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Updated: Mar 15, 2026

Quantifying Agonist Activity at G Protein-coupled Receptors
Published on: December 26, 2011
A Pluridimensional View of Biased Agonism
Claudio M Costa-Neto1, Lucas T Parreiras-E-Silva2, Michel Bouvier1
1Department of Biochemistry and Immunology, Ribeirao Preto Medical School, University of São Paulo, Ribeirao Preto, Brazil (C.M.C.-N., L.T.P.-S.); and Department of Biochemistry and Molecular Medicine and Institute for Research in Immunology and Cancer, University of Montréal, Montréal, Canada (L.T.P.-S., M.B.) claudio@fmrp.usp.br michel.bouvier@umontreal.ca.
Abstract:
When studying G protein-coupled receptor (GPCR) signaling and ligand-biased agonism, at least three dimensional spaces must be considered, as follows: 1) the distinct conformations that can be stabilized by different ligands promoting the engagement of different signaling effectors and accessory regulators; 2) the distinct subcellular trafficking that can be conferred by different ligands, which results in spatially distinct signals; and 3) the differential binding kinetics that maintain the receptor in specific conformation and/or subcellular localization for different periods of time, allowing for the engagement of distinct signaling effector subsets. These three pluridimensional aspects of signaling contribute to different faces of functional selectivity and provide a complex, interconnected way to define the signaling profile of each individual ligand acting at GPCRs. In this review, we discuss how each of these aspects may contribute to the diversity of signaling, but also how they shed light on the complexity of data analyses and interpretation. The impact of phenotype variability as a source of signaling diversity, and the influence of novel and more sensitive assays in the detection and analysis of signaling pluridimensionality, is also discussed. Finally, we discuss perspectives for the use of the concept of pluridimensional signaling in drug discovery, in which we highlight future predictive tools that may facilitate the identification of compounds with optimal therapeutic and safety properties based on the signaling signatures of drug candidates.
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