Enhanced sampling algorithms.
Enhanced sampling algorithms.
复制标题
增强的采样算法。
作者：
A. Mitsutake;Yoshiharu Mori;Y. Okamoto
在具有多个自由度的生物分子系统（特别是全原子模型）中，例如蛋白质和核酸，存在数量惊人的局部最小能量态。规范系综中的传统模拟几乎没有什么用处，因为它们往往会陷入这些能量局部最小值的状态。因此，增强构象采样技术的需求量很大。广义系综中的模拟在势能空间中执行随机游走，可以克服这个困难。仅通过一次模拟运行，就可以通过单直方图和/或多直方图重新加权技术获得作为温度函数的物理量的规范系综平均值。在本文中，我们回顾了广义集成算法在生物分子系统中的使用。首先描述了三种著名的方法，即多规范算法、模拟回火法和副本交换法。给出了算法的蒙特卡罗和分子动力学版本。然后我们提出这三种广义集成算法的各种扩展。使用短肽和蛋白质系统测试了该方法的有效性。
In biomolecular systems (especially all-atom models) with many degrees of freedom such as proteins and nucleic acids, there exist an astronomically large number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. Enhanced conformational sampling techniques are thus in great demand. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms in biomolecular systems. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present various extensions of these three generalized-ensemble algorithms. The effectiveness of the methods is tested with short peptide and protein systems.
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影响因子：
4.4
作者：
Zhang, Cheng;Ma, Jianpeng
通讯作者：
Ma, Jianpeng
影响因子：
4.4
作者：
Shirts, Michael R.;Chodera, John D.
通讯作者：
Chodera, John D.
影响因子：
4.4
作者：
De Simone, Alfonso;Derreumaux, Philippe
通讯作者：
Derreumaux, Philippe
影响因子：
3.3
作者：
Roitberg, Adrian E.;Okur, Asim;Simmerling, Carlos
通讯作者：
Simmerling, Carlos
DOI：
10.1073/pnas.84.10.3086
发表时间：
1987-05-01
影响因子：
11.1
作者：
OOI, T;OOBATAKE, M;SCHERAGA, HA
通讯作者：
SCHERAGA, HA