Integrated Approaches in Pharmacology, Computer Simulations and Machine Learning to Predict Ligand Signaling Pathways via the Anti-Inflammatory Receptor GPR84
Supervisors:
Prof Graeme Milligan, School of Biomolecular Sciences (University of Glasgow)
Dr Irina Tikhonova, School of Pharmacy (Queen's University Belfast)
Summary:
This project involves data generation and analysis to predict ligand signaling pathways in G protein-coupled receptors employing pharmacology, computer simulations and machine learning. You will focus on GPR84, a new promising anti-inflammatory target by profiling series of GPR84 ligands in several functional assays at UoG. You also conduct computer simulations of the receptor-ligand complexes and evaluate various binding properties using supercomputing facilities available at QUB. You will use machine learning to analyze the generated data and make predictions. You will test predictions back in the lab using functional assays and mutagenesis. You will learn cutting-edge computational approaches in data collection, mining, and analysis at the interface of chemistry and biology as well as state-of-the-art binding and functional assays, facilitating skills development in drug design research applicable in academia and industry.