期刊
NATURE COMMUNICATIONS
卷 6, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms8283
关键词
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资金
- Center for Molecular Analysis and Design (CMAD) at Stanford University
- Simbios, NIH Center for Biomedical Computation [GM072970]
- NIH [R01GM62828]
- Biomedical Data Science Initiative Fellowship from Stanford University School of Medicine
Recent successes in simulating protein structure and folding dynamics have demonstrated the power of molecular dynamics to predict the long timescale behaviour of proteins. Here, we extend and improve these methods to predict molecular switches that characterize conformational change pathways between the active and inactive state of nitrogen regulatory protein C (NtrC). By employing unbiased Markov state model-based molecular dynamics simulations, we construct a dynamic picture of the activation pathways of this key bacterial signalling protein that is consistent with experimental observations and predicts new mutants that could be used for validation of the mechanism. Moreover, these results suggest a novel mechanistic paradigm for conformational switching.
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