期刊
JOURNAL OF CHEMICAL INFORMATION AND MODELING
卷 59, 期 9, 页码 3794-3802出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jcim.9b00362
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资金
- NIH [P41-GM104601]
- Office of Science, U.S. Department of Energy [DE-AC02-06CH11357]
- National Science Foundation (NSF) [MCB517221]
- France and Chicago Collaborating in The Sciences (FACCTS) program
- Office of Science of the U.S. Department of Energy [DE-AC02-06CH11357]
An effective hybrid single-dual-topology protocol is designed for the calculation of relative binding affinities of small ligands to a receptor. The protocol was developed as an extension of the NAMD molecular dynamics program, which exclusively supports a dual-topology framework for relative alchemical free-energy perturbation (FEP) calculations. In this protocol, the alchemical end states are represented as two separate molecules sharing a common substructure identified through maximum structural mapping. Within the substructure, an atom-to-atom correspondence is established, and each pair of corresponding atoms is holonomically constrained to share identical coordinates at all time throughout the simulation. The forces are projected and combined at each step for propagation. Following this formulation, a set of illustrative calculations of reliable experiment/simulation data, including relative solvation free energies of small molecules and relative binding affinities of drug compounds to proteins, are presented. To enhance sampling of the dual-topology region, the FEP calculations were carried out within a replica-exchange MD scheme supported by the multiple-copy algorithm module of NAMD, with periodically attempted swapping of the thermodynamic coupling parameter lambda between neighboring states. The results are consistent with experiments and benchmarks reported in the literature, lending support to the validity of the current protocol. In summary, this hybrid single-dual-topology approach combines the conceptual simplicity of the dual-topology paradigm with the advantageous sampling efficiency of the single-topology approach, making it an ideal strategy for high-throughput in silico drug design.
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