About the project
Free energy calculations using molecular dynamics are widely used in the pharmaceutical industry to predict drug binding affinities. Scaffold hopping presents distinct challenges however. The very large number of possible alternate scaffolds means that the method used must be very efficient, while the potentially large chemical change creates problems with method accuracy. In this project you will address these problems.
The search for drug molecules is risky and expensive. Having identified a high quality and tractable chemical starting point (a hit), further optimisation takes place by modifying the functional groups attached to a central, rigid-ring scaffold. This central scaffold is seldom changed, as optimising new chemistry without a clear view on whether the molecule is effective, is time consuming and expensive. Reliable in-silico predictions of binding affinity for new scaffolds (without wet-lab work) would be a game-changing tool.
Here you will enumerate possible alternate scaffold structures for a known hit molecule. You will use advanced free energy simulations to target these scaffolds quickly, and optimise the binding affinity estimates by incorporating quantum mechanical energies. Finally, the synthetic accessibility of the candidate scaffolds will be assessed to provide a ranked list for synthesis and testing.
You will spend at least 3 months of this 3 years 6 months' studentship working at Kvantify, where you will learn how computer modelling is applied to drug discovery. You will be supervised by Prof Jonathan Essex at the University of Southampton, and by Dr Michael Carter from Kvantify. Both are expert in the development and application of computational methods to drug discovery.
