title: Nucleic acid reactivity: challenges for next-generation semiempirical quantum models.
abstract: Semiempirical quantum models are routinely used to study mechanisms of RNA catalysis and phosphoryl transfer reactions using combined quantum mechanical (QM)/molecular mechanical methods. Herein, we provide a broad assessment of the performance of existing semiempirical quantum models to describe nucleic acid structure and reactivity to quantify their limitations and guide the development of next-generation quantum models with improved accuracy. Neglect of diatomic differential overlap and self-consistent density-functional tight-binding semiempirical models are evaluated against high-level QM benchmark calculations for seven biologically important datasets. The datasets include: proton affinities, polarizabilities, nucleobase dimer interactions, dimethyl phosphate anion, nucleoside sugar and glycosidic torsion conformations, and RNA phosphoryl transfer model reactions. As an additional baseline, comparisons are made with several commonly used density-functional models, including M062X and B3LYP (in some cases with dispersion corrections). The results show that, among the semiempirical models examined, the AM1/d-PhoT model is the most robust at predicting proton affinities. AM1/d-PhoT and DFTB3-3ob/OPhyd reproduce the MP2 potential energy surfaces of 6 associative RNA phosphoryl transfer model reactions reasonably well. Further, a recently developed linear-scaling "modified divide-and-conquer" model exhibits the most accurate results for binding energies of both hydrogen bonded and stacked nucleobase dimers. The semiempirical models considered here are shown to underestimate the isotropic polarizabilities of neutral molecules by approximately 30%. The semiempirical models also fail to adequately describe torsion profiles for the dimethyl phosphate anion, the nucleoside sugar ring puckers, and the rotations about the nucleoside glycosidic bond. The modeling of pentavalent phosphorus, particularly with thio substitutions often used experimentally as mechanistic probes, was problematic for all of the models considered. Analysis of the strengths and weakness of the models suggests that the creation of robust next-generation models should emphasize the improvement of relative conformational energies and barriers, and nonbonded interactions.
authors.affiliation: Department of Chemistry, Scientific Computation, University of Minnesota, 207 Pleasant St. SE, Minneapolis, Minnesota, 55455-0431.|Center for Integrative Proteomics Research, BioMaPS Institute for Quantitative Biology, Department of Chemistry and Chemical Biology, Rutgers University, 174 Frelinghuysen Road, Piscataway, New Jersy, 08854-8076.
authors.forename: Ming
authors.initials: M
authors.lastname: Huang
authors.affiliation: Center for Integrative Proteomics Research, BioMaPS Institute for Quantitative Biology, Department of Chemistry and Chemical Biology, Rutgers University, 174 Frelinghuysen Road, Piscataway, New Jersy, 08854-8076.
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Giese
authors.affiliation: Center for Integrative Proteomics Research, BioMaPS Institute for Quantitative Biology, Department of Chemistry and Chemical Biology, Rutgers University, 174 Frelinghuysen Road, Piscataway, New Jersy, 08854-8076.
authors.forename: Darrin M
authors.initials: DM
authors.lastname: York
mesh_terms: D011522:Protons; D011789:Quantum Theory; D012313:RNA / Q000737:chemistry*
chemical_list: D011522:Protons; D012313:RNA
keywords: RNA catalysis; benchmark data; quantum mechanical force field; quantum mechanics/molecular mechanics; semiempirical methods