Improved methods for predicting peptide binding affinity to MHC class II molecules

Kamilla Kjærgaard Jensen, Massimo Andreatta, Paolo Marcatili, Søren Buus, Jason A Greenbaum, Zhen Yan, Alessandro Sette, Bjoern Peters, Morten Nielsen*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Abstract

    Major histocompatibility complex class II (MHC-II) molecules are expressed on the surface of professional antigen presenting cells where they display peptides to T helper cells, which orchestrate the onset and outcome of many host immune responses. Understanding which peptides will be presented by the MHC-II molecule is therefore important for understanding the activation of T helper cells and can be used to identify T-cell epitopes. We here present updated versions of two MHC class II peptide binding affinity prediction methods, NetMHCII and NetMHCIIpan. These were constructed using an extended data set of quantitative MHC-peptide binding affinity data obtained from the Immune Epitope Database covering HLA-DR, HLA-DQ, HLA-DP and H-2 mouse molecules. We show that training with this extended data set improved the performance for peptide binding predictions for both methods. Both methods are publicly available at www.cbs.dtu.dk/services/NetMHCII-2.3 and www.cbs.dtu.dk/services/NetMHCIIpan-3.2. This article is protected by copyright. All rights reserved.
    Original languageEnglish
    JournalImmunology
    Volume154
    Issue number3
    Pages (from-to)394-406
    ISSN0019-2805
    DOIs
    Publication statusPublished - 2018

    Keywords

    • MHC binding specificity
    • T-cell epitope
    • Affinity predictions
    • Immunogenic peptides
    • Peptide-MHC binding

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