, Volume 67, Issue 11–12, pp 641–650 | Cite as

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 NielsenEmail author
Original Paper


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


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



This work was supported with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under Contract No. HHSN272201200010C, and from the Agencia Nacional de Promoción Científica y Tecnológica, Argentina (PICT-2012-0115). MN is a researcher at the Argentinean national research council (CONICET).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Massimo Andreatta
    • 1
  • Edita Karosiene
    • 2
  • Michael Rasmussen
    • 3
  • Anette Stryhn
    • 3
  • Søren Buus
    • 3
  • Morten Nielsen
    • 1
    • 4
    Email author
  1. 1.Instituto de Investigaciones BiotecnológicasUniversidad Nacional de San MartínSan MartínArgentina
  2. 2.Division of Vaccine DiscoveryLa Jolla Institute for Allergy and ImmunologyLa JollaUSA
  3. 3.Laboratory of Experimental Immunology, Faculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark
  4. 4.Center for Biological Sequence Analysis, Department of Systems BiologyTechnical University of DenmarkLyngbyDenmark

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