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Br J Pharmacol. 2015 Sep;172(17):4238-53. doi: 10.1111/bph.13217. Epub 2015 Jul 21.

Gaddum Memorial Lecture 2014: receptors as an evolving concept: from switches to biased microprocessors.

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1
Department of Pharmacology, University of North Carolina School of Medicine, Chapel Hill, NC, USA.

Erratum in

  • Br J Pharmacol. 2016 Jan;173(2):412.

Abstract

This review is based on the JR Vane Medal Lecture presented at the BPS Winter Meeting in December 2014 by T. Kenakin. A recording of the lecture is included as supporting information and can also be viewed online here: https://www.youtube.com/watch?v=xrP81AQ8l-8. Pharmacological models used to describe drug agonism and antagonism have evolved over the past 20 years from a parsimonious model describing single active and inactive receptor states to models of multiconformational receptor systems modified by ligand conformational selection. These latter models describe the observed, presently underexploited, pharmacological mechanism of ligand-directed biased signalling. Biased signals can be quantified with transduction coefficients (ΔΔLog(τ/KA) values), a scale grounded in the Black/Leff operational model; this enables the optimization of biased profiles through medicinal chemistry. The past decades have also brought the availability of new technologies to measure multiple functional effects mediated by seven transmembrane receptors. These have confirmed that drugs can have many efficacies, which may be collaterally linked, that is there is no linear sequence of activities required. In addition, new functional screening assays have introduced increasing numbers of allosteric ligands into drug discovery. These molecules are permissive (they do not necessarily preclude endogenous signalling in vivo); therefore, they may allow better fine tuning of pathological physiology. The permissive quality of allosteric ligands can also change the quality of endogenous signalling efficacy ('induced bias') as well as the quantity of signal; in this regard, indices related to ΔΔLog(τ/KA) values (namely ΔLog(αβ) values) can be used to quantify these effects for optimization in the drug discovery process. All of these added scales of drug activity will, hopefully, allow better targeting of candidate molecules towards therapies.

PMID:
26075971
PMCID:
PMC4556465
DOI:
10.1111/bph.13217
[Indexed for MEDLINE]
Free PMC Article

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