Prediction of peptide affinity to HLA DR molecules.

Abstract

A method to quantitatively predict peptide binding to HLA DRB1*0401, B1*0101, and B1*1501 has been developed using a dataset of the relative contributions of each of the naturally occurring amino acids in the context of a simplified peptide backbone. The prediction assumed that the relative role of each of the peptide sidechains could be treated independently and could be measured by assaying each of the twenty naturally occurring amino acids at the central eleven positions of a 13 residue peptide previously shown to contain the minimal requirements for high affinity binding to HLA DR proteins. Three separate databases were generated. They were shown to have predictive value when tested on a set of 13 unrelated peptides known to bind the DR proteins with a wide range of apparent affinity. The DRB1*0401 database was tested further by analyzing myelin basic protein. All 13 amino acid peptides containing a hydrophobic amino acid at the third position were synthesized and assayed for binding purified DRB1*0401. In every case, the measured affinity correlated with the predictive values within the experimental error of the assays. Finally, the ability to predict peptide binding to MHC class II molecules was shown to help in identifying T cell determinants. The specificity of DRB1*0401 restricted T cell hybridomas against human serum albumin corresponded to two peptides, predicted, and shown to bind the class II protein with high affinity.