基于网络药理学结合 LC-MS 探索麦味地黄煎剂治疗非小细胞肺癌的机制

IF 1.5 4区医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2024-01-01 DOI:10.2174/1573409920666230823161355

Tao Jiang, Yang Lu, Wanzhi Yang, Jinhong Xu, Mingxing Zhu, Yong Huang, Fang Bao, Shengqi Zheng, Yongxia Li

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引用次数: 0

摘要

目的方法：采用网络药理学和液相色谱-质谱（LC-MS）技术，探讨麦味地黄汤治疗非小细胞肺癌（NSCLC）的机制：方法：采用液相色谱-质谱联用技术（LC-MS）检测麦味地黄煎剂中的有效成分。利用 SuperPred 数据库收集麦味地黄汤有效成分的相关靶点，并从 GeneCards、DisgenNET 和 OMIM 数据库中收集非小细胞肺癌的相关靶点。在此基础上，对靶点进行了 PPI 网络构建、GO 富集分析和 KEGG 通路注释分析。最后，使用 AutoDock Vina 进行分子对接：结果：我们通过 LC-MS 结合 ADME 水平进一步筛选了 16 种有效的中药化合物。在此基础上，我们通过蛋白质相互作用网络分析获得了 77 个核心靶点。通过GO、KEGG分析和分子对接结果，我们最终筛选出了麦味地黄煎剂治疗NSCLC的潜在靶点：TP53、STAT3、MAPK3：结论：麦味地黄煎剂可通过核心调节TP53/STAT3/MAPK3信号通路在治疗NSCLC中发挥作用。

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To Explore the Mechanism of Maiwei Dihuang Decoction in the Treatment of Non-small Cell Lung Cancer based on Network Pharmacology Combined with LC-MS.

Objective: To explore the mechanism of Maiwei Dihuang decoction in the treatment of non-small cell lung cancer (NSCLC) by using network pharmacology and LC-MS technology.

Methods: The effective components in Maiwei Dihuang decoction were detected by liquid chromatography- mass spectrometry (LC-MS). Use the SuperPred database to collect the relevant targets of the active ingredients of Mai Wei Di Tang, and then collect the relevant targets of nonsmall cell lung cancer from GeneCards, DisgenNET and OMIM databases. On this basis, PPI network construction, GO enrichment analysis and KEGG pathway annotation analysis were carried out for target sites. Finally, AutoDock Vina is used for molecular docking.

Results: We further screened 16 effective Chinese herbal compounds through LC-MS combined with ADME level. On this basis, we obtained 77 core targets through protein interaction network analysis. Through GO, KEGG analysis and molecular docking results, we finally screened out the potential targets of Maiwei Dihuang Decoction for NSCLC: TP53, STAT3, MAPK3.

Conclusion: Maiwei Dihuang decoction may play a role in the treatment of NSCLC by coregulating TP53/STAT3/MAPK3 signal pathway.

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来源期刊

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

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.