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Amino Acids Pattern-Biased Spiral Search for Protein Structure Prediction

机译:氨基酸模式偏向螺旋搜索用于蛋白质结构预测

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Proteins are essentially sequences of amino acids. They adopt specific folded 3-dimensional structures to perform specific tasks. The formation of 3-dimensional structures is largely guided by the constituent amino acids. Therefore, the positional presence of amino acids in a sequence might play important roles during the protein folding process. In this paper, we present a new heuristic derived from the positional patterns of amino acids in a sequence. With the help of a biased tabu tenure, we apply this heuristic within a spiral search algorithm. The spiral search is an efficient algorithm to develop hydrophobic core in a protein structure pulling hydrophobic amino acids towards the core centre in a spiral fashion. On a set of standard benchmark proteins, we experimentally show that applying our new heuristic improves the performance of a spiral search algorithm consistently.
机译:蛋白质本质上是氨基酸序列。他们采用特定的折叠3维结构来执行特定任务。 3维结构的形成主要由组成氨基酸指导。因此,序列中氨基酸的位置可能在蛋白质折叠过程中起重要作用。在本文中,我们提出了一种新的启发式方法,该方法源自序列中氨基酸的位置模式。借助有偏见的禁忌权,我们在螺旋搜索算法中应用了这种启发式方法。螺旋搜索是一种有效的算法,可以开发蛋白质结构中的疏水核心,将疏水氨基酸以螺旋方式拉向核心中心。在一组标准基准蛋白质上,我们实验证明了应用新的启发式方法可以持续改善螺旋搜索算法的性能。

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