Receptor bias (revision 5)
Old revision·18:58, 22 Oct 2024·CommaCarys
| Receptor bias | |
|---|---|
| Also called | Biased agonism, functional selectivity |
| At the GLP-1 receptor | cAMP versus β-arrestin recruitment |
| Measured as | A bias factor, relative to a reference agonist |
| Topic infobox · conventions | |
Receptor bias, also termed biased agonism or functional selectivity, is the tendency of an agonist to favour one downstream signalling pathway over another at the same receptor. It arises because different agonists stabilise different receptor conformations, and those conformations couple differently to the available transducers.[1]
At the GLP-1 receptor the pathways usually compared are cAMP accumulation, which mediates the insulinotropic effect, and β-arrestin recruitment, which terminates G-protein signalling and drives receptor internalisation.[1]
Bias is quantified as a bias factor relative to a reference agonist, and the number depends on the reference chosen, the cell system, the readout and the incubation time. Bias factors from different publications are not comparable.[2]
The concept
[edit]Classical receptor theory treats an agonist's effect as a single efficacy applied to a single pathway. Biased agonism replaces this with a vector: an agonist has an efficacy for each transducer, and the ratio between them is what "bias" names.[2]
Quantification requires care because potency and efficacy differences that are not bias — receptor reserve differences between assays, for instance — can masquerade as it. Operational models exist to separate the two and their assumptions are not always met.[2]
The concept is real and well supported at the level of receptor conformation. What is contested is whether measured bias predicts anything clinically.[1]
References
- ^ a b c Jones B, Buenaventura T, Kanda N, et al. "Targeting GLP-1 receptor trafficking to improve agonist efficacy." Nature Communications 9:1602 (2018). PMID 29686245.
- ^ a b c Kenakin T, Christopoulos A. "Signalling bias in new drug discovery: detection, quantification and therapeutic impact." Nature Reviews Drug Discovery 12(3):205–216 (2013). PMID 23411724.