NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence.
BACKGROUND
Binding of peptides to Major Histocompatibility Complex (MHC) molecules is the single most selective step in the recognition of pathogens by the cellular immune system. The human MHC class I system (HLA-I) is extremely polymorphic. The number of registered HLA-I molecules has now surpassed 1500. Characterizing the specificity of each separately would be a major undertaking.


RESULTS
Here, we have drawn on a large database of known peptide-HLA-I interactions to develop a bioinformatics method, which takes both peptide and HLA sequence information into account, and generates quantitative predictions of the affinity of any peptide-HLA-I interaction. Prospective experimental validation of peptides predicted to bind to previously untested HLA-I molecules, cross-validation, and retrospective prediction of known HIV immune epitopes and endogenous presented peptides, all successfully validate this method. We further demonstrate that the method can be applied to perform a clustering analysis of MHC specificities and suggest using this clustering to select particularly informative novel MHC molecules for future biochemical and functional analysis.


CONCLUSIONS
Encompassing all HLA molecules, this high-throughput computational method lends itself to epitope searches that are not only genome- and pathogen-wide, but also HLA-wide. Thus, it offers a truly global analysis of immune responses supporting rational development of vaccines and immunotherapy. It also promises to provide new basic insights into HLA structure-function relationships. The method is available at http://www.cbs.dtu.dk/services/NetMHCpan.
Nielsen
Morten
M
Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk
Lundegaard
Claus
C
Blicher
Thomas
T
Lamberth
Kasper
K
Harndahl
Mikkel
M
Justesen
Sune
S
Røder
Gustav
G
Peters
Bjoern
B
Sette
Alessandro
A
Lund
Ole
O
Buus
Søren
S
D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D015234:HLA-A Antigens / Q000737:chemistry* / Q000378:metabolism; D015235:HLA-B Antigens / Q000737:chemistry* / Q000378:metabolism; D006801:Humans; D010455:Peptides / Q000737:chemistry / Q000378:metabolism*; D012984:Software
D015234:HLA-A Antigens; D015235:HLA-B Antigens; D010455:Peptides