A computational strategy for finding novel targets and therapeutic compounds for opioid dependence.
A computational strategy for finding novel targets and therapeutic compounds for opioid dependence.
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一种用于寻找阿片类药物依赖性的新靶标和治疗化合物的计算策略。
DOI：
10.1371/journal.pone.0207027
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发表时间：
2018
期刊：
影响因子：
3.7
通讯作者：
Wu W
中科院分区：
文献类型：
--
作者：
Wu X;Xie S;Wang L;Fan P;Ge S;Xie XQ;Wu W
阿片类药物被广泛用于治疗不同类型的疼痛，但处方阿片类药物的过度使用和滥用导致阿片类药物在美国流行。长期使用阿片类药物除具有镇痛作用外，还可引起耐受、依赖甚至成瘾。阿片类药物成瘾的有效治疗仍然是当今的一大挑战。关于阿片类药物成瘾作用的研究集中在纹状体，这是大脑中负责药物依赖和成瘾的主要成分。一些转录调控因子与阿片类药物成瘾有关，但阿片类药物的镇痛作用与其介导的依赖行为之间的关系尚未在分子水平上得到深入研究。在本文中，我们开发了一种新的计算策略，确定阿片类药物依赖和成瘾的新靶点和潜在的治疗分子化合物。我们采用了几种统计和机器学习技术，并确定了随着时间的推移差异表达的基因，这些基因与暴露于吗啡或海洛因后的依赖相关行为有关，以及调节这些基因的潜在转录调节因子，使用小鼠纹状体的时程基因表达数据。此外，我们的研究结果显示，这些依赖相关基因和转录调节因子中的一些已知在阿片类药物介导的镇痛和耐受中发挥关键作用，这表明阿片类药物诱导的疼痛相关通路和依赖之间的复杂关系可能在阿片类药物暴露的早期阶段发展。最后，我们确定了可以潜在靶向依赖相关基因和转录调节因子的小化合物。这些化合物可能有助于开发阿片类药物依赖和成瘾的有效治疗方法。我们还建立了一个数据库（daportals.org），用于我们发现的所有阿片类药物诱导依赖相关基因和转录调节因子，以及靶向这些基因和转录调节因子的小化合物。
Opioids are widely used for treating different types of pains, but overuse and abuse of prescription opioids have led to opioid epidemic in the United States. Besides analgesic effects, chronic use of opioid can also cause tolerance, dependence, and even addiction. Effective treatment of opioid addiction remains a big challenge today. Studies on addictive effects of opioids focus on striatum, a main component in the brain responsible for drug dependence and addiction. Some transcription regulators have been associated with opioid addiction, but relationship between analgesic effects of opioids and dependence behaviors mediated by them at the molecular level has not been thoroughly investigated. In this paper, we developed a new computational strategy that identifies novel targets and potential therapeutic molecular compounds for opioid dependence and addiction. We employed several statistical and machine learning techniques and identified differentially expressed genes over time which were associated with dependence-related behaviors after exposure to either morphine or heroin, as well as potential transcription regulators that regulate these genes, using time course gene expression data from mouse striatum. Moreover, our findings revealed that some of these dependence-associated genes and transcription regulators are known to play key roles in opioid-mediated analgesia and tolerance, suggesting that an intricate relationship between opioid-induce pain-related pathways and dependence may develop at an early stage during opioid exposure. Finally, we determined small compounds that can potentially target the dependence-associated genes and transcription regulators. These compounds may facilitate development of effective therapy for opioid dependence and addiction. We also built a database (http://daportals.org) for all opioid-induced dependence-associated genes and transcription regulators that we discovered, as well as the small compounds that target those genes and transcription regulators.
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