Abstract
Promiscuous T‐cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA‐A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide‐binding predictions for HLA‐A∗0201, ∗0204, and ∗0205 alleles, good accuracy for ∗0206 allele, and marginal accuracy for ∗0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide‐binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA‐A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.