通过网络药理学和分子对接探索复方芪连片治疗糖尿病视网膜病变的机制

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2024-04-13 DOI:10.2174/0115734099298932240308104437
Jiangwei Jia, Bo Liu, Xin Wang, Fenglan Ji, Fuchun Wen, Lianlian Song, Huibo Xu, Tao Ding
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引用次数: 0

摘要

背景:糖尿病视网膜病变(DR)是糖尿病常见的慢性并发症之一,已发展成为全球成人不可逆视力损伤的主要原因。中国开发了复方芪连片(CQLT)用于治疗和预防 DR,但其作用机制仍不清楚。研究目的本研究采用网络药理学、分子对接和体内验证实验研究复方芪连片对 DR 的活性成分和分子机制。研究方法通过TCSMP数据库收集CQLT的活性成分和靶点,通过GeneCards、OMIM和Drugbank数据库获得DR的靶点。我们利用 STRING 数据库建立了蛋白质-蛋白质相互作用网络。使用 Metascape 数据库进行了基因本体(GO)和京都基因组百科全书(KEGG)通路富集分析。使用 AutoDock Vina 进行了分子对接,以研究 CQLT 成分与核心靶标之间的相互作用。此外,我们还选择了 ZDF 大鼠建立 DR 模型进行实验研究。结果筛选了 CQLT 中的 39 个活性成分和 448 个靶点,其中 90 个靶点与 DR 共享。KEGG 通路富集分析确定了 181 条通路。分子对接结果表明,主要活性成分与核心靶点有很强的结合能力。动物实验结果表明,CQLT 抗 DR 的机制与抑制视网膜 mTOR/HIF-1α/VEGF 信号通路、减轻炎症反应、抑制视网膜新生血管、保护视网膜功能和形态有关。结论本研究初步探讨了CQLT治疗DR的机制,证明CQLT通过多成分、多靶点、多途径发挥抗DR作用。这些研究结果表明,CQLT有望成为一种潜在的DR治疗药物,并有助于开发新型治疗方法。
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Network Pharmacology and Molecular Docking to Explore the Mechanism of Compound Qilian Tablets in Treating Diabetic Retinopathy
Background: Diabetic Retinopathy (DR) is one of the common chronic complications of diabetes mellitus, which has developed into the leading cause of irreversible visual impairment in adults worldwide. The Compound Qilian Tablets (CQLT) were developed in China for the treatment and prevention of DR, but their mechanism of action is still unclear. Objective: In the present study, network pharmacology, molecular docking, and in vivo validation experiments were used to investigate the active components and molecular mechanisms of CQLT against DR. Methods: The active components and targets of CQLT were collected through the TCSMP database, and the targets of DR were obtained from GeneCards, OMIM, and Drugbank databases. We established a protein-protein interaction network using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Metascape database. Molecular docking using AutoDock Vina was performed to investigate the interactions between components of CQLT and core targets. Moreover, we selected ZDF rats to establish a DR model for the experimental studies. Results: 39 active components and 448 targets in CQLT were screened, among which 90 targets were shared with DR. KEGG pathway enrichment analysis identified 181 pathways. The molecular docking results demonstrated that the main active components had strong binding ability to the core targets. The results from animal experiments indicate that the mechanism of CQLT against DR is associated with inhibiting the retinal mTOR/HIF-1α/VEGF signaling pathway, alleviating the inflammatory response, suppressing retinal neovascularization, and protecting the function and morphology of the retina. Conclusion: The present study preliminarily explored the mechanism of CQLT in treating DR and demonstrated that CQLT exerts anti-DR effects through multiple components, multiple targets, and multiple pathways. These findings suggest that CQLT shows promise as a potential therapeutic agent for DR and could contribute to developing novel treatments.
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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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