PREDICTION AND MAPPING OF IGE EPITOPES IN THE ALLERGENIC EGG PROTEINS USING COMPUTATIONAL APPROACHES

Abstract

Food allergy is an emerging public health problem that is most prevalent during infancy, affecting up to 6% of young children. Food allergy denotes an immunologic mechanism represented almost exclusively by IgE-mediated reactions. Rapid advances have been made in the past few years on allergen characterization and sequence determination by biochemical and molecular biological approaches. However, the last decade has seen rapid progress in identification of allergenic proteins and prediction of both linear and conformational epitope based on sequence or structure information using bioinformatics software. This study aims at identifying potential allergenic proteins in the egg proteome and also predicting and mapping IgE epitopes in the predicted allergenic proteins in egg using in silico approaches. We have used the support vector machine module of AlgPred, based on amino acid and dipeptide composition, to predict highly allergenic proteins in egg proteome. The structures of some allergenic proteins that lack crystal structure information were predicted using ab-intio methods. The prediction of IgE epitopes were carried out on all the predicted allergenic proteins using SPADE, EPITOPIA, SEPPA and ELLIPRO. The potential allergenic proteins in the egg proteome were identified. We then predict linear and conformational epitopes in these allergenic proteins by various softwares using different approaches to compare the predicted IgE epitopes. We also characterized the epitope in terms of properties like solvent accessibility, electrostatic potential, hydrophobicity and total area of epitope. The results obtained have been correlated with experimental studies reported in the literature. The study for the first time reports a consensus report of the epitope patches for each allergenic protein in egg proteome predicted using different approaches. It is hoped that these results will be useful for epitope identification and characterization based on a given protein sequence and structure information and pave way for vaccine development for allergic patients in future.