Drug Discovery and Medicinal Chemistry

Artificial Intelligence is revolutionising drug discovery, allowing us to develop better medicines faster. Research at Queen Mary includes the development of generative models for drug discovery in skeletal and cardiac muscle disease, deep learning-based methods for the prediction of peptide-receptor interactions, machine learning and druggability prediction for target prioritisation, and transfer learning for drug discovery. Queen Mary hosts the AI for Drug Discover Doctoral Training Programme funded by the BBSRC. 
 

Examples of QM staff working in this field: 

• Prof Conrad Bessant is head of the AI for Drug Discover Doctoral Training Programme  His research interest is the automation of scientific discovery in the biomedical domain using machine learning, logic modelling, network science and Bayesian inference. 

• Dr Arianna Fornili is Director of the Artificial Intelligence for Drug Discovery MSc programme and specializes in computational protein dynamics modelling to understand function, uncover disease mechanisms, and design therapeutic molecules. 

• Dr Wojciech Kopec is a Lecturer in Computational Pharmaceutical Chemistry and works on biophysical mechanisms and pharmacology of ion channels using computational approaches. 

Research Centres:  
Centre for Chemical Research; Centre for Molecular Cell Biology