Department of Chemistry, The University of Chicago, Chicago, Illinois 60637, USA.
J Phys Chem B. 2010 May 27;114(20):6979-89. doi: 10.1021/jp101476g.
Simulations are important for understanding complex reactions, but their interpretation is challenging owing to the large number of degrees of freedom typically involved. To address this issue, various means for relating the dynamics of a stochastic system to its structural and energetic features have been introduced. Here, we show how two leading approaches can be combined to advantage. We use the network of transitions observed in a reversible folding/unfolding simulation of a 20-residue three-stranded antiparallel beta-sheet peptide (beta3s) to estimate the probabilities of committing to stable states (the native state and major nonnative states), and these then serve as the basis for an efficient statistical procedure for identifying physical variables that describe the dynamics. We find that a single coordinate that jointly characterizes the formation of the two native turns of beta3s can adequately describe the overall folding process, despite its complex nature. Additional features associated with major pathways leading from individual nonnative states are resolved; indeed, a key result is an improved understanding of the unfolded state. Connections to other methods for analyzing complex reactions are discussed.
模拟对于理解复杂反应非常重要,但由于通常涉及大量自由度,因此其解释具有挑战性。为了解决这个问题,已经引入了各种将随机系统的动力学与其结构和能量特征联系起来的方法。在这里,我们展示了如何将两种领先的方法结合起来以发挥优势。我们使用在对 20 残基三股反平行 β-折叠肽 (β3s) 的可逆折叠/去折叠模拟中观察到的转换网络来估计稳定状态(天然状态和主要非天然状态)的概率,然后这些概率作为有效统计程序的基础,用于识别描述动力学的物理变量。我们发现,一个共同描述两个天然β3s 转角形成的坐标可以充分描述整个折叠过程,尽管其性质复杂。与从单个非天然状态出发的主要途径相关的其他特征也得到了解析;事实上,一个关键的结果是对未折叠状态有了更好的理解。还讨论了与分析复杂反应的其他方法的联系。