The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions
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- Lori A. Burns
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology 1 , Atlanta, Georgia 30332-0400, USA
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- John C. Faver
- Quantum Theory Project, The University of Florida 3 , 2328 New Physics Building, Gainesville, Florida 32611-8435, USA
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- Zheng Zheng
- Quantum Theory Project, The University of Florida 3 , 2328 New Physics Building, Gainesville, Florida 32611-8435, USA
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- Michael S. Marshall
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology 1 , Atlanta, Georgia 30332-0400, USA
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- Daniel G. A. Smith
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology 1 , Atlanta, Georgia 30332-0400, USA
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- Kenno Vanommeslaeghe
- Department of Analytical Chemistry and Pharmaceutical Technology (FABI), Center for Pharmaceutical Research (CePhaR), Vrije Universiteit Brussel (VUB) 4 , Laarbeeklaan 103, B-1090 Brussels, Belgium
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- Alexander D. MacKerell
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland 5 , Baltimore, Maryland 21201, USA
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- Kenneth M. Merz
- Quantum Theory Project, The University of Florida 3 , 2328 New Physics Building, Gainesville, Florida 32611-8435, USA
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- C. David Sherrill
- Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology 1 , Atlanta, Georgia 30332-0400, USA
説明
<jats:p>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.</jats:p>
収録刊行物
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- The Journal of Chemical Physics
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The Journal of Chemical Physics 147 (16), 2017-09-11
AIP Publishing