title: Recognition of the ligand-type specificity of classical and non-classical MHC I proteins.
abstract: Functional characterization of proteins belonging to the MHC I superfamily involves knowing their cognate ligands, which can be peptides, lipids or none. However, the experimental identification of these ligands is not an easy task and generally requires some a priori knowledge of their chemical nature (ligand-type specificity). Here, we trained k-nearest neighbor and support vector machine classifiers that predict the ligand-type specificity MHC I proteins with great accuracy. Moreover, we applied these classifiers to human and mouse MHC I proteins of uncharacterized ligands, obtaining some results that can be instrumental to unravel the function of these proteins.
authors: Department of Microbiology I-Immunology, Facultad de Medicina, Universidad Complutense de Madrid, Ave Complutense S/N, Madrid 28040, Spain.
authors: Eduardo
authors: E
authors: Martínez-Naves
authors: Esther M
authors: EM
authors: Lafuente
authors: Pedro A
authors: PA
authors: Reche
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D019295:Computational Biology; D006680:HLA Antigens / Q000737:chemistry / Q000378:metabolism*; D006801:Humans; D008024:Ligands; D051379:Mice; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011485:Protein Binding; D011487:Protein Conformation; D015203:Reproducibility of Results; D016415:Sequence Alignment; D013379:Substrate Specificity
chemical_list: D006680:HLA Antigens; D008024:Ligands