netmhcpan, a method for quantitative predictions of peptide binding to any hla-a and -b locus protein of known sequencenetmhcpan,定量预测方法- b位点的蛋白质和肽绑定于任何已知的序列.pdfVIP

NetMHCpan, a Method for Quantitative Predictions of Peptide Binding to Any HLA-A and -B Locus Protein of Known Sequence 1 1 1 2 2 2 2 3 Morten Nielsen *, Claus Lundegaard , Thomas Blicher , Kasper Lamberth , Mikkel Harndahl , Sune Justesen , Gustav Røder , Bjoern Peters , 3 1 2 Alessandro Sette , Ole Lund , Søren Buus 1 Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, Lyngby, Denmark, 2 Department of Experimental Immunology, Institute of Medical Microbiology and Immunology, University of Copenhagen, Copenhagen, Denmark, 3 La Jolla Institute for Allergy and Immunology, San Diego, California, United States of America 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. Principal Findings. 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 sugges