We use computational modelling to understand biological processes, such as enzyme catalysis and protein-ligand interactions. In collaboration with experimental groups, these mechanistic insights enable rational design and optimisation of protein inhibitors and inform design strategies of new active molecules.
Biomolecular Modelling
Relevant Publications
H. T. H. Chan, L. Brewitz, P. Lukacik, C. Strain-Damerell, M. A. Walsh, C. J. Schofield, F. Duarte. Studies on the selectivity of the SARS-CoV-2 papain-like protease reveal the importance of the P2' proline of the viral polyprotein. RSC Chem. Biol., 2023, 5(2), 17-130
H. T. H. Chan, A. S. F. Oliveira, C. J. Schofield, A. J. Mulholland, F. Duarte, Dynamical nonequilibrium molecular dynamics simulations identify allosteric sites and positions associated with drug resistance in the SARS-CoV-2 main protease. JACS Au 2023, 3, 6, 1767–1774.
H. T. H. Chan, M. A. Moesser, R. K. Walters, T. R. Malla, R. M. Twidale, Tobias John, H. M. Deeks, T. Johnston-Wood, V. Mikhailov, R. B. Sessions, W.Dawson, E. Salah, P. Lukacik, C. Strain-Damerell, C. D.Owen, T. Nakajima, K.Świderek, A. Lodola, V. Moliner, D.R. Glowacki, M. A. Walsh, C. J. Schofield, L. Genovese, D. K. Shoemark, A. J. Mulholland, F. Duarte, G. M. Morris. Discovery of SARS-CoV-2 Mpro Peptide Inhibitors from Modelling Substrate and Ligand Binding. Chem. Sci. 2021, , 12, 13686-13703.
