Homology Modeling of Sesame Allergenic Protein and Prediction of B-Cell Linear Antigenic Epitopes Using Immunoinformatic Tools

Sesame (<i>Sesamum indicum</i> L.) has emerged as a significant food allergen and is now classified among the "Big Eight" allergens due to its increasing prevalence and potential to cause severe allergic reactions, including anaphylaxis. Seven sesame allergens have been identified; however, their structures and epitopes have not been thoroughly studied. In the present study, we predicted the tertiary structures of these seven sesame allergens and identified the B-cell epitopes using immunoinformatic tools, suggesting them as potential targets for allergen immunotherapy. Consequently, homology modeling and tertiary structure prediction were performed for the seven allergens with unknown structures. A total of 62 peptides were identified through prediction analysis. Twenty-eight out of the 62 predicted epitopes are located in regions that are positionally conserved with previously reported epitopes in homologous allergens. They share certain key amino acids. The spatial distribution of some predicted B-cell linear epitopes is depicted, providing multiple perspectives. The predicted consensus epitopes and structures can serve as suitable candidates for designing immunotherapeutic vaccines.