期刊
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 11, 期 3, 页码 1094-1101出版社
AMER CHEMICAL SOC
DOI: 10.1021/ct5010017
关键词
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资金
- Biomedical Data Science Initiative Fellowship from Stanford School of Medicine
- SIMBIOS NIH National Center for Biomedical Computation through the NIH Roadmap for Medical Research [U54 GM07297]
- [NSF-MCB-0954714]
- [NIH-R01-GM062868]
Molecular dynamics with explicit solvent is favored for its ability to more correctly simulate aqueous biological processes and has become routine thanks to increasingly powerful computational resources. However, analysis techniques including Markov state models (MSMs) ignore solvent atoms and focus solely on solute coordinates despite solvent being implicated in myriad biological phenomena. We present a unified framework called solvent-shells featurization for including solvent degrees of freedom in analysis and show that this method produces better models. We apply this method to simulations of dewetting in the two-domain protein BphC to generate a predictive MSM and identify functional water molecules. Furthermore, the proposed methodology could be easily extended for building MSMs of any systems with indistinguishable components.
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