Journal
JOURNAL OF CHEMICAL PHYSICS
Volume 147, Issue 16, Pages -Publisher
AMER INST PHYSICS
DOI: 10.1063/1.5001028
Keywords
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Funding
- United States National Science Foundation [ACI-1449723, CHE-1566192]
- United States National Institutes of Health [R01 GM044974, R01 GM066859, GM070855, GM072558, R44GM109635]
- Direct For Mathematical & Physical Scien
- Division Of Chemistry [1566192] Funding Source: National Science Foundation
- Office of Advanced Cyberinfrastructure (OAC)
- Direct For Computer & Info Scie & Enginr [1449723] Funding Source: National Science Foundation
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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. Published by AIP Publishing.
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