Computational and experimental investigation of G protein-coupled receptor signalling mechanisms

Abstract

G Protein-Coupled Receptors (GPCRs) are 7-transmembrane domain proteins. These receptors translate extracellular stimuli into cellular responses through heterotrimeric G proteins and β-arrestin proteins. These receptors are of considerable therapeutic interest, targeted by over 500 drugs approved by the Food and Drug Administration (FDA). Understanding the signalling transduction of GPCRs aids the development of therapeutics for various diseases, including cardiovascular disease, obesity, neurological disorders, pain and cancer. The pharmacological study of GPCRs involves examining their interaction and responses to endogenous and exogenous ligands. New technologies and experimental techniques have markedly advanced the frontier of this field, illuminating underlying signalling mechanisms of GPCRs. Bioluminescence Resonance Energy Transfer (BRET)-based techniques were used to probe the underlying signalling mechanisms of the Calcitonin Receptor-Like Receptor (CLR). Results revealed a previously unknown interaction between CLR, G protein Receptor Kinases (GRKs), and β-arrestins. Further investigation into CLR’s desensitisation by β-arrestins revealed interesting and unexpected results. Using Förster Resonance Energy Transfer (FRET)-based techniques, the functional expression of CLR in human primary endothelial cells was investigated. This work revealed the expression of the Adrenomedullin (AM) Receptor (AMR) in endothelial cells from various tissues, extending the conclusions of previous work concerning the AMR to tissues in the heart, lungs and cardiovascular system. New experimental techniques utilising luminescence, BRET, and FRET technologies have facilitated the exploration of cellular processes at higher mechanistic resolutions. Modelling these data enables the quantification of these cellular responses, improving the comparability and interpretability of data. Mechanistic modelling, in particular, enables the generation of precise and testable hypotheses. The clarity and explicitness oaered by this approach make it ideally suited to understanding the mechanisms of GPCR signalling. The Parathyroid Hormone Receptor 1 (PTH1R) was mechanistically modelled to investigate mutations in GNAS, the gene encoding the Gαs protein. These mutations are linked to the rare iiimetabolic disease pseudohypoparathyroidism (PHP) type 1c (PHP1c). The modelling involved abstraction of the experimental system into a model, input of this model into a computational framework for simulations, and then alignment of simulation data with experimental data. Data alignment and fitting gave rise to different qualitative and quantitative approaches. Previously, the exact nature of the mutations’ perturbed signalling was unknown. Mechanistic modelling, in combination with experimental data, revealed distinct explanations for each mutation. Models then predicted the implications of these explanations, producing various predictions. This thesis concludes that mechanistic modelling with modern, high-precision experimental techniques is a potent approach to understanding GPCR pharmacology.