TY - JOUR
T1 - Major histocompatibility complex class I binding predictions as a tool in epitope discovery
AU - Lundegaard, Claus
AU - Lund, Ole
AU - Buus, Søren
AU - Nielsen, Morten
N1 - Keywords: Animals; Computational Biology; Epitopes, T-Lymphocyte; Histocompatibility Antigens Class I; Humans; Protein Binding
PY - 2010/7
Y1 - 2010/7
N2 - 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.
AB - 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.
U2 - 10.1111/j.1365-2567.2010.03300.x
DO - 10.1111/j.1365-2567.2010.03300.x
M3 - Journal article
C2 - 20518827
SN - 0953-4954
VL - 130
SP - 309
EP - 318
JO - Immunology. Supplement
JF - Immunology. Supplement
IS - 3
ER -