bioRxivImmunology
Deep motif deconvolution of HLA-II peptidomes for robust class II epitope predictions
J. Racle, J. Michaux, G. A. Rockinger, M. Arnaud, S. Bobisse, C. Chong, P. Guillaume, G. Coukos, A. Harari, C. Jandus, M. Bassani-Sternberg, D. Gfeller
Abstract
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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