TY - JOUR T1 - NetMHC pan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data JF - bioRxiv DO - 10.1101/149518 SP - 149518 AU - Vanessa Jurtz AU - Sinu Paul AU - Massimo Andreatta AU - Paolo Marcatili AU - Bjoern Peters AU - Morten Nielsen Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/06/13/149518.abstract N2 - Cytotoxic T cells are of central importance in the immune system’s response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC (major histocompatibility complex) class I molecules. Peptide binding to MHC molecules is the single most selective step in the antigen presentation pathway. On the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has therefore attracted large attention. In the past, predictors of peptide-MHC interaction have in most cases been trained on binding affinity data. Recently an increasing amount of MHC presented peptides identified by mass spectrometry has been published containing information about peptide processing steps in the presentation pathway and the length distribution of naturally presented peptides. Here, we present NetMHCpan-4.0, a method trained on both binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increased predictive performance compared to state-of-the-art when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes. ER -