Molecular recognition and drug discovery
Our research interests are broadly in the areas of molecular recognition and drug discovery. We use computational methodologies to understand at a molecular level a wide variety of biological processes and phenomena. We develop predictive models that can be used to design new molecules in silico. We seek to understand what factors contribute to success and failure in drug discovery.
A significant proportion of our work is done in collaboration with other drug discovery scientists from academia and industry. Current projects include the use of computer simulations to predict organ transplant outcomes, using machine learning to predict bioactivity profiles, target tractability prediction, structure-based drug discovery, and the use of text mining to identify bioactivity data from a variety of sources.