AN EMPIRICAL-METHOD FOR THE PREDICTION OF T-CELL EPITOPES

Identification of T-cell epitopes from foreign proteins is the current focus of much research, Methods using simple two or three position mo tifs have proved useful in epitope prediction for major histocompatibi lity complex (MHC) class I, but to date not for MHC class II molecules . We utilized data from pool sequence analysis of peptides eluted from two HLA-DR13 alleles to construct a computer algorithm for predicting the probability that a given sequence will be naturally processed and presented on these alleles. We assessed the ability of this method to predict known self-peptides from these DR-13 alleles, DRB11301 and * 1302, as well as an immunodominant T-cell epitope. We also compared th e predictions of this scoring procedure with the measured binding affi nities of a panel of overlapping peptides from hepatitis B virus surfa ce antigen. We concluded that this method may have wide application fo r the prediction of T-cell epitopes for both MHC class I and class II molecules.