Tao Jiang, Yang Lu, Wanzhi Yang, Jinhong Xu, Mingxing Zhu, Yong Huang, Fang Bao, Shengqi Zheng, Yongxia Li
{"title":"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","authors":"Tao Jiang, Yang Lu, Wanzhi Yang, Jinhong Xu, Mingxing Zhu, Yong Huang, Fang Bao, Shengqi Zheng, Yongxia Li","doi":"10.2174/1573409920666230823161355","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>Maiwei Dihuang decoction may play a role in the treatment of NSCLC by coregulating TP53/STAT3/MAPK3 signal pathway.</p>","PeriodicalId":10886,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"590-597"},"PeriodicalIF":1.5000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"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.\",\"authors\":\"Tao Jiang, Yang Lu, Wanzhi Yang, Jinhong Xu, Mingxing Zhu, Yong Huang, Fang Bao, Shengqi Zheng, Yongxia Li\",\"doi\":\"10.2174/1573409920666230823161355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>Maiwei Dihuang decoction may play a role in the treatment of NSCLC by coregulating TP53/STAT3/MAPK3 signal pathway.</p>\",\"PeriodicalId\":10886,\"journal\":{\"name\":\"Current computer-aided drug design\",\"volume\":\" \",\"pages\":\"590-597\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current computer-aided drug design\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/1573409920666230823161355\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, MEDICINAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current computer-aided drug design","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1573409920666230823161355","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, MEDICINAL","Score":null,"Total":0}
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.
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.