个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:吉林大学
学位:博士
所在单位:数学科学学院
学科:基础数学
办公地点:数学科学学院525
电子邮箱:lyfdlut@dlut.edu.cn
基于TAP分子亲和力模型预测MHCⅠ类分子提呈短肽的免疫原性
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发表时间:2020-01-01
发表刊物:生物化学与生物物理进展
卷号:47
期号:2
页面范围:157-168
摘要:The major histocompatibility complex (MHC)I binding affinity models have contributed to screen the candidate peptides, and have assisted the experiments in determining the peptides that can form complexes with MHCImolecules to activate cytotoxic T cells. The transporter associated with antigen processing (TAP) binding models could also be used for screening the candidate peptides. How to make the best of the two types of binding affinity models for screening out the candidate peptides, the similarities and differences between the selectivity of TAP and MHC I molecules in peptides and the biological mechanism of that similarities and differences, these three questions remains obscure. Herein, we rearranged the TAP binding test set, increasing its size to 699. The established TAP binding model based on Kernel-function stabilized matrix method (KSMM) had a higher prediction accuracy than that of the state of the art, achieving a relevant correlation coefficient of 0.89 on a 5-fold cross-validation. The integrative prediction of HLA-A3 affinity and TAP affinity models remarkedly improved the discrimination accuracy, with the AUC value increasing from similar to 0.82 to 0.87. This improvement is due to the different preferences of the two types of affinity models for the best defined amino acids on 2nd and 9th positions, as well as to the complementarity of such different preferences. The results of TAP-peptide docking also supported this conclusion. The TAP model is available online: http://www.bilologymaths.top/mbtwo/major.aspx.
备注:新增回溯数据