Sarah Hall-Swan

This paper evaluates the effectiveness of general protein language models and negative data generation strategies in predicting TCR-peptide-MHC interactions, finding that they struggle to distinguish positive from negative TCRs.

HLAIIPred predicts HLAII-presented peptides using a Transformer-based model, outperforming existing methods and identifying core interaction residues.

DINC-COVID provides a webserver for ensemble docking of SARS-CoV-2 proteins with flexible receptors and ligands, generating and scoring plausible binding modes.