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

机译:从头开始使用配对电位和遗传算法设计蛋白质。

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摘要

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.
机译: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3维结构。有了这些知识,也许最令人振奋的前景将是设计新蛋白质来执行指定任务的可能性,这一应用可能在医学和生物技术中被证明非常重要。无需全面了解蛋白质折叠过程即可实现有效的蛋白质设计。在本文中,描述了一种简单的方法,用于设计适合给定3维结构的氨基酸序列。通过一系列统计确定的电位(包括残基间成对和溶剂化术语)评估设计序列与给定折叠的相容性,这些电位先前已应用于蛋白质折叠识别问题。为了产生最适合折叠的序列,使用了遗传算法,从而通过以自然选择方式进行随机搜索来优化序列。

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