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利用成对势和遗传算法进行从头蛋白质设计。

De novo protein design using pairwise potentials and a genetic algorithm.

作者信息

Jones D T

机构信息

Department of Biochemistry and Molecular Biology, University College, London United Kingdom.

出版信息

Protein Sci. 1994 Apr;3(4):567-74. doi: 10.1002/pro.5560030405.

Abstract

One of the major goals of molecular biology is to understand how protein chains fold into a unique 3-dimensional structure. Given this knowledge, perhaps the most exciting prospect will be the possibility of designing new proteins to perform designated tasks, an application that could prove to be of great importance in medicine and biotechnology. It is possible that effective protein design may be achieved without the requirement for a full understanding of the protein folding process. In this paper a simple method is described for designing an amino acid sequence to fit a given 3-dimensional structure. The compatibility of a designed sequence with a given fold is assessed by means of a set of statistically determined potentials (including interresidue pairwise and solvation terms), which have been previously applied to the problem of protein fold recognition. In order to generate sequences that best fit the fold, a genetic algorithm is used, whereby the sequence is optimized by a stochastic search in the style of natural selection.

摘要

分子生物学的主要目标之一是了解蛋白质链如何折叠成独特的三维结构。有了这方面的知识,或许最令人兴奋的前景将是设计新蛋白质以执行特定任务的可能性,这一应用在医学和生物技术领域可能会被证明具有极其重要的意义。有可能在不完全理解蛋白质折叠过程的情况下实现有效的蛋白质设计。本文描述了一种简单的方法,用于设计适合给定三维结构的氨基酸序列。通过一组统计确定的势能(包括残基间成对相互作用和溶剂化项)来评估设计序列与给定折叠结构的兼容性,这些势能先前已应用于蛋白质折叠识别问题。为了生成最适合该折叠结构的序列,使用了遗传算法,通过自然选择风格的随机搜索对序列进行优化。

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