期刊
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 11, 期 2, 页码 753-765出版社
AMER CHEMICAL SOC
DOI: 10.1021/ct500867u
关键词
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资金
- U.S. National Science Foundation (NSF) [DMS-1319731]
- NSF Center for Theoretical Biological Physics (CTBP) [PHY-0822283]
- National Institutes of Health [R01GM096188]
- Genomics Institute of the Novartis Research Foundation
- NSF
- NIH
- HHMI
- NBCR
- CTBP
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [1319731] Funding Source: National Science Foundation
- Division Of Physics
- Direct For Mathematical & Physical Scien [1427654] Funding Source: National Science Foundation
- Division Of Physics
- Direct For Mathematical & Physical Scien [1308264] Funding Source: National Science Foundation
Proteinligand binding is a key biological process at the molecular level. The identification and characterization of small-molecule binding sites on therapeutically relevant proteins have tremendous implications for target evaluation and rational drug design. In this work, we used the recently developed level-set variational implicit-solvent model (VISM) with the Coulomb field approximation (CFA) to locate and characterize potential proteinsmall-molecule binding sites. We applied our method to a data set of 515 proteinligand complexes and found that 96.9% of the cocrystallized ligands bind to the VISM-CFA-identified pockets and that 71.8% of the identified pockets are occupied by cocrystallized ligands. For 228 tight-binding proteinligand complexes (i.e, complexes with experimental pK(d) values larger than 6), 99.1% of the cocrystallized ligands are in the VISM-CFA-identified pockets. In addition, it was found that the ligand binding orientations are consistent with the hydrophilic and hydrophobic descriptions provided by VISM. Quantitative characterization of binding pockets with topological and physicochemical parameters was used to assess the ligandability of the pockets. The results illustrate the key interactions between ligands and receptors and can be very informative for rational drug design.
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