ArticleMolecular pharmacology2015
A novel method for analyzing extremely biased agonism at G protein-coupled receptors.
Article in Molecular pharmacology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Kinetic Benefit(s) of Allosteric Receptor Blockade by Positive Allosteric Modulator Antagonists.ACS pharmacology & translational science · 2026Review
- Triazole 187 is a biased KOR agonist that suppresses itch without sedation and induces anxiolytic-like behaviors in mice.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
- Review
- Article
- Bidirectional Modification of aACS central science · 2025Article
- Biased Opioid Receptor Agonists: Balancing Analgesic Efficacy and Side-Effect Profiles.International journal of molecular sciences · 2025Review
- Limitations and potential of κOR biased agonists for pain and itch management.Neuropharmacology · 2024Review
- Quantitative receptor model for responses that are left- or right-shifted versus occupancy (are more or less concentration sensitive): the SABRE approach.Frontiers in pharmacology · 2023Article
- Community guidelines for GPCR ligand bias: IUPHAR review 32.British journal of pharmacology · 2022Review
- Kappa Opioid Receptor Antagonists as Potential Therapeutics for Mood and Substance Use Disorders.Handbook of experimental pharmacology · 2022Article
- Biased Ligands at the Kappa Opioid Receptor: Fine-Tuning Receptor Pharmacology.Handbook of experimental pharmacology · 2022Review
- G protein signaling-biased mu opioid receptor agonists that produce sustained G protein activation are noncompetitive agonists.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Pharmacological Characterization of Low Molecular Weight Biased Agonists at the Follicle Stimulating Hormone Receptor.International journal of molecular sciences · 2021Article
- Strategies for DevelopingThe Journal of pharmacology and experimental therapeutics · 2020Review
- A single unified model for fitting simple to complex receptor response data.Scientific reports · 2020Article
- Disconnect between signalling potency and in vivo efficacy of pharmacokinetically optimised biased glucagon-like peptide-1 receptor agonists.Molecular metabolism · 2020Article
- A cellular perspective of bias at G protein-coupled receptors.Protein science : a publication of the Protein Society · 2020Review
- The Influence of Peptide Context on Signaling and Trafficking of Glucagon-like Peptide-1 Receptor Biased Agonists.ACS pharmacology & translational science · 2020Article
- Application of Fluorine- and Nitrogen-Walk Approaches: Defining the Structural and Functional Diversity of 2-Phenylindole Class of Cannabinoid 1 Receptor Positive Allosteric Modulators.Journal of medicinal chemistry · 2020Article
- Functional Selectivity and Antinociceptive Effects of a Novel KOPr Agonist.Frontiers in pharmacology · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
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 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. Although 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 article, 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 κ 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.