Department of Pharmacy, The Sixth Affiliated Hospital of Kunming Medical University, Yuxi, Yunnan, China.
Indian J Pharmacol. 2022 Mar-Apr;54(2):110-117. doi: 10.4103/ijp.ijp_374_21.
The present study aimed to elucidate the molecular network mechanism of the Rujiling capsule in the treatment of hyperplasia of mammary glands through network pharmacology and molecular docking.
TCMSP and TCMID databases were screened for the active components and their action targets of the Rujiling capsule, whereas the disease targets of hyperplasia of mammary glands were searched in GeneCard and DisGeNET databases. Venny software was employed to identify the common targets of drugs and diseases. Cytoscape software was used to construct the network pharmacological diagram of "drug-active components-target" and the intersection targets were subjected to protein-protein interaction analysis by STRING platform and Cytoscape software. The DAVID database was exploited for gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of the intersection target. After that, the key target genes with a degree value greater than the median were verified with the active components in molecular docking.
A total of 691 drug targets, 251 disease targets, and 108 intersection targets were obtained after retrieval and screening. Among the 686 items enriched by GO included 522 biological processes, 110 molecular functions, and 54 cellular components. At the same time, 114 signal pathways were enriched by KEGG. The results of molecular docking revealed that the docking energies of main active components and some core targets were all <-5 kcal/mol.
Henceforth, highlighted the role of the Rujiling capsule in the treatment of hyperplasia of mammary glands through multiple components, multiple targets, and multiple signal pathways.
本研究旨在通过网络药理学和分子对接方法阐明乳灵胶囊治疗乳腺增生的分子网络机制。
在 TCMSP 和 TCMID 数据库中筛选乳灵胶囊的活性成分及其作用靶点，在 GeneCard 和 DisGeNET 数据库中搜索乳腺增生病的靶点。利用 Venny 软件识别药物和疾病的共同靶点。采用 Cytoscape 软件构建“药物-活性成分-靶点”网络药理学图，并通过 STRING 平台和 Cytoscape 软件对交集靶点进行蛋白质-蛋白质相互作用分析。利用 DAVID 数据库对交集靶点进行基因本体（GO）和京都基因与基因组百科全书（KEGG）富集分析。然后，用分子对接验证关键目标基因与活性成分的关系。
检索和筛选后共获得 691 个药物靶点、251 个疾病靶点和 108 个交集靶点。GO 富集分析共包含 522 个生物学过程、110 个分子功能和 54 个细胞组成，KEGG 通路富集分析共包含 114 个信号通路。分子对接结果显示，主要活性成分与部分核心靶点的对接能均小于-5 kcal/mol。
乳灵胶囊通过多成分、多靶点、多信号通路发挥治疗乳腺增生的作用。
