title: Quantitative prediction of class I MHC/epitope binding affinity using QSAR modeling derived from amino acid structural information.
abstract: The activation of T cell immune responses, which relies on peptide antigens transported by TAP and bound to major histocompatibility complex (MHC) molecules, is recognized by T cell receptors (TCR). The quantitative prediction of MHC-epitope binding affinity can facilitate epitope screening and reduce cost and experimental efforts greatly. In this study, a comprehensive quantitative prediction method of binding affinity was established using quantitative structureactivity relationship (QSAR) modeling derived from amino acid physicochemical information. Firstly, the epitope was characterized by a set of amino acid physicochemical parameters. Secondly, the structural variables were optimized by the stepwise regression (STR). Finally, the robust quantitative models with were built by multiple linear regressions (MLR) for 31 MHC Class I subtypes. The normalized regression coefficients (NRCs) of QSAR model could demonstrate the mechanism of interaction of MHC, epitope, and TCR very well. The contribution of amino acid at each position of epitope, which was calculated by NRC, could determine which one was favorable for binding affinity or not. Therefore, the quantitative models established by STR-MLR could be used to guide virtual combinational design and high throughout screening of CTL epitope. Besides, they have many advantages, such as definite physiochemical indication, easier calculation and explanation, and good performances.
authors.forename: Yuanqiang
authors.initials: Y
authors.lastname: Wang
authors.forename: Pengpeng
authors.initials: P
authors.lastname: Zhou
authors.forename: Yong
authors.initials: Y
authors.lastname: Lin
authors.forename: Mao
authors.initials: M
authors.lastname: Shu
authors.forename: Yong
authors.initials: Y
authors.lastname: Hu
authors.forename: Qingyou
authors.initials: Q
authors.lastname: Xia
authors.affiliation: (Qingyou Xia) State Key Laboratory of Silkworm Genome Biology, Southwest University, Chongqing, 400715, P.R. China. xiaqy@swu.edu.cn.
authors.forename: Zhihua
authors.initials: Z
authors.lastname: Lin
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry / Q000276:immunology; D000939:Epitopes / Q000737:chemistry* / Q000276:immunology*; D015395:Histocompatibility Antigens Class I / Q000737:chemistry* / Q000276:immunology*; D006801:Humans; D018448:Models, Immunological; D008958:Models, Molecular; D021281:Quantitative Structure-Activity Relationship; D011948:Receptors, Antigen, T-Cell / Q000737:chemistry / Q000276:immunology*
chemical_list: D000596:Amino Acids; D000939:Epitopes; D015395:Histocompatibility Antigens Class I; D011948:Receptors, Antigen, T-Cell