Computer-aided drug design, chemical biology, biomolecular interactions, computer simulations and statistical mechanics.
|Left: Computation of free energies of binding for host/guest association using thermodynamic cycles. Right: Computed water-mediated interaction in a protein-ligand complex.|
Molecular recognition, the association of two or more molecules, is fundamental to life. A greater understanding of molecular recognition also enables profound technological advances in healthcare and engineering. A central challenge for molecular science is therefore to advance our understanding of the physical principles of molecular recognition to the level where biological processes, such as protein-ligand association, can be quantitatively predicted and engineered. Research in the group focuses on the development of molecular simulation methods to quantify the structure, dynamics and thermodynamics of molecular recognition processes in biomolecular systems that are of pharmaceutical relevance.
|Left: Design of a b -peptide inhibitor of the interaction between the proteins p53 & MDM2. Right: Evaluation of the affinity of the best designs with a fluorescence polarization assay.|
To be relevant to pre-clinical drug discovery, current computational methods trade-off rigour for speed. New computational methods are needed to reliably and efficiently design drug-like ligands targeting a wide range of biological molecules. The group leverages high-performance computing resources and develops approximate computer-aided drug design methods inspired by detailed molecular simulations to improve on the state-of-the art and yet maintain a throughput compatible with the fast pace of pre-clinical drug discovery. Joint computational and experimental efforts undertaken with collaborators to target medically relevant systems provide opportunities to critically assess the effectiveness of computational modelling.