title: NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence.
abstract: 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.
authors.affiliation: Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, Lyngby, Denmark. mniel@cbs.dtu.dk
authors.forename: Morten
authors.initials: M
authors.lastname: Nielsen
authors.forename: Claus
authors.initials: C
authors.lastname: Lundegaard
authors.forename: Thomas
authors.initials: T
authors.lastname: Blicher
authors.forename: Kasper
authors.initials: K
authors.lastname: Lamberth
authors.forename: Mikkel
authors.initials: M
authors.lastname: Harndahl
authors.forename: Sune
authors.initials: S
authors.lastname: Justesen
authors.forename: Gustav
authors.initials: G
authors.lastname: Røder
authors.forename: Bjoern
authors.initials: B
authors.lastname: Peters
authors.forename: Alessandro
authors.initials: A
authors.lastname: Sette
authors.forename: Ole
authors.initials: O
authors.lastname: Lund
authors.forename: Søren
authors.initials: S
authors.lastname: Buus
mesh_terms: 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
chemical_list: D015234:HLA-A Antigens; D015235:HLA-B Antigens; D010455:Peptides