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

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

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

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

ID: 189861945