Beyond natural amino acids: Extending immunogenicity risk assessment to non-canonical peptide drugs through chemical feature encoding
Maria Cairoli, Catherine Jean Betts, Morten Nielsen, Olga Obrezanova, Leonardo De Maria
The paper develops a machine learning framework to predict MHC class II binding for canonical and modified peptides by incorporating chemical features, improving immunogenicity risk assessment for non-canonical peptide drugs.
European Peptide Symposium (EPS) · Sep 25, 2026Peer-reviewedBioinformatics