Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification

Massimo Andreatta, Edita Karosiene, Michael Rasmussen, Anette Stryhn, Søren Buus, Morten Nielsen

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    A key event in the generation of a cellular response against malicious organisms through the endocytic pathway is binding of peptidic antigens by major histocompatibility complex class II (MHC class II) molecules. The bound peptide is then presented on the cell surface where it can be recognized by T helper lymphocytes. NetMHCIIpan is a state-of-the-art method for the quantitative prediction of peptide binding to any human or mouse MHC class II molecule of known sequence. In this paper, we describe an updated version of the method with improved peptide binding register identification. Binding register prediction is concerned with determining the minimal core region of nine residues directly in contact with the MHC binding cleft, a crucial piece of information both for the identification and design of CD4+ T cell antigens. When applied to a set of 51 crystal structures of peptide-MHC complexes with known binding registers, the new method NetMHCIIpan-3.1 significantly outperformed the earlier 3.0 version. We illustrate the impact of accurate binding core identification for the interpretation of T cell cross-reactivity using tetramer double staining with a CMV epitope and its variants mapped to the epitope binding core. NetMHCIIpan is publicly available at http://www.cbs.dtu.dk/services/NetMHCIIpan-3.1.
    Original languageEnglish
    JournalImmunogenetics
    Volume67
    Issue number11-12
    Pages (from-to)641-650
    Number of pages10
    ISSN0093-7711
    DOIs
    Publication statusPublished - 2015

    Keywords

    • Artificial neural networks
    • Binding core
    • MHC class II
    • Peptide binding
    • Peptide-MHC
    • T cell cross-reactivity

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