Computational Approaches for Prediction of Conformational Epitopes for Birch Betv 1 and Hazel Cor A1 Targeting B-cells

Abstract

Through targeted interactions mediated by receptors on antibodies, B-cells effectively neutralize invading pathogens by binding with remarkable precision to specific molecular regions, called epitopes. This study focuses on enhancing B-cell epitope predictions via computational methods. Antigen sequences are fragmented into peptides and docked against IgE antibodies to identify top-scoring interactions. Peptides with the highest scores undergo further analysis to assess bond interactions. By examining overlapping sequences within the antigen model, the positions of predicted epitopes are determined. Residues involved in bond interactions are documented for these overlapping peptide sequences. Validation is achieved through antigen-antibody docking studies to confirm the predicted epitope sites. Ultimately, the integration of computational and experimental methodologies holds promise for the rational design of immunotherapeutic interventions targeting Birch and Hazel allergens, paving the way for precision medicine in allergy treatment.