化学学报 ›› 2013, Vol. 71 ›› Issue (04): 670-678.DOI: 10.6023/A12121059 上一篇    

研究论文

基于ISC-SVR方法预测Th细胞表位

于畅宇, 刘伟, 刘涛, 宋哲, 朱鸣华   

  1. 大连理工大学高科技研究院 大连 116023
  • 投稿日期:2012-12-17 发布日期:2013-01-31
  • 通讯作者: 刘伟 E-mail:jchjys@dlut.edu.cn

Prediction of Th Cell Epitopes Based on ISC-SVR Method

Yu Changyu, Liu Wei, Liu Tao, Song Zhe, Zhu Minghua   

  1. College of Advanced Science and Technology, Dalian University of Technology, Dalian 116023
  • Received:2012-12-17 Published:2013-01-31

外源性抗原蛋白被抗原提呈细胞(APC)摄取送入溶酶体中被降解为长度不一的肽段. 在HLA-DM分子辅助下, MHC II类分子相关恒定链多肽(class II-associated invariant chain peptide, CLIP)从MHC II类分子的肽结合槽解离, 使得外源性抗原降解的肽段进入MHC II类分子空的肽结合槽中, 形成稳定的抗原肽-MHC II类分子复合物. 之后再被提呈到APC细胞表面供CD4+Th细胞的TCR识别, 激活Th细胞分泌细胞因子, 促进CTL细胞特异性杀伤靶细胞或辅助B细胞产生抗体. Th细胞的活化对机体的细胞免疫和体液免疫功能都有重要的辅助作用. 本工作基于迭代自洽策略与支持向量回归机(ISC-SVR)方法建立了MHC II类分子与外源性抗原肽结合亲合力预测模型, 采用13mer扩展核心结合序列可以提高预测模型的性能, 分别按照均值法、最大值法、结合法、加权平均值法4种方法计算MHC II类分子与抗原肽的结合亲合力值. 对17种MHC II类分子配型进行了回归分析, 与其他预测模型相比较, 本工作模型都得到了最佳AUC值. 最后, 以HLA DRB1*0101分子为例, 分析讨论了MHC II类分子与抗原肽的结合特异性.

关键词: T细胞, 表位, 外源性抗原, MHC II类分子, 支持向量回归机

Exogenous antigen proteins are absorbed by antigen presenting cells (APC) and translated into lysosome in which they are degraded into short peptides with different length. A fragment called class II-associated invariant chain peptide (CLIP) lodges in the peptide-binding groove after the Ii chain is progressively degraded by lysosomal proteases. With the help of HLA-DM molecule, CLIP is removed from the binding groove of MHC class II molecule, which makes the degraded peptides enter into the empty binding groove to form steady peptide-MHC class II complexes. The peptide-MHC class II complexes are ultimately trafficked to the cell surface to be recognized by CD4+T cell surface receptor (TCR). This process can activate Th cells to secrete cell factors that promote CTL cells to kill target cells specifically or assist B cells to make antibody against bacteria. Activation of Th cells has important supplementary effect on the cellular immunity and humoral immunity function. In this paper, the support vector regression method combined with iterative self-consistent strategy (ISC-SVR) were used to build the models to predict affinities of exogenous antigen peptides binding to MHC class II molecules. In order to improve the predictive performance, the predictive models were based on 13mer extended core binding sequence rather than traditional 9mer core binding sequence. We computed the affinity of MHC class II molecule binding to peptide with four methods, which were the mean method, the max method, the combine method and the eave method respectively. The predictive performance of the ISC-SVR model is validated on data sets of 17 MHC class II alleles. The results show that the model has certain rationality and accuracy in T cell epitopes prediction. Compared to other predictive models with the same data set, the predictive performance of our model is more satisfying. For each MHC class II allele, the ISC-SVR model got the best AUC value which was used to measure the predictive performance. Furthermore, for HLA DRB1*0101 molecule, we obtained the specificities of MHC class II molecule binding to peptides which were consistent with previous experimental results.

Key words: T cell, epitope, exogenous antigen, MHC class II molecule, support vector regression