基于Fast ICA方法预测Th细胞表位
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摘要
适应性免疫应答(adaptive immune response)是指T和B淋巴细胞因对抗原的特异性识别而活化、增殖、分化,最终形成效应细胞,并通过其所分泌的抗体或细胞因子表现出一定生物学效应的过程。
     T细胞表位(epitope)能够激活T细胞的免疫应答,在适应性免疫应答中发挥重要的作用。而T细胞对其的识别具有MHC限制性,并且根据参与的MHC分子的不同分为MHCI类途径和MHCⅡ类途径。
     在MHCⅡ类途径中,MHCⅡ类分子只能与特定的抗原肽结合,为了研究抗原肽和MHCⅡ类分子的结合特异性,本文采用交叉验证与固定点迭代算法相结合的方法(CV-FastICA),分别建立了三种基于13-mer扩展核心结合序列的MHCⅡ类配体的定量构效关系(quantitative structure-activity relationship, QSAR)模型,并与基于9-mer核心结合序列的模型进行了比较。通过比较各个模型预测性能,可知建立模型时需要考虑核心结合序列两侧的扩展位置上氨基酸的影响。另外,本文以HLADRBl*0101为例,分析了抗原肽的不同位置氨基酸对MHCⅡ类分子的结合特异性,所得结果与实验结果基本一致。
     首先,通过理论模型来预测候选Th表位,再利用相应的生物实验加以验证,可以减少实验成本,提高鉴定效率。本文使用CV-Fast ICA方法建立MHCⅡ类分子与抗原肽相互作用结合的QSAR模型,对了解免疫机理和指导表位疫苗的开发具有一定的指导意义。
Adaptive immune response means the process of T and B lymphocytes due to the specificity of the recognition of antigen, activation and proliferation and differentiation, finally form effect cells, and through the secretions of the antibody or cell factors show some biological effects.
     T cell epitopes could activate immune response of T cell, and play an important role in adaptive immune response. And the identification of T cell with MHC restrictive. There are two antigen presentations, the MHC I antigen processing and presentation pathway and the MHC II antigen processing and presentation pathway.
     In the MHC class II antigen processing and presentation pathway, only certain peptides could bind to MHC class II molecule. In order to study the binding specificities between peptide and MHC class II molecule, we through CV-Fast ICA method built three QSAR models of MHC class Ⅱ ligand based on13-mer extended core binding sequence and compared with the models of MHC class Ⅱ ligand based on9-mer core binding sequence. Through compared among the predictive performance of models, it is known that the adjacent positions of core binding sequence need to be considered. In addition, to HLA DRB0*0101as an example, the specificities of MHC class Ⅱ molecule binding antigen peptide were analyzed. And the specificities agree with the experiment results.
     Theoretical models to predict the candidate Th cell epitopes, then verified through biological experiment can reduce the experimental cost and improve the efficiency of Th cell epitopes identified. The method in this paper helps in further understanding the interaction between MHC class Ⅱ molecules and antigenic peptides. And it can also be instructs the designing and developing of the epitope vaccine.
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