Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, HP, India.
National Bureau of Animal Genetic Resources, Karnal, Haryana, India.
Methods Mol Biol. 2020;2131:155-171. doi: 10.1007/978-1-0716-0389-5_6.
With advancements in sequencing technologies, vast amount of experimental data has accumulated. Due to rapid progress in the development of bioinformatics tools and the accumulation of data, immunoinformatics or computational immunology emerged as a special branch of bioinformatics which utilizes bioinformatics approaches for understanding and interpreting immunological data. One extensively studied aspect of applied immunology involves using available databases and tools for prediction of B- and T-cell epitopes. B and T cells comprise two arms of adaptive immunity.This chapter first reviews the methodology we used for computational identification of B- and T-cell epitopes against enterotoxigenic Escherichia coli (ETEC). Then we discuss other databases of epitopes and analysis tools for T-cell and B-cell epitope prediction and vaccine design. The predicted peptides were analyzed for conservation and population coverage. HLA distribution analysis for predicted epitopes identified efficient MHC binders. Epitopes were further tested using computational docking studies to bind in MHC-I molecule cleft. The predicted epitopes were conserved and covered more than 80% of the world population.
随着测序技术的进步,大量的实验数据已经积累起来。由于生物信息学工具的快速发展和数据的积累,免疫信息学或计算免疫学作为生物信息学的一个特殊分支出现了,它利用生物信息学方法来理解和解释免疫学数据。应用免疫学中一个广泛研究的方面涉及到利用现有的数据库和工具来预测 B 细胞和 T 细胞表位。B 细胞和 T 细胞构成了适应性免疫的两个分支。本章首先回顾了我们用于计算鉴定肠产毒性大肠杆菌(ETEC)的 B 细胞和 T 细胞表位的方法。然后我们讨论了其他用于 T 细胞和 B 细胞表位预测和疫苗设计的表位数据库和分析工具。预测的肽段被分析其保守性和人群覆盖率。对预测的表位进行 HLA 分布分析,以鉴定有效的 MHC 结合物。进一步使用计算对接研究来测试预测的表位与 MHC-I 分子凹槽的结合。预测的表位具有保守性,覆盖了全球 80%以上的人群。