利用插入/删除频率阵列改进蛋白质序列结构比对。

Kyle Ellrott, Jun-tao Guo, Victor Olman, Ying Xu
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引用次数: 0

摘要

随着蛋白质的进化,并不是氨基酸序列的每个部分都有相同的被删除或允许插入的概率,因为不是每个氨基酸在维持蛋白质结构方面都起着同样重要的作用。然而,在折叠识别方法中最流行的模型将每个氨基酸缺失和插入视为等概率事件。我们分析了同源和类似序列的比对模式,以确定插入和缺失的模式,并使用该信息来确定目标序列中不同氨基酸的插入和缺失统计。我们将这些模式定义为插入/删除(Indel)频率阵列(IFA)。通过将IFA应用于蛋白质穿线问题,我们能够提高比对精度,特别是对序列同源性较低的蛋白质。
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Improvement in protein sequence-structure alignment using insertion/deletion frequency arrays.

As a protein evolves, not every part of the amino acid sequence has an equal probability of being deleted or for allowing insertions, because not every amino acid plays an equally important role in maintaining the protein structure. However the most prevalent models in fold recognition methods treat every amino acid deletion and insertion as equally probable events. We have analyzed the alignment patterns for homologous and analogous sequences to determine patterns of insertion and deletions, and used that information to determine the statistics of insertions and deletions for different amino acids of a target sequence. We define these patterns as Insertion/Deletion (Indel) Frequency Arrays (IFA). By applying IFA to the protein threading problem, we have been able to improve the alignment accuracy, especially for proteins with low sequence identity.

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