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TAPPred对抗原中TAP结合肽的预测

TAPPred prediction of TAP-binding peptides in antigens.

作者信息

Bhasin Manoj, Lata Sneh, Raghava G P S

机构信息

Institute of Microbial Technology, Chandigarh, India.

出版信息

Methods Mol Biol. 2007;409:381-6. doi: 10.1007/978-1-60327-118-9_28.

Abstract

The transporter associated with antigen processing (TAP) plays a crucial role in the transport of the peptide fragments of the proteolysed antigenic or self-altered proteins to the endoplasmic reticulum where the association between these peptides and the major histocompatibility complex (MHC) class I molecules takes place. Therefore, prediction of TAP-binding peptides is highly helpful in identifying the MHC class I-restricted T-cell epitopes and hence in the subunit vaccine designing. In this chapter, we describe a support vector machine (SVM)-based method TAPPred that allows users to predict TAP-binding affinity of peptides over web. The server allows user to predict TAP binders using a simple SVM model or cascade SVM model. The server also allows user to customize the display/output. It is freely available for academicians and noncommercial organization at the address http://www.imtech.res.in/raghava/tappred.

摘要

与抗原加工相关的转运体(TAP)在将经蛋白酶水解的抗原性或自身改变的蛋白质的肽片段转运至内质网的过程中起着关键作用,在该内质网中,这些肽与主要组织相容性复合体(MHC)I类分子之间会发生结合。因此,预测TAP结合肽对于识别MHC I类限制性T细胞表位以及进而在亚单位疫苗设计中非常有帮助。在本章中,我们描述了一种基于支持向量机(SVM)的方法TAPPred,它允许用户通过网络预测肽的TAP结合亲和力。该服务器允许用户使用简单的SVM模型或级联SVM模型来预测TAP结合剂。该服务器还允许用户定制显示/输出。它可供学者和非商业组织免费使用,网址为http://www.imtech.res.in/raghava/tappred

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