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Deep motif deconvolution of HLA-II peptidomes for robust class II epitope predictions

By Julien Racle, Justine Michaux, Georg Alexander Rockinger, Marion Arnaud, Sara Bobisse, Chloe Chong, Philippe Guillaume, George Coukos, Alexandre Harari, Camilla Jandus, Michal Bassani-Sternberg, David Gfeller

Posted 03 Feb 2019
bioRxiv DOI: 10.1101/539338 (published DOI: 10.1038/s41587-019-0289-6)

CD4 T cells are key for priming and regulating immune recognition of infected and cancer cells, but predictions of class II epitopes have limited accuracy. We combined unbiased Mass Spectrometry-based HLA-II peptidomics with a novel motif deconvolution algorithm to profile and analyze a total of 99265 unique HLA-II ligands. Our work demonstrates substantial improvement in the definition of HLA-II binding motifs and enhanced accuracy in class II epitope predictions.

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