摘要
抗原表位预测是免疫信息学研究的重要方向之一,可以给实验提供重要的线索。B细胞表位或抗原决定簇是抗原中可被B细胞受体或抗体特异性识别并结合的部位。实际上,近90%的B细胞表位是构象性的。即使抗原蛋白质三级结构已知,B细胞表位预测仍然是一大挑战。该文结合实例阐述当今主要的构象性B细胞表位预测方法和算法:机器学习预测、非机器学习的计算预测、基于噬菌体展示数据的识别方法,以及一些也可用于构象性B细胞表位预测的通用蛋白质-蛋白质界面预测方法;介绍最新相关预测软件和Web服务资源,说明未来的研究趋势。
Accurate prediction of epitopes is an important goal of immunoinformatics,which can give important clues to experiments. B-cell epitopes or antigenic determinant is a part of an antigen recognized by either a particular antibody molecule or a particular B-cell receptor of the immune system. Up to 90% of B-cell epitopes are conformational in nature. Even when the tertiary structure of the antigen is available,the accurate prediction of B-cell epitopes remains challenging. First,this review illustrated current prediction methods and algorithms for the conformational B-cell epitopes by describing some examples,including machine-learning approaches,computational prediction methods independent of machine-learning approach,Phage-displayed data based approaches,along with some universal recognizing approaches of protein-protein interface prediction. Next,it presented the latest software packages and web services available online that relate to conformational B-cell epitope prediction,and projected future developments.
出处
《生命科学》
CSCD
北大核心
2010年第9期946-951,共6页
Chinese Bulletin of Life Sciences
关键词
抗原
抗体
表位
预测
构象性
antigen
antibody
epitope
prediction
conformational
