期刊
NATURE CHEMISTRY
卷 6, 期 1, 页码 15-21出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/NCHEM.1821
关键词
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资金
- Google Inc.
- Simbios NIH National Center on Biocomputing through the NIH Roadmap for Medical Research Grant [U54 GM07297]
- Stanford School of Medicine Dean's Fellowship
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [U54GM072970] Funding Source: NIH RePORTER
- NATIONAL LIBRARY OF MEDICINE [R01LM005652] Funding Source: NIH RePORTER
Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro-to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor beta(2)AR. Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.
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