title: NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ.
abstract: Major histocompatibility complex class II (MHCII) molecules play an important role in cell-mediated immunity. They present specific peptides derived from endosomal proteins for recognition by T helper cells. The identification of peptides that bind to MHCII molecules is therefore of great importance for understanding the nature of immune responses and identifying T cell epitopes for the design of new vaccines and immunotherapies. Given the large number of MHC variants, and the costly experimental procedures needed to evaluate individual peptide-MHC interactions, computational predictions have become particularly attractive as first-line methods in epitope discovery. However, only a few so-called pan-specific prediction methods capable of predicting binding to any MHC molecule with known protein sequence are currently available, and all of them are limited to HLA-DR. Here, we present the first pan-specific method capable of predicting peptide binding to any HLA class II molecule with a defined protein sequence. The method employs a strategy common for HLA-DR, HLA-DP and HLA-DQ molecules to define the peptide-binding MHC environment in terms of a pseudo sequence. This strategy allows the inclusion of new molecules even from other species. The method was evaluated in several benchmarks and demonstrates a significant improvement over molecule-specific methods as well as the ability to predict peptide binding of previously uncharacterised MHCII molecules. To the best of our knowledge, the NetMHCIIpan-3.0 method is the first pan-specific predictor covering all HLA class II molecules with known sequences including HLA-DR, HLA-DP, and HLA-DQ. The NetMHCpan-3.0 method is available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.0 .
authors.affiliation: Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Building 208, Kemitorvet, 2800, Lyngby, Denmark, edita@cbs.dtu.dk.
authors.forename: Edita
authors.initials: E
authors.lastname: Karosiene
authors.forename: Michael
authors.initials: M
authors.lastname: Rasmussen
authors.forename: Thomas
authors.initials: T
authors.lastname: Blicher
authors.forename: Ole
authors.initials: O
authors.lastname: Lund
authors.forename: Søren
authors.initials: S
authors.lastname: Buus
authors.forename: Morten
authors.initials: M
authors.lastname: Nielsen
mesh_terms: D000595:Amino Acid Sequence; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D006682:HLA-DP Antigens / Q000737:chemistry / Q000235:genetics / Q000276:immunology*; D006683:HLA-DQ Antigens / Q000737:chemistry / Q000235:genetics / Q000276:immunology*; D006684:HLA-DR Antigens / Q000737:chemistry / Q000235:genetics / Q000276:immunology*; D000949:Histocompatibility Antigens Class II / Q000145:classification / Q000235:genetics / Q000276:immunology*; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D017433:Protein Structure, Secondary; D017434:Protein Structure, Tertiary; D015203:Reproducibility of Results; D017386:Sequence Homology, Amino Acid
chemical_list: D006682:HLA-DP Antigens; D006683:HLA-DQ Antigens; D006684:HLA-DR Antigens; D000949:Histocompatibility Antigens Class II
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