Martínez Naves, EduardoLafuente Duarte, EstherReche, Pedro A2023-06-202023-06-202011[1] Maenaka, K. and Jones, E.Y. (1999) MHC superfamily structure and the immune system. Curr. Opin. Struct. Biol. 9, 745–753. [2] Townsend, A. and Bodmer, H. (1989) Antigen recognition by class I-restricted T lymphocytes. Annu. Rev. Immunol. 7, 601–624. [3] Braud, V.M., Allan, D.S. and McMichael, A.J. (1999) Functions of nonclassical MHC and non-MHC-encoded class I molecules. Curr. Opin. Immunol. 11, 100–108. [4] Rodgers, J.R. and Cook, R.G. (2005) MHC class Ib molecules bridge innate and acquired immunity. Nat. Rev. Immunol. 5, 459–471. [5] Martínez-Naves, E., Lafuente, E.M. and Reche, P.A. (2011) Classification of MHC I proteins according to their ligand-type specificity in: 10th International Conference on Artificial Immune Systems (Liò, P., Nicosia, G. and Stibor, T., Eds.), pp. 55–65, Springer-Verlag Cambridge, England, UK. [6] Frank, E., Hall, M., Trigg, L., Holmes, G. and Witten, I.H. (2004) Data mining in bioinformatics using WEKA. Bioinformatics 20, 2479–2481. [7] Wu, X. et al. (2008) Top 10 algorithms in data mining. Knowl. Inf. Syst 14, 1–37. [8] Dasarathy, B.V. (1991) Nearest neighbor (NN) norms: NN pattern classification techniques, IEEE Computer Society Press, Los Alamitos, California. [9] Shatsky, M., Nussinov, R. and Wolfson, H.J. (2004) A method for simultaneous alignment of multiple protein structures. Proteins 56, 143–156. [10] Shatsky, M., Nussinov, R. and Wolfson, H.J. (2006) Optimization of multiplesequence alignment based on multiple-structure alignment. Proteins. 62, 209–217. [11] Notredame, C., Higgins, D.G. and Heringa, J. (2000) T-Coffee: A novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 302, 205–217. [12] Firestine, S.M., Nixon, A.E. and Benkovic, S.J. (1996) Threading your way to protein function. Chem. Biol. 3, 779–783. [13] Felsenstein, J. (1985) Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39, 783–791. [14] Carro, A., Tress, M., de Juan, D., Pazos, F., Lopez-Romero, P., del Sol, A., Valencia, A. and Rojas, A.M. (2006) TreeDet: a web server to explore sequence space. Nucleic Acids Res. 34, W110–W115. [15] Bhasin, M., Reinherz, E.L. and Reche, P.A. (2006) Recognition and classification of histones using support vector machine. J. Comput. Biol. 13, 102–112. [16] Yang, Z. and Bjorkman, P.J. (2008) Structure of UL18, a peptide-binding viral MHC mimic, bound to a host inhibitory receptor. Proc. Natl. Acad. Sci. USA 105, 10095–10100. [17] Crowley, M.P., Fahrer, A.M., Baumgarth, N., Hampl, J., Gutgemann, I., Teyton, L. and Chien, Y. (2000) A population of murine cd T cells that recognize an inducible MHC class Ib molecule. Science 287, 314–316. [18] Shin, S., El-Diwany, R., Schaffert, S., Adams, E.J., Garcia, K.C., Pereira, P. and Chien, Y.H. (2005) Antigen recognition determinants of cd T cell receptors. Science 308, 252–255. [19] Koch, M. et al. (2007) Structures of an MHC class I molecule from B21 chickens illustrate promiscuous peptide binding. Immunity 27, 885–899. [20] Hee, C.S., Gao, S., Loll, B., Miller, M.M., Uchanska-Ziegler, B., Daumke, O. and Ziegler, A. (2010) Structure of a classical MHC class I molecule that binds ‘‘non-classical’’ ligands. PLoS Biol. 8, e1000557. [21] Loconto, J. et al. (2003) Functional expression of murine V2R pheromone receptors involves selective association with the M10 and M1 families of MHC class Ib molecules. Cell 112, 607–618. [22] Olson, R., Huey-Tubman, K.E., Dulac, C. and Bjorkman, P.J. (2005) Structure of a pheromone receptor-associated MHC molecule with an open and empty groove. PLoS Biol. 3, e257. [23] Treiner, E. et al. (2003) Selection of evolutionarily conserved mucosalassociated invariant T cells by MR1. Nature 422, 164–169. [24] Huang, S., Gilfillan, S., Cella, M., Miley, M.J., Lantz, O., Lybarger, L., Fremont, D.H. and Hansen, T.H. (2005) Evidence for MR1 antigen presentation to mucosal-associated invariant T cells. J. Biol. Chem. 280, 21183–21193. [25] Le Bourhis, L. et al. (2010) Antimicrobial activity of mucosal-associated invariant T cells. Nat. Immunol. 11, 701–708. [26] Abos, B., Gomez Del Moral, M., Gozalbo-Lopez, B., Lopez-Relano, J., Viana, V. and Martinez-Naves, E. (2011) Human MR1 expression on the cell surface is acid sensitive, proteasome independent and increases after culturing at 26 degrees C. Biochem. Biophys. Res. Commun. 411, 632–636. [27] Shimamura, M. et al. (2007) Modulation of Va19 NKT cell immune responses by a-mannosyl ceramide derivatives consisting of a series of modified sphingosines. Eur J Immunol. 37, 1836–1844. [28] Huang, S. et al. (2008) MR1 uses an endocytic pathway to activate mucosalassociated invariant T cells. J. Exp. Med. 205, 1201–1211. [29] Lafuente, E.M. and Reche, P.A. (2009) Prediction of MHC-peptide binding: a systematic and comprehensive overview. Curr. Pharm. Des. 15, 3209–3220.1873-346810.1016/j.febslet.2011.10.007https://hdl.handle.net/20.500.14352/41998Functional 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.engAtribución 3.0 Españajournal articlehttp://www.sciencedirect.com/science/article/pii/S0014579311007459open access577.257:004Classical MHC class I moleculeNon-classical MHC class I moleculeMachine learningLigandPredictionBiología molecular (Biología)Bioinformática2415 Biología Molecular