Premium
Identifying ligand‐specific signalling within biased responses: focus on δ opioid receptor ligands
Author(s) -
Charfi I,
Audet N,
Bagheri Tudashki H,
Pineyro G
Publication year - 2015
Publication title -
british journal of pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.432
H-Index - 211
eISSN - 1476-5381
pISSN - 0007-1188
DOI - 10.1111/bph.12705
Subject(s) - functional selectivity , g protein coupled receptor , opioid receptor , confounding , signalling , opioid , neuroscience , computational biology , analgesic , focus (optics) , bioinformatics , receptor , medicine , pharmacology , computer science , psychology , biology , physics , optics , microbiology and biotechnology
Opioids activate GPCRs to produce powerful analgesic actions but at the same time induce side effects and generate tolerance, which restrict their clinical use. Reducing this undesired response profile has remained a major goal of opioid research and the notion of 'biased agonism' is raising increasing interest as a means of separating therapeutic responses from unwanted side effects. However, to fully exploit this opportunity, it is necessary to confidently identify biased signals and evaluate which type of bias may support analgesia and which may lead to undesired effects. The development of new computational tools has made it possible to quantify ligand-dependent signalling and discriminate this component from confounders that may also yield biased responses. Here, we analyse different approaches to identify and quantify ligand-dependent bias and review different types of confounders. Focus is on δ opioid receptor ligands, which are currently viewed as promising agents for chronic pain management.