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Pan-specific prediction of peptide-MHC-I complex stability; a correlate of T cell immunogenicity
M Rasmussen2, E Fenoy3
M Nielsen1,3, Buus S2, Accepted JI June, 2016

1Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark
2Division of Experimental Immunology, Institute of Medical Microbiology and Immunology, University of Copenhagen, Denmark

Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of antigens to cytotoxic T lymphocytes (CTL) and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, i.e. the binding affinity, yet it has been show that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared to binding affinity. Here, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop neural networks based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural networks predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at