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bioRxiv · 10.1101/539338

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

Racle, J.·Michaux, J.·Rockinger, G. A.·Arnaud, M.·Bobisse, S.·Chong, C.·Guillaume, P.·Coukos, G.·Harari, A.·Jandus, C.·Bassani-Sternberg, M.·Gfeller, D.
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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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Racle, J., Michaux, J., Rockinger, G. A., Arnaud, M., Bobisse, S., Chong, C., Guillaume, P., Coukos, G., Harari, A., Jandus, C., Bassani-Sternberg, M., Gfeller, D.. 2019-02-03. Deep motif deconvolution of HLA-II peptidomes for robust class II epitope predictions. https://doi.org/10.1101/539338

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