Abstract
G protein-coupled receptors (GPCRs) interact with multiple intracellular effector proteins such that different ligands may preferentially activate one signal pathway over others, a phenomenon known as signaling bias. Signaling bias can be quantified to optimize drug selection for preclinical research. Here, we describe moderate-throughput methods to quantify signaling bias of known and novel compounds. In the example provided, we describe a method to define cannabinoid-signaling bias in a cell culture model of Huntington's disease (HD). Decreasing type 1 cannabinoid receptor (CB1) levels is correlated with chorea and cognitive deficits in HD. There is evidence that elevating CB1 levels and/or signaling may be beneficial for HD patients while decreasing CB1 levels and/or signaling may be detrimental. Recent studies have found that G alpha(i/o)-biased CB1 agonists activate extracellular signal-regulated kinase (ERK), increase CB1 protein levels, and improve viability of cells expressing mutant huntingtin. In contrast, CB1 agonists that are beta-arrestin1-biased were found to reduce CB1 protein levels and cell viability. Measuring agonist bias of known and novel CB1 agonists will provide important data that predict CB1-specific agonists that might be beneficial in animal models of HD and, following animal testing, in HD patients. This method can also be applied to study signaling bias for other GPCRs.