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- Title
Footprints of antigen processing boost MHC class II natural ligand predictions.
- Authors
Barra, Carolina; Alvarez, Bruno; Paul, Sinu; Sette, Alessandro; Peters, Bjoern; Andreatta, Massimo; Buus, Søren; Nielsen, Morten
- Abstract
Background: Major histocompatibility complex class II (MHC-II) molecules present peptide fragments to T cells for immune recognition. Current predictors for peptide to MHC-II binding are trained on binding affinity data, generated in vitro and therefore lacking information about antigen processing. Methods: We generate prediction models of peptide to MHC-II binding trained with naturally eluted ligands derived from mass spectrometry in addition to peptide binding affinity data sets. Results: We show that integrated prediction models incorporate identifiable rules of antigen processing. In fact, we observed detectable signals of protease cleavage at defined positions of the ligands. We also hypothesize a role of the length of the terminal ligand protrusions for trimming the peptide to the MHC presented ligand. Conclusions: The results of integrating binding affinity and eluted ligand data in a combined model demonstrate improved performance for the prediction of MHC-II ligands and T cell epitopes and foreshadow a new generation of improved peptide to MHC-II prediction tools accounting for the plurality of factors that determine natural presentation of antigens.
- Subjects
MAJOR histocompatibility complex; FOOTPRINTS; ANTIGEN processing; LIGANDS (Biochemistry); T cells; IMMUNE recognition
- Publication
Genome Medicine, 2018, Vol 10, Issue 1, pN.PAG
- ISSN
1756-994X
- Publication type
Article
- DOI
10.1186/s13073-018-0594-6