换一批摘要Molecular kinetics underlies all biological phenomena and, like many other biological processes, may best be understood in terms of networks. These networks, called Markov state models (MSMs), are typically built from physical simulations. Thus, they are capable of quantitative prediction of experiments and can also provide an intuition for complex conformational changes. Their primary application has been to protein folding; however, these technologies and the insights they yield are transferable. For example, MSMs have already proved useful in understanding human diseases, such as protein misfolding and aggregation in Alzheimer's disease.
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关键词
Markov state modelsmolecular dynamicssimulationsprotein foldingconformational changeAlzheimer's disease
分类号
Q2（细胞生物学）
栏目名称
DOI
10.1038/cr.2010.57
发布时间
2010-07-12（万方平台首次上网日期，不代表论文的发表时间）
基金项目
the NSF GRFP（(NIH R01-GM062868;NIH U54 GM072970;;NSF EF-0623664)）
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