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用于蛋白质折叠的新型蒙特卡罗算法。

New Monte Carlo algorithms for protein folding.

作者信息

Hansmann U H, Okamoto Y

机构信息

Department of Physics Michigan Technological University, Houghton, MI 49931-1295, USA.

出版信息

Curr Opin Struct Biol. 1999 Apr;9(2):177-83. doi: 10.1016/S0959-440X(99)80025-6.

Abstract

Over the past three decades, a number of powerful simulation algorithms have been introduced to the protein folding problem. For many years, the emphasis has been placed on how to both overcome the multiple minima problem and find the conformation with the global minimum potential energy. Since the new view of the protein folding mechanism (based on the free energy landscape of the protein system) arose in the past few years, however, it is now of interest to obtain a global knowledge of the phase space, including the intermediate and denatured states of proteins. Monte Carlo methods have proved especially valuable for these purposes. As well as new, powerful optimization techniques, novel algorithms that can sample much a wider phase space than conventional methods have been established.

摘要

在过去三十年里,人们针对蛋白质折叠问题引入了许多强大的模拟算法。多年来,重点一直放在如何克服多重极小值问题以及找到具有全局最小势能的构象上。然而,自从蛋白质折叠机制的新观点(基于蛋白质系统的自由能景观)在过去几年出现以来,现在人们感兴趣的是获得相空间的全局知识,包括蛋白质的中间态和变性态。事实证明,蒙特卡罗方法对于这些目的特别有价值。除了新的强大优化技术外,还建立了能够比传统方法采样更广泛相空间的新颖算法。

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