Gfeller D, De Los Rios P, Caflisch A, Rao F
Laboratoire de Biophysique Statistique, SB/ITP, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Proc Natl Acad Sci U S A. 2007 Feb 6;104(6):1817-22. doi: 10.1073/pnas.0608099104. Epub 2007 Jan 31.
The kinetics of biomolecular isomerization processes, such as protein folding, is governed by a free-energy surface of high dimensionality and complexity. As an alternative to projections into one or two dimensions, the free-energy surface can be mapped into a weighted network where nodes and links are configurations and direct transitions among them, respectively. In this work, the free-energy basins and barriers of the alanine dipeptide are determined quantitatively using an algorithm to partition the network into clusters (i.e., states) according to the equilibrium transitions sampled by molecular dynamics. The network-based approach allows for the analysis of the thermodynamics and kinetics of biomolecule isomerization without reliance on arbitrarily chosen order parameters. Moreover, it is shown on low-dimensional models, which can be treated analytically, as well as for the alanine dipeptide, that the broad-tailed weight distribution observed in their networks originates from free-energy basins with mainly enthalpic character.
生物分子异构化过程的动力学,如蛋白质折叠,由高维且复杂的自由能表面所支配。作为投影到一维或二维的替代方法,自由能表面可以映射到一个加权网络中,其中节点和链接分别是构型以及它们之间的直接转变。在这项工作中,使用一种算法根据分子动力学采样的平衡转变将网络划分为簇(即状态),从而定量确定丙氨酸二肽的自由能盆地和势垒。基于网络的方法允许在不依赖任意选择的序参量的情况下分析生物分子异构化的热力学和动力学。此外,在可以进行解析处理的低维模型以及丙氨酸二肽中都表明,在它们的网络中观察到的宽尾权重分布源自主要具有焓特征的自由能盆地。