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Computational systems pharmacology analysis of cannabidiol: a combination of chemogenomics-knowledgebase network analysis and integrated in silico modeling and simulation.
Acta Pharmacologica Sinica ( IF 8.2 ) Pub Date : 2018-09-10 , DOI: 10.1038/s41401-018-0071-1
Yue-Min Bian 1, 2, 3 , Xi-Bing He 1, 2, 3 , Yan-Kang Jing 1, 2, 3 , Li-Rong Wang 1, 2, 3 , Jun-Mei Wang 1, 2, 3 , Xiang-Qun Xie 1, 2, 3, 4
Affiliation  

With treatment benefits in both the central nervous system and the peripheral system, the medical use of cannabidiol (CBD) has gained increasing popularity. Given that the therapeutic mechanisms of CBD are still vague, the systematic identification of its potential targets, signaling pathways, and their associations with corresponding diseases is of great interest for researchers. In the present work, chemogenomics-knowledgebase systems pharmacology analysis was applied for systematic network studies to generate CBD-target, target-pathway, and target-disease networks by combining both the results from the in silico analysis and the reported experimental validations. Based on the network analysis, three human neuro-related rhodopsin-like GPCRs, i.e., 5-hydroxytryptamine receptor 1 A (5HT1A), delta-type opioid receptor (OPRD) and G protein-coupled receptor 55 (GPR55), were selected for close evaluation. Integrated computational methodologies, including homology modeling, molecular docking, and molecular dynamics simulation, were used to evaluate the protein-CBD binding modes. A CBD-preferred pocket consisting of a hydrophobic cavity and backbone hinges was proposed and tested for CBD-class A GPCR binding. Finally, the neurophysiological effects of CBD were illustrated at the molecular level, and dopamine receptor 3 (DRD3) was further predicted to be an active target for CBD.

中文翻译:

大麻二酚的计算系统药理学分析:化学基因组学-知识库网络分析的结合,并集成在计算机建模和模拟中。

随着中枢神经系统和外周系统的治疗益处,大麻二酚 (CBD) 的医疗用途越来越受欢迎。鉴于 CBD 的治疗机制尚不明确,系统识别其潜在靶点、信号通路及其与相应疾病的关联是研究人员非常感兴趣的。在目前的工作中,化学基因组学-知识库系统药理学分析被应用于系统网络研究,通过结合计算机分析的结果和报告的实验验证,生成 CBD 靶点、靶点通路和靶点疾病网络。基于网络分析,三种人类神经相关的类视紫红质 GPCR,即 5-羟色胺受体 1A (5HT1A),选择 delta 型阿片受体 (OPRD) 和 G 蛋白偶联受体 55 (GPR55) 进行密切评估。综合计算方法,包括同源建模、分子对接和分子动力学模拟,用于评估蛋白质-CBD 结合模式。提出了一个由疏水腔和骨架铰链组成的 CBD 首选口袋,并测试了 CBD A 类 GPCR 结合。最后,在分子水平上阐明了 CBD 的神经生理效应,并进一步预测多巴胺受体 3 (DRD3) 是 CBD 的活性靶标。提出了一个由疏水腔和骨架铰链组成的 CBD 首选口袋,并测试了 CBD A 类 GPCR 结合。最后,在分子水平上阐明了 CBD 的神经生理效应,并进一步预测多巴胺受体 3 (DRD3) 是 CBD 的活性靶标。提出了一个由疏水腔和骨架铰链组成的 CBD 首选口袋,并测试了 CBD A 类 GPCR 结合。最后,在分子水平上阐明了 CBD 的神经生理效应,并进一步预测多巴胺受体 3 (DRD3) 是 CBD 的活性靶标。
更新日期:2019-01-26
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