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Systems Pharmacological Approach to Investigate the Mechanism of Ohwia caudata for Application to Alzheimer’s Disease

机译:系统药理学方法来研究大叶黄花应用于阿尔茨海默氏病的机理

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摘要

Ohwia caudata (OC)—a traditional Chinese medicine (TCM)—has been reported to have large numbers of flavonoids, alkaloids, and triterpenoids. The previous studies on OC for treating Alzheimer’s disease (AD) only focused on single targets and its mechanisms, while no report had shown about the synergistic mechanism of the constituents from OC related to their potential treatment on dementia in any database. This study aimed to predict the bioactive targets constituents and find potential compounds from OC with better oral bioavailability and blood–brain barrier permeability against AD, by using a system network level-based in silico approach. The results revealed that two new flavonoids, and another 26 compounds isolated from OC in our lab, were highly connected to AD-related signaling pathways and biological processes, which were confirmed by compound–target network, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, respectively. Predicted by the virtual screening and various network pharmacology methods, we found the multiple mechanisms of OC, which are effective for alleviating AD symptoms through multiple targets in a synergetic way.
机译:据报道,传统的中药(TCM)大黄草(OC)含有大量的类黄酮,生物碱和三萜类化合物。先前有关OC治疗阿尔茨海默氏病(AD)的研究仅集中于单一目标及其机制,而在任何数据库中都没有关于OC成分与痴呆症潜在治疗相关的协同机制的报道。这项研究旨在通过使用基于系统网络水平的计算机模拟方法,从OC中预测具有生物活性的目标成分,并从OC中寻找具有更好口服生物利用度和血脑屏障通透性的潜在化合物。结果表明,在我们的实验室中,从OC中分离出了两种新的黄酮类化合物,以及另外26种化合物,它们与AD相关的信号通路和生物过程高度相关,这些均已通过化合物-靶标网络,基因本体论(GO)分析和京都议定书得到了证实。基因和基因组百科全书(KEGG)途径富集分析分别。通过虚拟筛选和各种网络药理学方法的预测,我们发现了OC的多种机制,这些机制可有效地协同作用通过多个​​靶点缓解AD症状。

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