| Literature DB >> 29096505 |
Lori A Burns1, John C Faver2, Zheng Zheng2, Michael S Marshall1, Daniel G A Smith1, Kenno Vanommeslaeghe3, Alexander D MacKerell4, Kenneth M Merz2, C David Sherrill1.
Abstract
Accurate potential energy models are necessary for reliable atomistic simulations of chemical phenomena. In the realm of biomolecular modeling, large systems like proteins comprise very many noncovalent interactions (NCIs) that can contribute to the protein's stability and structure. This work presents two high-quality chemical databases of common fragment interactions in biomolecular systems as extracted from high-resolution Protein DataBank crystal structures: 3380 sidechain-sidechain interactions and 100 backbone-backbone interactions that inaugurate the BioFragment Database (BFDb). Absolute interaction energies are generated with a computationally tractable explicitly correlated coupled cluster with perturbative triples [CCSD(T)-F12] "silver standard" (0.05 kcal/mol average error) for NCI that demands only a fraction of the cost of the conventional "gold standard," CCSD(T) at the complete basis set limit. By sampling extensively from biological environments, BFDb spans the natural diversity of protein NCI motifs and orientations. In addition to supplying a thorough assessment for lower scaling force-field (2), semi-empirical (3), density functional (244), and wavefunction (45) methods (comprising >1M interaction energies), BFDb provides interactive tools for running and manipulating the resulting large datasets and offers a valuable resource for potential energy model development and validation.Year: 2017 PMID: 29096505 PMCID: PMC5656042 DOI: 10.1063/1.5001028
Source DB: PubMed Journal: J Chem Phys ISSN: 0021-9606 Impact factor: 3.488