Pharmacological Characterization of Levorphanol, a G-Protein Biased Opioid Analgesic

左吗啡醇(一种G蛋白偏向性阿片类镇痛药)的药理学特征

阅读:1

Abstract

BACKGROUND: Levorphanol is a potent analgesic that has been used for decades. Most commonly used for acute and cancer pain, it also is effective against neuropathic pain. The recent appreciation of the importance of functional bias and the uncovering of multiple µ opioid receptor splice variants may help explain the variability of patient responses to different opioid drugs. METHODS: Here, we evaluate levorphanol in a variety of traditional in vitro receptor binding and functional assays. In vivo analgesia studies using the radiant heat tail flick assay explored the receptor selectivity of the responses through the use of knockout (KO) mice, selective antagonists, and viral rescue approaches. RESULTS: Receptor binding studies revealed high levorphanol affinity for all the μ, δ, and κ opioid receptors. In S-GTPγS binding assays, it was a full agonist at most µ receptor subtypes, with the exception of MOR-1O, but displayed little activity in β-arrestin2 recruitment assays, indicating a preference for G-protein transduction mechanisms. A KO mouse and selective antagonists confirmed that levorphanol analgesia was mediated through classical µ receptors, but there was a contribution from 6 transmembrane targets, as illustrated by a lower response in an exon 11 KO mouse and its rescue with a virally transfected 6 transmembrane receptor splice variant. Compared to morphine, levorphanol had less respiratory depression at equianalgesic doses. CONCLUSIONS: While levorphanol shares many of the same properties as the classic opioid morphine, it displays subtle differences that may prove helpful in its clinical use. Its G-protein signaling bias is consistent with its diminished respiratory depression, while its incomplete cross tolerance with morphine suggests it may prove valuable clinically with opioid rotation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。