SVM based method for predicting HLA-DRB1^∗0401 binding peptides in an antigen sequence

Abstract

Summary: Prediction of peptides binding with MHC class II allele HLA-DRB10401 can effectively reduce the number of experiments required for identifying helper T cell epitopes.This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1^∗0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique. Available: A web server HLA-DR4Pred based on above approach is available at http://www.imtech.res.in/raghava/ hladr4pred/ and http://bioinformatics.uams.edu/mirror/ ladr4pred/ (Mirror Site).