Structure-based prediction of binding peptides to MHC class I molecules: Application to a broad range of MHC alleles

Specific binding of antigenic peptides to major histocompatibility complex (MHC) class I molecules is a prerequisite for their recognition by cytotoxi c T-cells. Prediction of MHC-binding peptides must therefore be incorporate d in any predictive algorithm attempting to identify immunodominant T-cell epitopes, based on the amino acid sequence of the protein antigen. Developm ent of predictive algorithms based on experimental binding data requires ex perimental testing of a very large number of peptides. A complementary appr oach relies on the structural conservation observed in crystallographically solved peptide-MHC complexes. By this approach, the peptide structure in t he MHC groove is used as a template upon which peptide candidates are threa ded, and their compatibility to bind is evaluated by statistical pairwise p otentials. Our original algorithm based on this approach used the pairwise potential table of Miyazawa and Jernigan (Miyazawa S, Jernigan RL, 1996, J Mol Biol 256:623-644) and succeeded to correctly identify good binders only for MHC molecules with hydrophobic binding pockets, probably because of th e high emphasis of hydrophobic interactions in this table. A recently devel oped pairwise potential table by Betancourt and Thirumalai (Betancourt MR, Thirumalai D, 1999, Protein Sci 8:361-369) that is based on the Miyazawa an d Jernigan table describes the hydrophilic interactions more appropriately. In this paper, we demonstrate how the use of this table, together with a n ew definition of MHC contact residues by which only residues that contribut e exclusively to sequence specific binding are included, allows the develop ment of an improved algorithm that can be applied to a wide range of MHC cl ass I alleles.