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A Simple Method for Quantifying Functional Selectivity and Agonist Bias

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Kenakin, Terry, Watson, Christian, Muniz-Medina, Vanessa, Christopoulos, Arthur, Novick, Steven·2012·ACS Chemical Neuroscience

Abstract

Activation of seven-transmembrane (7TM) receptors by agonists does not always lead to uniform activation of all signaling pathways mediated by a given receptor. Relative to other ligands, many agonists are "biased" toward producing subsets of receptor behaviors. A hallmark of such "functional selectivity" is cell type dependence; this poses a particular problem for the profiling of agonists in whole cell test systems removed from the therapeutic one(s). Such response-specific cell-based variability makes it difficult to guide medicinal chemistry efforts aimed at identifying and optimizing therapeutically meaningful agonist bias. For this reason, we present a scale, based on the Black and Leff operational model, that contains the key elements required to describe 7TM agonism, namely, affinity (K(A) (-1)) for the receptor and efficacy (τ) in activating a particular signaling pathway. Utilizing a "transduction coefficient" term, log(τ/K(A)), this scale can statistically evaluate selective agonist effects in a manner that can theoretically inform structure-activity studies and/or drug candidate selection matrices. The bias of four chemokines for CCR5-mediated inositol phosphate production versus internalization is quantified to illustrate the practical application of this method. The independence of this method with respect to receptor density and the calculation of statistical estimates of confidence of differences are specifically discussed.

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Metadata

Authors
Kenakin, T., Watson, C., Muniz-Medina, V., Christopoulos, A., & Novick, S.
Venue
ACS Chemical Neuroscience
Published
2012-01-23
Volume
3
Issue
3
Pages
193-203
ISSN
1948-7193 (ISSN-L)
OpenAlex
W138314167
Cited by
484
References
0
FWCI
7.76
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A Simple Method for Quantifying Functional Selectivity and Agonist Bias. https://app.cochat.ai/papers/10.1021/cn200111m
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Kenakin, T., Watson, C., Muniz-Medina, V., Christopoulos, A., & Novick, S. (2012). A Simple Method for Quantifying Functional Selectivity and Agonist Bias. ACS Chemical Neuroscience. https://doi.org/10.1021/cn200111m

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