新型阿片类镇痛药的研发进展
Research progress of novel opioid analgesics
贺春波 1王丹 2杨淑佳 2周开文 2邓怡平 1董守良3
作者信息
- 1. 德州学院药学院,山东 德州 253023;新型药用辅料与缓控释制剂山东省工程研究中心,山东 德州 253023
- 2. 新型药用辅料与缓控释制剂山东省工程研究中心,山东 德州 253023;德州学院健康医学院,山东 德州 253023
- 3. 兰州大学生命科学学院动物学与生物医学系,兰州 730000;甘肃省新药临床前研究重点实验室,兰州 730000
- 折叠
摘要
阿片类镇痛药是目前已知疗效最好的镇痛药,然而其便秘、耐受和成瘾等毒副作用严重限制了其临床应用.随着对阿片受体信号转导机制的深入认知和药物设计技术的不断进步,研究者们近年来尝试了许多有前景、不同于传统的改造吗啡骨架结构的全新方法,致力于开发低毒高效的阿片类镇痛药.本文聚焦于目前比较主流的偏向性激动、"一药多靶"和外周激动3种新型研发策略,介绍了各个策略实现镇痛活性与不良反应相对分离的基本原理,并结合相应代表性药物的最新研究进展进行简要综述.其中,近期获批上市的新型阿片类镇痛药奥赛利定和泰吉利定都是偏向性μ阿片受体激动剂,Cebranopadol是典型的"一药多靶"镇痛药,NFEPP是外周阿片受体激动剂的代表性药物.上述几种研发策略相辅相成,为阿片类镇痛新药的研发提供了借鉴与参考.
Abstract
Opioid analgesics are currently known as the best analgesics.However,toxicity and side effects such as constipation,tolerance and addiction severely limit their clinical application.With the in-depth understanding of the signal transduction mechanism of opioid receptors and the continuous advancement of drug design technology,researchers have managed to develop many promising new methods to get low-toxic and more efficient opioid analgesics,which are different from the traditional morphine skeleton structure modifications.This article focuses on three new research strategies of G-protein biased activation,"one drug-multiple targets"and peripheral activation.The basic principles of relative separation of analgesic activity and adverse drug reaction by each strategy are introduced,and the latest research progress of representative drugs is briefly reviewed.Among them,the recently approved novel opioid analgesics oliceridine and tegileridine are G-protein biased μ-opioid receptor agonists,Cebranopadol is a typical"one drug-multiple targets"analgesic,and NFEPP is a representative drug of peripheral opioid receptor agonists.The above several strategies complement each other and provide reference for the development of new opioid analgesic drugs.
关键词
阿片类镇痛药/偏向性激动剂/一药多靶/外周激动剂/新药研发Key words
opioid analgesic/biased agonist/one drug-multiple targets/peripheral agonist/new drug development引用本文复制引用
基金项目
山东省自然科学基金项目(ZR2023QH304)
德州学院科学研究基金项目(2021xjrc212)
出版年
2024
国家科技期刊平台
NSTL
万方数据