MHC Class I binding predictions as a tool in epitope discovery

CLAUS LUNDEGAARD; OLE LUND; SØREN BUUS; MORTEN NIELSEN

IMMUNOLOGY

WILEY-BLACKWELL PUBLISHING, INC

Año: 2010 p. 309 - 318

0019-2805

SUMMARY: Over the last decade, in silico models of the major histocompatibility complex (MHC) class I pathway have developed significantly. Before, peptide binding could only be reliably modelled for a few major human or mouse histocompatibility molecules; now, high-accuracy predictions are available for any human leucocyte antigen (HLA) -A or -B molecule with known protein sequence. Furthermore, peptide binding to MHC molecules from several non-human primates, mouse strains and other mammals can now be predicted. In this review, a number of different prediction methods are briefly explained, highlighting the most useful and historically important. Selected case stories, where these ´reverse immunology´ systems have been used in actual epitope discovery, are briefly reviewed. We conclude that this new generation of epitope discovery systems has become a highly efficient tool for epitope discovery, and recommend that the less accurate prediction systems of the past be abandoned, as these are obsolete.