Abstract
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.
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The authors pay high tribute to the experts and scholars who have devoted themselves to the study of food allergy and immunology.
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He, S., Zhou, F. (2024). Characterization of T-Cell Epitopes in Food Allergens by Bioinformatic Tools. In: Cabanillas, B. (eds) Food Allergens. Methods in Molecular Biology, vol 2717. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3453-0_6
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DOI: https://doi.org/10.1007/978-1-0716-3453-0_6
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