Diane Joseph‐McCarthy

This paper shows that focusing on complementarity-determining regions (CDRs) in antibody sequences improves binding affinity prediction using region-aware pretraining strategies.

This study evaluates AlphaFold3's ability to predict cryptic pockets and their ligand binding, showing it can generate accurate structural ensembles when provided with ligands.

The paper uses FTMap to analyze 50 antibody-antigen complexes, finding that paratopes are hot spot-rich and that Trp/Tyr residues drive hot spot formation.

This study evaluates AlphaFold protein models for ligand docking, showing they outperform unbound structures and match ligand-bound structures in fragment docking.

The paper introduces two methods to map mimotopes to epitopes, including an ensemble approach and a novel algorithm called MimoTree that handles gaps in sequences.

The paper identifies a druggable site on GRP78 at the SARS-CoV-2 interface and screens compounds to disrupt this interaction, potentially leading to new antiviral therapeutics.

This paper develops machine learning models to identify viral spike proteins and classify respiratory virus families from sequence data with high accuracy.