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Identification of related proteins with weak sequence identity using secondary structure information

机译:使用二级结构信息鉴定弱序列同一性的相关蛋白质

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摘要

Molecular modeling of proteins is confronted with the problem of finding homologous proteins, especially when few identities remain after the process of molecular evolution. Using even the most recent methods based on sequence identity detection, structural relationships are still difficult to establish with high reliability. As protein structures are more conserved than sequences, we investigated the possibility of using protein secondary structure comparison (observed or predicted structures) to discriminate between related and unrelated proteins sequences in the range of 10%–30% sequence identity. Pairwise comparison of secondary structures have been measured using the structural overlap (Sov) parameter. In this article, we show that if the secondary structures likeness is >50%, most of the pairs are structurally related. Taking into account the secondary structures of proteins that have been detected by BLAST, FASTA, or SSEARCH in the noisy region (with high E value), we show that distantly related protein sequences (even with <20% identity) can be still identified. This strategy can be used to identify three-dimensional templates in homology modeling by finding unexpected related proteins and to select proteins for experimental investigation in a structural genomic approach, as well as for genome annotation.
机译:蛋白质的分子建模面临着寻找同源蛋白质的问题,尤其是在分子进化过程中几乎没有身份的情况下。即使使用基于序列同一性检测的最新方法,仍然很难以高可靠性建立结构关系。由于蛋白质结构比序列更保守,我们研究了使用蛋白质二级结构比较(观察或预测的结构)在10%至30%序列同一性范围内区分相关和不相关蛋白质序列的可能性。已使用结构重叠(Sov)参数测量了二级结构的成对比较。在本文中,我们表明,如果二级结构相似度> 50%,则大多数配对在结构上相关。考虑到BLAST,FASTA或SSEARCH在嘈杂区域(具有高E值)检测到的蛋白质的二级结构,我们表明仍可以识别远距离相关的蛋白质序列(即使具有<20%的同一性)。该策略可用于通过发现意外的相关蛋白质来鉴定同源性建模中的三维模板,并选择蛋白质用于结构基因组方法的实验研究以及用于基因组注释。

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