Recent Progress in Antibody Epitope Prediction

被引:23
作者
Zeng, Xincheng [1 ]
Bai, Ganggang [1 ]
Sun, Chuance [1 ]
Ma, Buyong [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, Engn Res Ctr Cell & Therapeut Antibody, Sch Pharm, MOE, Shanghai 200240, Peoples R China
[2] Shanghai Digiwiser Biol Inc, Shanghai 200131, Peoples R China
关键词
antibody; artificial intelligence; antibody design; epitope; B-CELL EPITOPES; CONFORMATIONAL SELECTION; BINDING-SITES; PROTEIN; SURFACE; RECOGNITION; REGIONS;
D O I
10.3390/antib12030052
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Recent progress in epitope prediction has shown promising results in the development of vaccines and therapeutics against various diseases. However, the overall accuracy and success rate need to be improved greatly to gain practical application significance, especially conformational epitope prediction. In this review, we examined the general features of antibody-antigen recognition, highlighting the conformation selection mechanism in flexible antibody-antigen binding. We recently highlighted the success and warning signs of antibody epitope predictions, including linear and conformation epitope predictions. While deep learning-based models gradually outperform traditional feature-based machine learning, sequence and structure features still provide insight into antibody-antigen recognition problems.
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页数:14
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