicsComputational ChemistryNucleic Acid ChemistryStructural BiologyForce FieldsMolecular DynamicsNucleic Acid DynamicsNucleic Acid ModelingNucleic Acid StructureRna StructureForce Field ModelsGlycosidic LinkagesMolecular Dynamics Of Nucleic AcidsMolecular Dynamics Simulations Of Nucleic AcidsNucleic Acid Force FieldsNucleic Acid SimulationsQuantum Chemical ModelingRna Structural Modeling
The study reparameterizes the glycosidic torsion χ in the Cornell et al. AMBER RNA force field, producing the χOL variant. The authors derived χOL from high‑level quantum‑chemical calculations that incorporate previously neglected solvation effects, and benchmarked it against earlier glycosidic tors.
We report a reparameterization of the glycosidic torsion χ of the Cornell et al. AMBER force field for RNA, χOL. The parameters remove destabilization of the anti region found in the ff99 force field and thus prevent formation of spurious ladder-like structural distortions in RNA simulations. They also improve the description of the syn region and the syn–anti balance as well as enhance MD simulations of various RNA structures. Although χOL can be combined with both ff99 and ff99bsc0, we recommend the latter. We do not recommend using χOL for B-DNA because it does not improve upon ff99bsc0 for canonical structures. However, it might be useful in simulations of DNA molecules containing syn nucleotides. Our parametrization is based on high-level QM calculations and differs from conventional parametrization approaches in that it incorporates some previously neglected solvation-related effects (which appear to be essential for obtaining correct anti/high-anti balance). Our χOL force field is compared with several previous glycosidic torsion parametrizations.
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Yan Zhao, Donald G. Truhlar · Theoretical Chemistry Accounts · 2007 · 30K citations · Full text
Natural Sciences, Chemistry, Physics +17
The Amber biomolecular simulation programs
David A. Case, Thomas E. Cheatham, Tom Darden et al. · Journal of Computational Chemistry · 2005 · 9.6K citations · Full text