Department of Oncology, Longhua Hospital Shanghai University of TCM, Shanghai, China.
Intensive Care Unit, Longhua Hospital Shanghai University of TCM, Shanghai, China.
Medicine (Baltimore). 2022 Jul 1;101(26):e29729. doi: 10.1097/MD.0000000000029729.
The aim of the study wasto explore the target and potential mechanism of Scutellariae Radix and Astragaloside in the treatment of lung cancer infection by network pharmacology. The target information of baicalein and flavonin was mined from CTD database and Swiss database. Genecards database, DRUGBANK database, and OMIM database were used to search for lung cancer related genes. The target protein network map (PPI) was drawn by using the STRING database analysis and Cytoscape3.7.1 software. With the help of Perl language, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene function analysis (GO) enrichment analysis were carried out by using the biological program package of R language. In total, 347 biological targets of Astragaloside and Scutellariae Radix were identified through the collection and analysis of multiple databases. In total, 1526 lung cancer targets were obtained from a multi-disease database. The "component-target" network of Astragaloside and Scutellariae Radix was constructed, and the protein interaction network (PPI) of the overlapping targets was analyzed to identify the key targets of drug-influenced diseases. In addition, KEGG pathway analysis and GO enrichment analysis were performed on the overlapping targets to explore the mechanism of Scutellariae Radix and Astragaloside in the treatment of lung cancer. Scutellariae Radix and Astragaloside have the characteristics of multi-component, multi-target and multi-pathway in the treatment of lung cancer, which provides a new idea and scientific basis for further research on the molecular mechanism of the antilung cancer effect of Scutellariae Radix and Astragaloside.
本研究旨在通过网络药理学探索黄芩和黄芪治疗肺癌感染的靶点及潜在机制。从 CTD 数据库和瑞士数据库中挖掘黄芩苷和黄酮的靶点信息。利用 Genecards 数据库、DRUGBANK 数据库和 OMIM 数据库搜索与肺癌相关的基因。通过 STRING 数据库分析和 Cytoscape3.7.1 软件绘制靶蛋白网络图（PPI）。借助 Perl 语言，利用 R 语言的生物程序包对 KEGG 通路富集分析和基因功能分析（GO）富集分析进行分析。通过多数据库的收集和分析，共鉴定出黄芪和黄芩的 347 个生物靶点。从多疾病数据库中获得 1526 个肺癌靶点。构建黄芪和黄芩的“成分-靶点”网络，分析重叠靶点的蛋白质相互作用网络（PPI），鉴定出药物影响疾病的关键靶点。此外，对重叠靶点进行 KEGG 通路分析和 GO 富集分析，探讨黄芩和黄芪治疗肺癌的作用机制。黄芩和黄芪在治疗肺癌方面具有多成分、多靶点和多途径的特点，为进一步研究黄芩和黄芪的抗肺癌作用分子机制提供了新的思路和科学依据。
