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Molecular Pharmacology

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Research ArticleArticle

A Novel Method for Analyzing Extremely Biased Agonism at G Protein–Coupled Receptors

Edward L. Stahl, Lei Zhou, Frederick J. Ehlert and Laura M. Bohn
Molecular Pharmacology May 2015, 87 (5) 866-877; DOI: https://doi.org/10.1124/mol.114.096503
Edward L. Stahl
Departments of Molecular Therapeutics and Neuroscience, The Scripps Research Institute, Jupiter, Florida (E.L.S., L.Z., L.M.B.); and Department of Pharmacology, School of Medicine, University of California–Irvine, Irvine, California (F.J.E.)
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Lei Zhou
Departments of Molecular Therapeutics and Neuroscience, The Scripps Research Institute, Jupiter, Florida (E.L.S., L.Z., L.M.B.); and Department of Pharmacology, School of Medicine, University of California–Irvine, Irvine, California (F.J.E.)
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Frederick J. Ehlert
Departments of Molecular Therapeutics and Neuroscience, The Scripps Research Institute, Jupiter, Florida (E.L.S., L.Z., L.M.B.); and Department of Pharmacology, School of Medicine, University of California–Irvine, Irvine, California (F.J.E.)
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Laura M. Bohn
Departments of Molecular Therapeutics and Neuroscience, The Scripps Research Institute, Jupiter, Florida (E.L.S., L.Z., L.M.B.); and Department of Pharmacology, School of Medicine, University of California–Irvine, Irvine, California (F.J.E.)
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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.

Footnotes

    • Received October 21, 2014.
    • Accepted February 13, 2015.
  • This work was supported by a grant from the National Institutes of Health National Institute on Drug Addiction [Grant R01-DA031927].

  • dx.doi.org/10.1124/mol.114.096503.

  • ↵Embedded ImageThis article has supplemental material available at molpharm.aspetjournals.org.

  • Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics
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Molecular Pharmacology: 87 (5)
Molecular Pharmacology
Vol. 87, Issue 5
1 May 2015
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Research ArticleArticle

A Competitive Model for Biased GPCR Agonists

Edward L. Stahl, Lei Zhou, Frederick J. Ehlert and Laura M. Bohn
Molecular Pharmacology May 1, 2015, 87 (5) 866-877; DOI: https://doi.org/10.1124/mol.114.096503

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Research ArticleArticle

A Competitive Model for Biased GPCR Agonists

Edward L. Stahl, Lei Zhou, Frederick J. Ehlert and Laura M. Bohn
Molecular Pharmacology May 1, 2015, 87 (5) 866-877; DOI: https://doi.org/10.1124/mol.114.096503
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