PhD in Biomedical Engineering

When we are ill we will often take a drug that we hope will make us better, but many drugs that are very effective at making us better also have side-effects that can be much less desirable. One reason why this may happen is that the drug activates (or deactivates) several different biological signalling pathways simultaneously, and there is evidence for this in a particular class of molecules called G protein coupled receptors (GPCRs) which are often involved in a large number of signalling pathways. Elimination of side effects requires us to adjust the chemical structure of the drug to trigger signalling pathways much more selectively. This requires us to understand the molecular basis of drug action in much more detail. Recent work in the supervisor’s lab has used machine learning techniques on a large set of molecular docking poses to identify key interactions between a drug and its target that are associated with the triggering of specific biological pathways, and to construct a uniquely detailed structure-activity relationship that identifies how small changes to a drug can radically change their pharmacological activity and thus help to guide the drug discovery process. The next step is to extend this work to look at much larger numbers of drug targets using large publicly available datasets to refine and extend our technique and generalise our early findings.