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Identification and characterization of plant-derived alkaloids, corydine and corydaline, as novel mu opioid receptor agonists
Pain remains a key therapeutic area with intensive efforts directed toward finding effective and safer analgesics in light of the ongoing opioid crisis. Amongst the neurotransmitter systems involved in pain perception and modulation, the mu-opioid receptor (MOR), a G protein-coupled receptor, repres...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427800/ https://www.ncbi.nlm.nih.gov/pubmed/32796875 http://dx.doi.org/10.1038/s41598-020-70493-1 |
Sumario: | Pain remains a key therapeutic area with intensive efforts directed toward finding effective and safer analgesics in light of the ongoing opioid crisis. Amongst the neurotransmitter systems involved in pain perception and modulation, the mu-opioid receptor (MOR), a G protein-coupled receptor, represents one of the most important targets for achieving effective pain relief. Most clinically used opioid analgesics are agonists to the MOR, but they can also cause severe side effects. Medicinal plants represent important sources of new drug candidates, with morphine and its semisynthetic analogues as well-known examples as analgesic drugs. In this study, combining in silico (pharmacophore-based virtual screening and docking) and pharmacological (in vitro binding and functional assays, and behavioral tests) approaches, we report on the discovery of two naturally occurring plant alkaloids, corydine and corydaline, as new MOR agonists that produce antinociceptive effects in mice after subcutaneous administration via a MOR-dependent mechanism. Furthermore, corydine and corydaline were identified as G protein-biased agonists to the MOR without inducing β-arrestin2 recruitment upon receptor activation. Thus, these new scaffolds represent valuable starting points for future chemical optimization towards the development of novel opioid analgesics, which may exhibit improved therapeutic profiles. |
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