Research Of The Localization Method For Conformational B Cell Epitope

B cell epitopes are special sites where the antigen can be specifically recognized and bound by the B cell antibody,and the immune function is exerted.Its accurate localization and analysis have important research value for immune prevention.As an important component of B cell epitope formation,the conformational epitope is an important branch of B cell epitope research.With the development of computer technology,how to analyze and predict the amount of B cell data through computer technology,and improve the accuracy of B cell epitope localization has become a research hotspot in this field.Based on the research of "Application of artificial intelligence algorithm in the prediction of conformational B cell epitopes",Taking the application of artificial intelligence algorithm in predicting conformational B cell antigen epitopes as the background and the antigen-antibody complex as the research object.A conformational B cell epitope localization prediction model based on PLR_DPC algorithm is proposed in this paper to improve the accuracy of epitope localization.On this basis,a prototype system for conformational B cell epitope localization was developed.The main research contents include:(1)Data analysis and pretreatment of antigen-antibody complexes : The original information of the antigen-antibody complexes are derived from the protein database.The complex epitope information is obtained through the immune epitope database.In this paper,the structure and amino acid characteristics of conformational B cell epitopes are analyzed,and the antigenic chain surface residue data of the complexes are numerically converted according to the seven indicators of structure and amino acid characteristics.(2)PLR_DPC conformation B cell epitope localization model and comparative analysis: The PLR and DPC algorithms are mainly studied,and the two algorithms are combined to construct PLR_DPC conformational B-cell epitope localization model.The PLR algorithm is used to regress the numerical features,determine the weight value of each feature index,and construct a weighted graph.On this basis,DPC is used to divide the weighted graph into regions and locate the epitope.At the same time,the accuracy of the algorithm model is evaluated by using the verification set data,and compared with Disco Tope2.0 and PEPITO.(3)Design of conformational B cell epitope localization prototype system: A conformational B-cell epitope localization prototype system is designed and implemented by using Anaconda2,MATLAB and other tools.The functions of singlechain coordinate data extraction,prominent index calculation,accessibility area calculation and conformational epitope localization are realized.