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病毒蛋白定位预测工具(Virus-PLoc):一种用于预测病毒蛋白在宿主细胞和病毒感染细胞内亚细胞定位的融合分类器。

Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells.

作者信息

Shen Hong-Bin, Chou Kuo-Chen

机构信息

Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, 1954 Hua-Shan Road, Shanghai 200030, China.

出版信息

Biopolymers. 2007 Feb 15;85(3):233-40. doi: 10.1002/bip.20640.

Abstract

Viruses can reproduce their progenies only within a host cell, and their actions depend both on its destructive tendencies toward a specific host cell and on environmental conditions. Therefore, knowledge of the subcellular localization of viral proteins in a host cell or virus-infected cell is very useful for in-depth studying of their functions and mechanisms as well as designing antiviral drugs. An analysis on the Swiss-Prot database (version 50.0, released on May 30, 2006) indicates that only 23.5% of viral protein entries are annotated for their subcellular locations in this regard. As for the gene ontology database, the corresponding percentage is 23.8%. Such a gap calls for the development of high throughput tools for timely annotating the localization of viral proteins within host and virus-infected cells. In this article, a predictor called "Virus-PLoc" has been developed that is featured by fusing many basic classifiers with each engineered according to the K-nearest neighbor rule. The overall jackknife success rate obtained by Virus-PLoc in identifying the subcellular compartments of viral proteins was 80% for a benchmark dataset in which none of proteins has more than 25% sequence identity to any other in a same location site. Virus-PLoc will be freely available as a web-server at http://202.120.37.186/bioinf/virus for the public usage. Furthermore, Virus-PLoc has been used to provide large-scale predictions of all viral protein entries in Swiss-Prot database that do not have subcellular location annotations or are annotated as being uncertain. The results thus obtained have been deposited in a downloadable file prepared with Microsoft Excel and named "Tab_Virus-PLoc.xls." This file is available at the same website and will be updated twice a year to include the new entries of viral proteins and reflect the continuous development of Virus-PLoc.

摘要

病毒只能在宿主细胞内繁殖后代,其作用既取决于对特定宿主细胞的破坏倾向,也取决于环境条件。因此,了解病毒蛋白在宿主细胞或病毒感染细胞中的亚细胞定位,对于深入研究其功能和机制以及设计抗病毒药物非常有用。对瑞士蛋白质数据库(2006年5月30日发布的第50.0版)的分析表明,在这方面只有23.5%的病毒蛋白条目标注了亚细胞定位。至于基因本体数据库,相应的百分比为23.8%。这种差距需要开发高通量工具,以便及时标注病毒蛋白在宿主细胞和病毒感染细胞内的定位。在本文中,开发了一种名为“Virus-PLoc”的预测工具,其特点是融合了许多基本分类器,每个分类器都根据K近邻规则进行设计。对于一个基准数据集,Virus-PLoc在识别病毒蛋白亚细胞区室方面获得的总体留一法成功率为80%,在该数据集中,同一位置的蛋白质之间的序列同一性均不超过25%。Virus-PLoc将作为一个网络服务器免费提供,网址为http://202.120.37.186/bioinf/virus,供公众使用。此外,Virus-PLoc已被用于对瑞士蛋白质数据库中所有没有亚细胞定位注释或注释不确定的病毒蛋白条目进行大规模预测。由此获得的结果已存入一个用Microsoft Excel编制的可下载文件中,名为“Tab_Virus-PLoc.xls”。该文件可在同一网站获取,并将每年更新两次,以纳入病毒蛋白的新条目,并反映Virus-PLoc的持续发展。

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