Specific binding of antigenic peptides to major
histocompatibility complex (MHC) class I molecules is a
prerequisite for their recognition by cytotoxic T-cells.
Prediction of MHC-binding peptides must therefore be incorporated
in any predictive algorithm attempting to identify immunodominant
T-cell epitopes, based on the amino acid sequence of the
protein antigen. Development of predictive algorithms based
on experimental binding data requires experimental testing
of a very large number of peptides. A complementary approach
relies on the structural conservation observed in crystallographically
solved peptide-MHC complexes. By this approach, the peptide
structure in the MHC groove is used as a template upon
which peptide candidates are threaded, and their compatibility
to bind is evaluated by statistical pairwise potentials.
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 the high emphasis of hydrophobic interactions
in this table. A recently developed pairwise potential
table by Betancourt and Thirumalai (Betancourt MR, Thirumalai
D, 1999, Protein Sci 8:361–369) that is
based on the Miyazawa and Jernigan table describes the
hydrophilic interactions more appropriately. In this paper,
we demonstrate how the use of this table, together with
a new definition of MHC contact residues by which only
residues that contribute exclusively to sequence specific
binding are included, allows the development of an improved
algorithm that can be applied to a wide range of MHC class
I alleles.