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一种基于序列相似性的蛋白质二级结构测定算法。

An algorithm for secondary structure determination in proteins based on sequence similarity.

作者信息

Levin J M, Robson B, Garnier J

出版信息

FEBS Lett. 1986 Sep 15;205(2):303-8. doi: 10.1016/0014-5793(86)80917-6.

Abstract

A secondary structure prediction algorithm is proposed on the hypothesis that short homologous sequences of amino acids have the same secondary structure tendencies. Comparisons are made with the secondary structure assignments of Kabsch and Sander from X-ray data [(1983) Biopolymers 22, 2577-2637] and an empirically determined similarity matrix which assigns a sequence similarity score between any two sequences of 7 residues in length. This similarity matrix differs in many respects from that of the Dayhoff substitution matrix [(1978) in: Atlas of Protein Sequence and Structure, (Dayhoff, M.O. ed). vol. 5. suppl. 3, pp. 353-358, National Biochemical Research Foundation, Washington, DC]. This homologue method had a prediction accuracy of 62.2% over 3 states for 61 proteins and 63.6% for a new set of 7 proteins not in the original data base.

摘要

基于短氨基酸同源序列具有相同二级结构倾向的假设,提出了一种二级结构预测算法。将其与卡布斯和桑德根据X射线数据给出的二级结构分配结果[(1983年)《生物聚合物》22卷,2577 - 2637页]以及一个经验确定的相似性矩阵进行比较,该相似性矩阵可对任意两个长度为7个残基的序列给出序列相似性得分。这个相似性矩阵在许多方面与戴霍夫替换矩阵不同[(1978年)载于《蛋白质序列与结构图谱》(戴霍夫,M.O.编)第5卷,增刊3,353 - 358页,国家生物化学研究基金会,华盛顿特区]。对于61种蛋白质,这种同源物方法在三种状态下的预测准确率为62.2%,对于原始数据库中未包含的一组新的7种蛋白质,预测准确率为63.6%。

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