Advances in In-silico B-cell Epitope Prediction

被引:29
|
作者
Sun, Pingping [1 ,2 ,3 ]
Gu, Sijia [1 ,2 ,3 ]
Su, Jiahang [1 ,2 ,3 ]
Tan, Liming [1 ,2 ,3 ]
Liu, Chang [1 ,2 ,3 ]
Ma, Zhiqiang [1 ,2 ,3 ]
机构
[1] Northeast Normal Univ, Sch Informat Sci & Technol, Changchun 130117, Jilin, Peoples R China
[2] Northeast Normal Univ, Key Lab Intelligent Informat Proc Jilin Univ, Changchun 130117, Jilin, Peoples R China
[3] Northeast Normal Univ, Inst Computat Biol, Changchun 130117, Jilin, Peoples R China
基金
国家重点研发计划;
关键词
Epitope prediction; Linear epitope; Conformational epitope; BCR; B-cell; Epitope; AMINO-ACID-COMPOSITION; ANTIGENIC DETERMINANTS; CONFORMATIONAL EPITOPES; SPATIAL EPITOPE; LINEAR EPITOPES; PEPTIDE; LOCATION; PROTEINS; MIMOTOPE; ANTIBODY;
D O I
10.2174/1568026619666181130111827
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Identification of B-cell epitopes in target antigens is one of the most crucial steps for epitope-based vaccine development, immunodiagnostic tests, antibody production, and disease diagnosis and therapy. Experimental methods for B-cell epitope mapping are time consuming, costly and labor intensive; in the meantime, various in-silico methods are proposed to predict both linear and conformational B-cell epitopes. The accurate identification of B-cell epitopes presents major challenges for immunoinformaticians. In this paper, we have comprehensively reviewed in-silico methods for B-cell epitope identification. The aim of this review is to stimulate the development of better tools which could improve the identification of B-cell epitopes, and further for the development of therapeutic antibodies and diagnostic tools.
引用
收藏
页码:105 / 115
页数:11
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