Author:
Salas-Estrada Leslie,Provasi Davide,Qui Xing,Kaniskan H. Ümit,Huang Xi-Ping,DiBerto Jeffrey F.,Ribeiro João Marcelo Lamim,Jin Jian,Roth Bryan L.,Filizola Marta
Abstract
ABSTRACTLikely effective pharmacological interventions for the treatment of opioid addiction include attempts to attenuate brain reward deficits during periods of abstinence. Pharmacological blockade of the κ-opioid receptor (KOR) has been shown to abolish brain reward deficits in rodents during withdrawal, as well as to reduce the escalation of opioid use in rats with extended access to opioids. Although KOR antagonists represent promising candidates for the treatment of opioid addiction, very few potent selective KOR antagonists are known to date and most of them exhibit significant safety concerns. Here, we used a generative deep learning framework for thede novodesign of chemotypes with putative KOR antagonistic activity. Molecules generated by models trained with this framework were prioritized for chemical synthesis based on their predicted optimal interactions with the receptor. Our models and proposed training protocol were experimentally validated by binding and functional assays.
Publisher
Cold Spring Harbor Laboratory
Reference76 articles.
1. Opioids;Handb Exp Pharmacol,2007
2. Azadfraf, M. H. , M.R.; Leaming , J.M. Opioid Addiction; StatPearls; 2022.
3. U.S. Overdose Deaths in 2021 Increased Half as Much as in 2020 - But Are Still Up 15% . 2022. https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2022/202205.htm (accessed.
4. Trends and Geographic Patterns in Drug and Synthetic Opioid Overdose Deaths — United States, 2013–2019
5. UNODC. World Drug Report 2021. 2021. https://www.unodc.org/unodc/data-and-analysis/wdr2021.html (accessed.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献