期刊
ANNUAL REVIEW OF PHYSICAL CHEMISTRY, VOL 64
卷 64, 期 -, 页码 295-316出版社
ANNUAL REVIEWS
DOI: 10.1146/annurev-physchem-040412-110006
关键词
path sampling; reaction rate; machine learning; molecular dynamics
资金
- Division Of Chemistry [0835824] Funding Source: National Science Foundation
The long-timescale dynamics of macromolecular systems can be oftentimes viewed as a reaction connecting metastable states of the system. In the past decade, various approaches have been developed to discover the collective motions associated with this dynamics. The corresponding collective variables are used in many applications, e.g., to understand the reaction mechanism, to quantify the system's free energy landscape, to enhance the sampling of the reaction path, and to determine the reaction rate. In this review we focus on a number of key developments in this field, providing an overview of several methods along with their relative regimes of applicability.
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