School of Food and Biological Engineering, Engineering Research Center of Bio-process of Ministry of Education, Hefei University of Technology, Hefei, China.
Methods Mol Biol. 2024;2717:77-99. doi: 10.1007/978-1-0716-3453-0_6.
The identification of T-cell epitopes is a critical step in the understanding of the immunologic mechanisms such as food allergy. Epitope screening in silico by bioinformatic tools can be used to identify T-cell epitopes, which can save time and resources. In this chapter, a multiparametric approach to predict and assess major histocompatibility complex (MHC) class II binding T-cell epitopes using bioinformatics was introduced for food allergens. Furthermore, the ability of predicted T-cell epitopes to induce interleukin (IL)-4, as well as the allergenicity potential based on the sequence analysis and population coverage of epitopes were also determined. The molecular docking approach was further used to explore the binding ability between epitopes and human leukocyte antigen (HLA) class II molecules. The amino acids that might be responsible for binding to HLA class II molecules and their binding interactions were analyzed.
T 细胞表位的鉴定是理解免疫机制（如食物过敏）的关键步骤。通过生物信息学工具进行表位筛选可以用于鉴定 T 细胞表位，从而节省时间和资源。本章介绍了一种使用生物信息学预测和评估食物过敏原主要组织相容性复合体（MHC）Ⅱ类结合 T 细胞表位的多参数方法。此外，还确定了预测的 T 细胞表位诱导白细胞介素（IL）-4 的能力，以及基于序列分析和表位人群覆盖率的变应原性潜力。进一步使用分子对接方法来探索表位与人类白细胞抗原（HLA）Ⅱ类分子之间的结合能力。分析了可能与 HLA Ⅱ类分子结合的氨基酸及其结合相互作用。
