结合生物信息学和网络药理学探讨五味子素治疗肥厚性心肌病的靶点和分子机制。

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2023-01-01 DOI:10.2174/1573409919666221124144713
Chaozhuang Shen, Pingping Shen, Xiaohu Wang, Xingwen Wang, Wenxin Shao, Kuo Geng, Haitang Xie
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引用次数: 1

摘要

背景:肥厚性心肌病(HCM)是最常见的遗传性心脏病,也是目前青少年运动员猝死的主要原因。五味子素(Schisandrin)是中药五味子(Schisandra chinensis)的质量标记物,对HCM有很好的治疗作用,但其药理机制尚不清楚。目的:探索五味子素作为抗肥厚性心肌病先导化合物的潜力并提供科学依据。方法:利用SwissADME网站对五味子苷类药物性质进行预测。然后,使用PharmMapper数据库预测潜在的药物靶点,并匹配Uniprot数据库中的基因名称。HCM靶点从NCBI、OMIM和Genecards数据库中收集,并与药物靶点交叉。将交叉靶点导入STRING数据库进行PPI分析,确定核心靶点。通过DAVID数据库对核心靶点进行KEGG和GO富集分析,并将所有网络图导入Cytoscape软件进行可视化优化。从GEO数据库下载hcm相关数据集,分析核心靶点,筛选差异表达靶基因进行分子对接。结果:通过药物与疾病交叉靶点的PPI网络分析,筛选出12个核心靶点。KEGG分析结果显示,它们主要参与Rap1、TNF、FoxO、PI3K-Akt等信号通路。差异分析后,还筛选了PPARG、EGFR和MMP3靶点。分子对接结果表明,五味子素与每个靶点的蛋白主干结合良好。结论:本研究利用网络药理学结合差异表达和分子对接预测五味子素可能通过作用于PPARG、EGFR、MMP3靶点治疗HCM,其调控过程可能涉及Rap1、TNF、FoxO、PI3K-Akt等信号通路,为后续研究提供有价值的参考。
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Integrating Bioinformatics and Network Pharmacology to Explore the Therapeutic Target and Molecular Mechanisms of Schisandrin on Hypertrophic Cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease and is currently the leading cause of sudden death in adolescent athletes. Schisandrin is a quality marker of the traditional Chinese medicine Schisandra chinensis, which has an excellent therapeutic effect on HCM, but its pharmacological mechanism remains unclear.

Objective: This study aimed to explore the potential and provide scientific evidence for schisandrin as a lead compound against hypertrophic cardiomyopathy.

Methods: The drug-like properties of schisandrin were predicted using the SwissADME website. Then, the PharmMapper database was used to predict potential drug targets and match gene names in the Uniprot database. HCM targets were collected from NCBI, OMIM, and Genecards databases and intersected with drug targets. The intersection targets were imported into the STRING database for PPI analysis, and core targets were identified. KEGG and GO enrichment analysis was performed on the core targets through the DAVID database, and all network maps were imported into Cytoscape software for visualization optimization. HCM-related datasets were downloaded from the GEO database to analyze core targets and screen differentially expressed target genes for molecular docking.

Results: After the PPI network analysis of the intersection targets of drugs and diseases, 12 core targets were screened out. The KEGG analysis results showed that they were mainly involved in Rap1, TNF, FoxO, PI3K-Akt, and other signaling pathways. After differential analysis, PPARG, EGFR, and MMP3 targets were also screened. The molecular docking results showed that schisandrin was well bound to the protein backbone of each target.

Conclusion: This study used network pharmacology combined with differential expression and molecular docking to predict that schisandrin may treat HCM by acting on PPARG, EGFR, and MMP3 targets, and the regulatory process may involve signaling pathways, such as Rap1, TNF, FoxO, and PI3K-Akt, which may provide a valuable reference for subsequent studies.

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来源期刊
Current computer-aided drug design
Current computer-aided drug design 医学-计算机:跨学科应用
CiteScore
3.70
自引率
5.90%
发文量
46
审稿时长
>12 weeks
期刊介绍: Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.
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