Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity

Michael Rasmussen, Emilio Fenoy, Mikkel Harndahl, Anne Bregnballe Kristensen, Ida Kallehauge Nielsen, Morten Nielsen, Søren Buus

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    Abstract

    Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to 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, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, 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 a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network 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 http://www.cbs.dtu.dk/services/NetMHCstabpan.
    Original languageEnglish
    JournalJournal of Immunology
    Volume197
    Issue number4
    Pages (from-to)1517-1524
    Number of pages8
    ISSN0022-1767
    DOIs
    Publication statusPublished - 2016

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