, Volume 66, Issue 7, pp 449–456

NetTepi: an integrated method for the prediction of T cell epitopes


  • Thomas Trolle
    • Center for Biological Sequence Analysis, Department of Systems BiologyThe Technical University of Denmark
    • Center for Biological Sequence Analysis, Department of Systems BiologyThe Technical University of Denmark
    • Instituto de Investigaciones BiotecnológicasUniversidad Nacional de San Martín
Original Paper

DOI: 10.1007/s00251-014-0779-0

Cite this article as:
Trolle, T. & Nielsen, M. Immunogenetics (2014) 66: 449. doi:10.1007/s00251-014-0779-0


Multiple factors determine the ability of a peptide to elicit a cytotoxic T cell lymphocyte response. Binding to a major histocompatibility complex class I (MHC-I) molecule is one of the most essential factors, as no peptide can become a T cell epitope unless presented on the cell surface in complex with an MHC-I molecule. As such, peptide-MHC (pMHC) binding affinity predictors are currently the premier methods for T cell epitope prediction, and these prediction methods have been shown to have high predictive performances in multiple studies. However, not all MHC-I binders are T cell epitopes, and multiple studies have investigated what additional factors are important for determining the immunogenicity of a peptide. A recent study suggested that pMHC stability plays an important role in determining if a peptide can become a T cell epitope. Likewise, a T cell propensity model has been proposed for identifying MHC binding peptides with amino acid compositions favoring T cell receptor interactions. In this study, we investigate if improved accuracy for T cell epitope discovery can be achieved by integrating predictions for pMHC binding affinity, pMHC stability, and T cell propensity. We show that a weighted sum approach allows pMHC stability and T cell propensity predictions to enrich pMHC binding affinity predictions. The integrated model leads to a consistent and significant increase in predictive performance and we demonstrate how this can be utilized to decrease the experimental workload of epitope screens. The final method, NetTepi, is publically available at


T cell epitopePeptide immunogenicityMHC binding specificityPeptide-MHC binding stabilityCytotoxic T lymphocyteMHC class I

Supplementary material

251_2014_779_MOESM1_ESM.pdf (96 kb)
Fig. S1Bar-plot showing the accumulated number of wins for each prediction method as a function of the predicted binding affinity for each epitope in the evaluation data set. (PDF 96 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2014