Collective variables for the study of long-time kinetics from molecular trajectories: theory and methods

被引:111
|
作者
Noe, Frank [1 ]
Clementi, Cecilia [2 ,3 ]
机构
[1] FU Berlin, Dept Math & Comp Sci, Arnimallee 6, D-14195 Berlin, Germany
[2] Rice Univ, Ctr Theoret Biol Phys, 6100 Main St, Houston, TX 77005 USA
[3] Rice Univ, Dept Chem, 6100 Main St, Houston, TX 77005 USA
基金
欧洲研究理事会; 美国国家科学基金会;
关键词
VARIATIONAL APPROACH; DYNAMICS; DEFINITION; VALIDATION; REVEAL;
D O I
10.1016/j.sbi.2017.02.006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Collective variables are an important concept to study high-dimensional dynamical systems, such as molecular dynamics of macromolecules, liquids, or polymers, in particular to define relevant metastable states and state-transition or phase-transition. Over the past decade, a rigorous mathematical theory has been formulated to define optimal collective variables to characterize slow dynamical processes. Here we review recent developments, including a variational principle to find optimal approximations to slow collective variables from simulation data, and algorithms such as the time-lagged independent component analysis. Using these concepts, a distance metric can be defined that quantifies how slowly molecular conformations interconvert. Extensions and open questions are discussed.
引用
收藏
页码:141 / 147
页数:7
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