A method for the quantification of biased signalling at constitutively active receptors

Hall, David A.; Giraldo, Jesús

doi:10.1111/bph.14190

Cited by 18 publications

(13 citation statements)

References 31 publications

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“…Most existing quantitative pharmacological models assume receptor functions along the lines of this operational model-based equation (Trzeciakowski, 1999a; Ehlert et al, 2011; Slack and Hall, 2012; Ehlert, 2015b; Copeland, 2016; Hall and Giraldo, 2018) with some additions needed for constitutive activity (Jenkinson, 2010; Kenakin, 2017; Kenakin, 2018b), including extension such as those by Ehlert and co-workers (Ehlert et al, 2011) or Hall and co-workers (Slack and Hall, 2012; Hall and Giraldo, 2018). However, there are noticeable disadvantages that hinder the widespread use of these K d and τ -based equations, most of which are overcome by the present model.…”

Section: Model Assumptions and Comparisons With Other Receptor Modelsmentioning

confidence: 99%

A Receptor Model With Binding Affinity, Activation Efficacy, and Signal Amplification Parameters for Complex Fractional Response Versus Occupancy Data

Buchwald

2019

Front. Pharmacol.

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In quantitative pharmacology, multi-parameter receptor models are needed to account for the complex nonlinear relationship between fractional occupancy and response that can occur due to the intermixing of the effects of partial receptor activation and post-receptor signal amplification. Here, a general two-state receptor model and corresponding quantitative forms are proposed that unify three distinct processes, each characterized with its own parameter: 1) receptor binding, characterized by K d , the equilibrium dissociation constant used for binding affinity; 2) receptor activation, characterized by an (intrinsic) efficacy parameter ε ; and 3) post-activation signal transduction (amplification), characterized by a gain parameter γ . Constitutive activity is accommodated via an additional ε R0 parameter quantifying the activation of the ligand-free receptor. Receptors can be active or inactive in both their ligand-free and ligand-bound states (two-state receptor theory), but ligand binding alters the likelihood of activation (induced fit). Because structural data now confirm that for most receptors in their active conformation, the small-molecule ligand-binding site is buried inside, straightforward binding to the active form (direct conformational selection) is unlikely. The proposed general equation has parameters that are more intuitive and better suited for optimization by nonlinear regression than those of the operational (Black and Leff) or del Castillo–Katz model. The model provides a unified framework for fitting complex data including a) fractional responses that do not match independently measured fractional occupancies, b) responses measured after partial irreversible inactivation of the “receptor reserve” (Furchgott method), c) fractional responses that are different along distinct downstream pathways (biased agonism), and d) responses with constitutive receptor activity. Furthermore, unlike previous models, the present one can be reduced back for special cases of its parameters to consecutively nested simplified forms that can be used on their own when adequate (e.g., ε R0 = 0, no constitutive activity; γ = 1: E max model for partial agonism; ε = 1: Clark equation).

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Section: Model Assumptions and Comparisons With Other Receptor Modelsmentioning

confidence: 99%

A Receptor Model With Binding Affinity, Activation Efficacy, and Signal Amplification Parameters for Complex Fractional Response Versus Occupancy Data

Buchwald

2019

Front. Pharmacol.

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“…Biased agonism was first "measured" by ranking the potency of different signaling outputs (16,17). Later, the "operational model" was revisited to devise the "bias factor" that, for a given agonist, may be calculated by knowing the maximal effect and the concentration giving the half maximal effect, and taking both a compound and a given pathway as reference (7,(18)(19)(20)(21). Bias factors calculated in such a way do not provide all the information needed for pharmacological and physiological understanding of this singularity, i.e.…”

Section: Introductionmentioning

confidence: 99%

Biased receptor functionality versus biased agonism in G-protein-coupled receptors

Franco

Aguinaga

Jiménez

et al. 2018

Biomolecular Concepts

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Functional selectivity is a property of G-protein-coupled receptors (GPCRs) by which activation by different agonists leads to different signal transduction mechanisms. This phenomenon is also known as biased agonism and has attracted the interest of drug discovery programs in both academy and industry. This relatively recent concept has raised concerns as to the validity and real translational value of the results showing bias; firstly biased agonism may vary significantly depending on the cell type and the experimental constraints, secondly the conformational landscape that leads to biased agonism has not been defined. Remarkably, GPCRs may lead to differential signaling even when a single agonist is used. Here we present a concept that constitutes a biochemical property of GPCRs that may be underscored just using one agonist, preferably the endogenous agonist. “Biased receptor functionality” is proposed to describe this effect with examples based on receptor heteromerization and alternative splicing. Examples of regulation of final agonist-induced outputs based on interaction with β-arrestins or calcium sensors are also provided. Each of the functional GPCR units (which are finite in number) has a specific conformation. Binding of agonist to a specific conformation, i.e. GPCR activation, is sensitive to the kinetics of the agonist-receptor interactions. All these players are involved in the contrasting outputs obtained when different agonists are assayed.

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“…The new analysis somewhat simplifies the determination of the bias factor. The current analysis methods are quite complex 8,[46][47][48][49][50][51][52][53] , involving multiple calculations and in some cases advanced curve fitting (such as simultaneous fitting of multiple ligand concentration-response curves). The kτ method is somewhat simpler, requiring a single bias calculation (the kτ ratio) and employing basic, familiar curve fitting.…”

Section: Discussionmentioning

confidence: 99%

“…Biased agonism quantification relates the capacity of a ligand to activate one pathway relative to one or more other pathways [9][10][11][12] . Numerous methods and scales have been developed and successfully applied 8,[46][47][48][49][50][51][52][53] . One approach is to compare ligand efficacy, i.e.…”

Section: Application To Quantifying Biased Agonismmentioning

confidence: 99%

A new kinetic method for measuring agonist efficacy and ligand bias using high resolution biosensors and a kinetic data analysis framework

Hoare¹,

Tewson

Quinn

et al. 2019

Preprint

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The kinetics/dynamics of signaling are of increasing value for G-protein-coupled receptor therapeutic development, including spatiotemporal signaling and the kinetic context of biased agonism. Effective application of signaling kinetics to developing new therapeutics requires reliable kinetic assays and an analysis framework to extract kinetic pharmacological parameters. Here we describe a platform for measuring arrestin recruitment kinetics to GPCRs using a high quantum yield, genetically encoded fluorescent biosensor, and a new analysis framework to quantify the recruitment kinetics. The sensor enabled high temporal resolution measurement of arrestin recruitment to the angiotensin AT1 and vasopressin V2 receptors. The analysis quantified the initial rate of arrestin signaling (kτ), a biologicallymeaningful kinetic drug efficacy parameter, by fitting time course data using routine curve-fitting methods. Biased agonism was assessed by comparing kτ values for arrestin recruitment with those for Gq signaling via the AT1 receptor. The kτ ratio values were in good agreement with bias estimates from existing methods. This platform potentially improves and simplifies assessment of biased agonism because the same assay modality is used to compare pathways (potentially in the same cells), the analysis method is parsimonious and intuitive, and kinetic context is factored into the bias measurement. Receptor excess over arrestin

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A method for the quantification of biased signalling at constitutively active receptors

Cited by 18 publications

References 31 publications

A Receptor Model With Binding Affinity, Activation Efficacy, and Signal Amplification Parameters for Complex Fractional Response Versus Occupancy Data

A Receptor Model With Binding Affinity, Activation Efficacy, and Signal Amplification Parameters for Complex Fractional Response Versus Occupancy Data

Biased receptor functionality versus biased agonism in G-protein-coupled receptors

A new kinetic method for measuring agonist efficacy and ligand bias using high resolution biosensors and a kinetic data analysis framework

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