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寡聚预测:一个通过将离散小波变换纳入周的伪氨基酸组成来预测同源寡聚蛋白的网络服务器。

OligoPred: a web-server for predicting homo-oligomeric proteins by incorporating discrete wavelet transform into Chou's pseudo amino acid composition.

机构信息

Department of Chemistry, Nanchang University, Nanchang 330031, China.

出版信息

J Mol Graph Model. 2011 Sep;30:129-34. doi: 10.1016/j.jmgm.2011.06.014. Epub 2011 Jul 7.

Abstract

In vivo, some proteins exist as monomers (single polypeptide chains) and others as oligomers. Not like monomers, oligomers are composed of two or more chains (subunits) that are associated with each other through non-covalent interactions and, occasionally, through disulfide bonds. These proteins are the structural components of various biological functions, including cooperative effects, allosteric mechanisms and ion-channel gating. However, with the dramatic increase in the number of protein sequences submitted to the public data bank, it is important for both basic research and drug discovery research to acquire the possible knowledge about homo-oligomeric attributes of their interested proteins in a timely manner. In this paper, a high-throughput method, combined support vector machines with discrete wavelet transform, has been developed to predict the protein homo-oligomers. The total accuracy obtained by the re-substitution test, jackknife test and independent dataset test are 99.94%, 96.17% and 96.18%, respectively, showing that the proposed method of extracting feature from the protein sequences is effective and feasible for predicting homo-oligomers. The online service is available at http://bioinfo.ncu.edu.cn/Services.aspx.

摘要

在体内,一些蛋白质以单体(单条多肽链)存在,而另一些则以寡聚体形式存在。与单体不同,寡聚体由两条或更多条通过非共价相互作用(偶尔通过二硫键)彼此关联的链(亚基)组成。这些蛋白质是各种生物功能的结构组成部分,包括协同效应、变构机制和离子通道门控。然而,随着提交给公共数据库的蛋白质序列数量的急剧增加,及时获取有关其感兴趣蛋白质的同源寡聚属性的可能知识,对于基础研究和药物发现研究都非常重要。在本文中,我们开发了一种高通量方法,将支持向量机与离散小波变换相结合,用于预测蛋白质同源寡聚体。重新替换测试、刀切测试和独立数据集测试的总准确率分别为 99.94%、96.17%和 96.18%,表明从蛋白质序列中提取特征的方法对于预测同源寡聚体是有效且可行的。在线服务可在 http://bioinfo.ncu.edu.cn/Services.aspx 获得。

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