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Review
. 2018 Apr;17(4):243-260.
doi: 10.1038/nrd.2017.229. Epub 2018 Jan 5.

Biased signalling: from simple switches to allosteric microprocessors

Affiliations
Review

Biased signalling: from simple switches to allosteric microprocessors

Jeffrey S Smith et al. Nat Rev Drug Discov. 2018 Apr.

Abstract

G protein-coupled receptors (GPCRs) are the largest class of receptors in the human genome and some of the most common drug targets. It is now well established that GPCRs can signal through multiple transducers, including heterotrimeric G proteins, GPCR kinases and β-arrestins. While these signalling pathways can be activated or blocked by 'balanced' agonists or antagonists, they can also be selectively activated in a 'biased' response. Biased responses can be induced by biased ligands, biased receptors or system bias, any of which can result in preferential signalling through G proteins or β-arrestins. At many GPCRs, signalling events mediated by G proteins and β-arrestins have been shown to have distinct biochemical and physiological actions from one another, and an accurate evaluation of biased signalling from pharmacology through physiology is crucial for preclinical drug development. Recent structural studies have provided snapshots of GPCR-transducer complexes, which should aid in the structure-based design of novel biased therapies. Our understanding of GPCRs has evolved from that of two-state, on-and-off switches to that of multistate allosteric microprocessors, in which biased ligands transmit distinct structural information that is processed into distinct biological outputs. The development of biased ligands as therapeutics heralds an era of increased drug efficacy with reduced drug side effects.

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Conflict of interest statement

Conflict of interest statement

R.J.L. is a cofounder and shareholder of Trevena.

Figures

Figure 1
Figure 1. Biased signaling can be encoded through three general mechanisms
(A) A balanced agonist binding to a balanced receptor in an unbiased system may display equivalent potencies for two different pathways, such as G protein and βarrestin, under assay conditions with similar amplification levels. (B) Biased agonism, or ‘druggable’ biased signaling, is encoded through the ligand. The ligand-receptor-effector complex generates distinct conformation(s) that preferentially signal through certain pathways relative to other pathways (βarrestin biased relative to G protein in this example). Unlike the balanced agonist in panel (A), a βarrestin biased agonist may display a left shift in potency relative to the G protein pathway under the same assay conditions. (C) Biased receptors, such as G protein-biased receptors that lack C-terminal phosphorylation sites necessary for βarrestin recruitment, signal preferentially through one pathway relative to another (G protein biased signaling in this example) despite being stimulated by a balanced agonist. Similar to biased ligands, biased receptors will also display a left shift of one pathway relative to another that may not be observed at an unbiased receptor under the same assay conditions. (D) System bias may be due to differential expression of signaling effectors or other cofactors. For example, higher expression of certain GRK and/or βarrestin isoforms can bias signaling towards the βarrestin pathway (shown here). Alternatively, lack of GRKs or βarrestins can bias signaling towards the G protein pathway (not shown).
Figure 2
Figure 2. Drug discovery strategies and physiological consequences of biased signalling
(A) The μ opioid receptor is a common drug target for analgesia. The endogenous ligand enkphalin (ENK) is unbiased (‘balanced’) with respect to G protein and βarrestin signaling. However, current μopioid selective agonists, such as morphine, that provide pain relief also cause adverse effects including respiratory depression, constipation, tolerance, and dependence. Both animal and human studies suggest that G protein signaling primarily mediates the analgesic efficacy, while βarrestin signaling mediates many of the adverse effects. Strongly G protein biased agonists, such as TRV130 and PZM21, may therefore provide clinical superiority to currently available agonists. (B) Relative to the wild-type receptor, the naturally occurring human vasopressin 2 receptor mutation R137H results in βarrestin biased signaling and is associated with familial nephrogenic diabetes insipidus. The vasopression R137H receptor variant is constitutively phosphorylated. This constitutive phosphorylation promotes greater βarrestin recruitment and internalization, even in the absence of arginine vasopressin (AVP, also known as antidiuretic hormone), compared to the wild-type receptor. Presumably, a significant reduction in vasopressin mediated Gαs signaling is sufficient to diminish aquaporin channel insertion into the renal collecting ducts, impeding urine concentration through reduced water resorption and leading to the clinical diagnosis of nephrogenic diabetes insipidus.
Figure 3
Figure 3. General approach to characterizing biased ligands
First, assays for different pathways should be chosen with the goal of minimizing differences in signal amplification. Such assay selection optimizes the window for identifying biased agonists (see example of a bias plot below). Time- and cell-dependent data should be obtained to ensure no significant kinetic or cell-specific effects. To qualitatively identify biased agonists, construct a ‘bias plot’ by, for example, graphing βarrestin activity on the x axis and G protein activity on the y axis (each normalized to pathway specific maximal signals in this example). Deviations from the reference agonist suggest the presence of ligand bias. If no biased signaling is observed on a bias plot, then it is unlikely that true biased signaling is present (even if calculated bias factors are statistically significant). Multiple approaches can be used to calculate bias factors (see text), such as a method based on intrinsic relative activities (calculator available online, at https://biasedcalculator.shinyapps.io/calc/). After identification and quantification of ligand bias, the physiological implications of such signaling can be tested in relevant cell lines or primary cells. Biased signaling properties can then be confirmed in the receptor from a relevant model organism and subsequently evaluated in the animal model for safety and efficacy.

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