The majority of drugs are prescribed on the premise that their desired and undesired effects are well characterised. However, the mechanisms underlying these effects can be elusive and are of interest to the pharmaceutical industry in terms of rational drug design. G protein-coupled receptors are a significant class of drug target that are capable of influencing multiple signalling processes, and downstream effects, simultaneously through a variety of effectors, such as G proteins or –β-arrestins. The effector activated by a given receptor is often a function of the ligand. This is termed functional selectivity and can contribute to adverse drug effects. Understanding functional selectivity in a mammalian setting is hindered by cross-talk between many competing signalling components. The Sc. cerevisiae pheromone response can be modified to isolate individual mammalian receptor- G protein interactions. Therefore, this simple organism represents an excellent tool to study functional selectivity. Further, the simplicity of this organism allows this pathway to be mathematically modelled. By applying mathematical models to mammalian GPCR signalling in yeast it is possible to extract experimentally inaccessible quantitative parameters underlying functional selectivity. This interdisciplinary approach to pharmacological mechanisms is an example of systems pharmacology. Here a systems pharmacology approach is applied to adenosine receptor signalling in yeast with a view to understanding the contribution of the ligand, receptor and G protein to functional selectivity. The first stage of this process was expression and characterisation of adenosine A1R, A2AR, A2BR and A3R subtypes in yeast. Here, the A1R and A2R subtypes were shown to be functional in yeast, but the A3R response was limited. The A1R signals through G proteins representing the inhibitory G αi family in yeast, while the A2AR and A2BR signal through both inhibitory and stimulatory G protein equivalents. Here ligand bias is quantified but further extended to describe adenosine receptor selectivity. Further, the yeast system was used to inform novel fluorescent compound development. Fluorescent ligand-binding rates would ultimately inform modelling studies. A minimal mathematical framework was developed to described A1R signalling in yeast. Ordinary differential equation models recreate dynamic cellular processes. Here an ODE model was applied to experimental time course data to predict rate constants throughout the yeast G protein cycle in the presence of the mammalian A1R. This model predicts that G protein subtype influences the ligand-receptor-G protein interactions of the A1R in yeast. Further modification of the system and fluorescent technologies may help validate these predictions.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:678711 |
| Date | January 2015 |
| Creators | Knight, Anthony |
| Publisher | University of Warwick |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://wrap.warwick.ac.uk/75201/ |
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