Madhushika Silva

The paper uses machine learning-augmented virtual screening to discover a novel series of Mac1 inhibitors for SARS-CoV-2 NSP3, validated by experimental assays and crystallography.

The paper develops a chemical probe targeting the USP16 zinc-finger ubiquitin-binding domain and evaluates its selectivity and activity in cellular assays.

This study introduces E-ASMS, a method to detect weak binders and assess enantioselectivity, identifying 16 binders across 12 human protein targets with confirmed binding mechanisms.

The paper identifies UNC10013, a covalent ligand targeting SETDB1's 3TD domain, which reduces methyltransferase activity and shows selectivity in cells.

The paper develops a resource for discovering ligands for WDR proteins using experimental and computational methods, leading to the identification of drug-like ligands for 9 out of 20 targets.