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基于系统药理学的方法研究当归芍药散治疗阿尔茨海默病的作用机制。

Systems pharmacology-based approach to investigate the mechanisms of Danggui-Shaoyao-san prescription for treatment of Alzheimer's disease.

机构信息

Clinical Research Center, Hainan Provincial Hospital of Traditional Chinese Medicine, Guangzhou University of Chinese Medicine, Haikou, 570000, China.

Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, 510000, China.

出版信息

BMC Complement Med Ther. 2020 Sep 18;20(1):282. doi: 10.1186/s12906-020-03066-4.

Abstract

BACKGROUND

Alzheimer's disease (AD) is the most common cause of dementia in the elderly, characterized by a progressive and irreversible loss of memory and cognitive abilities. Currently, the prevention and treatment of AD still remains a huge challenge. As a traditional Chinese medicine (TCM) prescription, Danggui-Shaoyao-san decoction (DSS) has been demonstrated to be effective for alleviating AD symptoms in animal experiments and clinical applications. However, due to the complex components and biological actions, its underlying molecular mechanism and effective substances are not yet fully elucidated.

METHODS

In this study, we firstly systematically reviewed and summarized the molecular effects of DSS against AD based on current literatures of in vivo studies. Furthermore, an integrated systems pharmacology framework was proposed to explore the novel anti-AD mechanisms of DSS and identify the main active components. We further developed a network-based predictive model for identifying the active anti-AD components of DSS by mapping the high-quality AD disease genes into the global drug-target network.

RESULTS

We constructed a global drug-target network of DSS consisting 937 unique compounds and 490 targets by incorporating experimental and computationally predicted drug-target interactions (DTIs). Multi-level systems pharmacology analyses revealed that DSS may regulate multiple biological pathways related to AD pathogenesis, such as the oxidative stress and inflammatory reaction processes. We further conducted a network-based statistical model, drug-likeness analysis, human intestinal absorption (HIA) and blood-brain barrier (BBB) penetration prediction to uncover the key ani-AD ingredients in DSS. Finally, we highlighted 9 key ingredients and validated their synergistic role against AD through a subnetwork.

CONCLUSION

Overall, this study proposed an integrative systems pharmacology approach to disclose the therapeutic mechanisms of DSS against AD, which also provides novel in silico paradigm for investigating the effective substances of complex TCM prescription.

摘要

背景

阿尔茨海默病(AD)是老年人中最常见的痴呆症类型,其特征是记忆和认知能力的进行性和不可逆转丧失。目前,AD 的预防和治疗仍然是一个巨大的挑战。当归芍药散(DSS)作为一种中药方剂,已在动物实验和临床应用中证明对缓解 AD 症状有效。然而,由于其复杂的成分和生物学作用,其潜在的分子机制和有效物质尚未完全阐明。

方法

本研究首先基于目前关于体内研究的文献,系统地综述和总结了 DSS 对 AD 的分子作用。此外,提出了一个整合的系统药理学框架,以探索 DSS 治疗 AD 的新机制并鉴定主要的活性成分。我们通过将高质量的 AD 疾病基因映射到全球药物 - 靶点网络,进一步开发了一个基于网络的预测模型,用于识别 DSS 的活性抗 AD 成分。

结果

我们通过整合实验和计算预测的药物 - 靶点相互作用(DTIs),构建了一个包含 937 个独特化合物和 490 个靶点的 DSS 全球药物 - 靶点网络。多层次系统药理学分析表明,DSS 可能调节与 AD 发病机制相关的多个生物学途径,如氧化应激和炎症反应过程。我们进一步进行了基于网络的统计模型、药物相似性分析、人类肠道吸收(HIA)和血脑屏障(BBB)渗透预测,以揭示 DSS 中的关键抗 AD 成分。最后,我们通过一个子网络突出了 9 种关键成分,并验证了它们对 AD 的协同作用。

结论

总之,本研究提出了一种综合系统药理学方法来揭示 DSS 治疗 AD 的机制,为研究复杂中药方剂的有效物质提供了新的计算范例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e099/7501700/d397806000da/12906_2020_3066_Fig1_HTML.jpg

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