A computational study of B-cell epitopes of wheat allergens and identification of its IgE binding residues

Abstract

In the contemporary research, biological computational tools have emerged to play a pivotal role in facilitating both cost and time efficient research in several domains of biology. One such domain is addressing the prevailing food allergy issues, where these computational tools have been proven of vital importance. Different tools use different mathematical modelling methods and computational algorithms to predict the result. Due to use of different methodologies in prediction of result the results received by various servers needs to be evaluated for similarity. In the present study, we discuss the identification of IgE binding allergy causing B-Cell epitopes of wheat (Triticum aestivum) allergens, namely ‘Tri a 14’, ‘Tri a 18’, ‘Tri a 19’, ‘Tri a 25’, ‘Tri a 26’, ‘Tri a 36’ and ‘Tri a 37’. Using total seven web servers (ABCPred, ElliPro, BepiPred 1.0b, BcePred, BCPred, CBTOPE and Disco Tope 2.0) 59 linear epitopes and 8 conformational epitopes were predicted in present study. Numbers of linear and conformational epitopes predicted by majority of employed web servers are shown in result. The predicted epitopes are analysed in terms of residues having hydrophilicity, polar nature and having exposed surface. In case of unavailability of suitable structure, in-silico homology modelling has been employed. Cross reactivity of T. aestivum with other food items has also been studied.