TY - JOUR T1 - A Novel Method for Analyzing Extremely Biased Agonism at G Protein-Coupled Receptors JF - Molecular Pharmacology JO - Mol Pharmacol DO - 10.1124/mol.114.096503 SP - mol.114.096503 AU - Edward L. Stahl AU - Lei Zhou AU - Fred J. Ehlert AU - Laura M. Bohn Y1 - 2015/01/01 UR - http://molpharm.aspetjournals.org/content/early/2015/02/13/mol.114.096503.abstract N2 - Seven transmembrane receptors were originally named and characterized based on their ability to couple to heterotrimeric G proteins. The assortment of coupling partners for G protein-coupled receptors (GPCR) has subsequently expanded to include other effectors (most notably the βarrestins). This diversity of partners available to the receptor has prompted the pursuit of ligands that selectively activate only a subset of the available partners. A biased or functionally selective ligand may be able to distinguish between different active states of the receptor and this would result in the preferential activation of one signaling cascade more than another. While application of the "standard" operational model for analyzing ligand bias is useful and suitable, in most cases, there are limitations that arise when the biased agonist fails to induce a significant response in one of the assays being compared. In this manuscript we describe a quantitative method for measuring ligand bias that is particularly useful for such cases of extreme bias. Using simulations and experimental evidence from several kappa opioid receptor agonists, we illustrate a "competitive" model for quantitating the degree and direction of bias. By comparing the results obtained from the competitive model with the standard model we demonstrate that the competitive model expands the potential for evaluating the bias of very partial agonists. We conclude the competitive model provides a useful mechanism for analyzing the bias of partial agonists that exhibit extreme bias. ER -