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 af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

547 Citationer (Scopus)

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-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.

OriginalsprogEngelsk
TidsskriftImmunology
Vol/bind154
Udgave nummer3
Sider (fra-til)394-406
ISSN0019-2805
DOI
StatusUdgivet - 2018

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