Network pharmacology and experimental verification to explore the effect of Hedyotis diffusa on Alzheimer's disease

IF 3.2 4区 医学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
JingXu Chen, JiaLi Rao, Hao Lu, Min Lu, ChengCheng Wang, Yan Cao
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Abstract

This study aimed to explore the active components and the effect of Hedyotis diffusa (HD) against Alzheimer's disease (AD) via network pharmacology, molecular docking, and experimental evaluations. We conducted a comprehensive screening process using the TCMSP, Swiss Target Prediction, and PharmMapper databases to identify the active components and their related targets in HD. In addition, we collected potential therapeutic targets of AD from the Gene Cards, Drugbank, and OMIM databases. Afterward, we utilized Cytoscape to establish both protein–protein interaction (PPI) networks and compound-target (C-T) networks. To gain further insights into the functional aspect, we performed GO and KEGG pathway analyses using the David database. Next, we employed Autodock vina to estimate the binding force between the components and the hub genes. To validate our network pharmacology findings, we conducted relevant experiments on Caenorhabditis elegans, further confirming the reliability of our results. Then a total of six active compounds and 149 therapeutic targets were detected. Through the analysis of the association between active compounds, therapeutic targets, and signaling pathways, it was observed that the therapeutic effect of HD primarily encompassed the inhibition of Aβ, suppression of AChE activity, and mitigating oxidative stress. Additionally, our investigation revealed that the key active compounds in HD primarily consisted of iridoids, which exhibited resistance against AD by acting on the Alzheimer's disease pathway and the AGE-RAGE signaling pathway in diabetic complications.

Abstract Image

Abstract Image

通过网络药理学和实验验证,探索白花蛇舌草对阿尔茨海默病的疗效。
本研究旨在通过网络药理学、分子对接和实验评估,探索白花蛇舌草(Hedyotis diffusa,HD)的活性成分及其对阿尔茨海默病(Alzheimer's disease,AD)的作用。我们利用 TCMSP、Swiss Target Prediction 和 PharmMapper 数据库进行了全面筛选,以确定 HD 中的活性成分及其相关靶点。此外,我们还从 Gene Cards、Drugbank 和 OMIM 数据库中收集了 AD 的潜在治疗靶点。之后,我们利用 Cytoscape 建立了蛋白质-蛋白质相互作用(PPI)网络和化合物-靶标(C-T)网络。为了进一步了解功能方面的情况,我们利用 David 数据库进行了 GO 和 KEGG 通路分析。接着,我们使用 Autodock vina 估算了各组分与枢纽基因之间的结合力。为了验证我们的网络药理学发现,我们在秀丽隐杆线虫上进行了相关实验,进一步证实了我们结果的可靠性。随后,我们共发现了 6 种活性化合物和 149 个治疗靶点。通过分析活性化合物、治疗靶点和信号通路之间的关联,我们发现 HD 的治疗作用主要包括抑制 Aβ、抑制 AChE 活性和减轻氧化应激。此外,我们的研究还发现,HD 中的关键活性化合物主要由虹膜类化合物组成,它们通过作用于阿尔茨海默病通路和糖尿病并发症中的 AGE-RAGE 信号通路,表现出抗抑郁作用。
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来源期刊
Chemical Biology & Drug Design
Chemical Biology & Drug Design 医学-生化与分子生物学
CiteScore
5.10
自引率
3.30%
发文量
164
审稿时长
4.4 months
期刊介绍: Chemical Biology & Drug Design is a peer-reviewed scientific journal that is dedicated to the advancement of innovative science, technology and medicine with a focus on the multidisciplinary fields of chemical biology and drug design. It is the aim of Chemical Biology & Drug Design to capture significant research and drug discovery that highlights new concepts, insight and new findings within the scope of chemical biology and drug design.
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