Deng Yaling, Ye Xianwen, Chen Yufan, Ren Hongmin, Xia Lanting, Liu Ying, Liu Minmin, Liu Haiping, Zhang Huangang, Wang Kairui, Zhang Jinlian, Zhang Zhongwei
School of Pharmacy, Jiangxi University of Traditional Chinese Medicine, Nanchang, China.
Patient Service Center, Ganzhou People's Hospital, Ganzhou, China.
Front Pharmacol. 2021 Feb 12;11:609825. doi: 10.3389/fphar.2020.609825. eCollection 2020.
The technology, network pharmacology and molecular docking technology of the ultra performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) were used to explore the potential molecular mechanism of (PG) in the treatment of lung cancer (LC). UPLC-Q-TOF-MS/MS technology was used to analyze the ingredients of PG and the potential LC targets were obtained from the Traditional Chinese Medicine Systems Pharmacology database, and the Analysis Platform (TCMSP), GeneCards and other databases. The interaction network of the drug-disease targets was constructed with the additional use of STRING 11.0. The pathway enrichment analysis was carried out using Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) in Metascape, and then the "Drug-Ingredients-Targets-Pathways-Disease" (D-I-T-P-D) network was constructed using Cytoscape v3.7.1. Finally, the Discovery Studio 2016 (DS) software was used to evaluate the molecular docking. Forty-seven compounds in PG, including triterpenoid saponins, steroidal saponins and flavonoids, were identified and nine main bioactive components including platycodin D were screened. According to the method of data mining, 545 potential drug targets and 2,664 disease-related targets were collected. The results of topological analysis revealed 20 core targets including caspase 3 (CASP3) and prostaglandin-endoperoxide synthase 2 (PTGS2) suggesting that the potential signaling pathway potentially involved in the treatment of LC included MAPK signaling pathway and P13K-AKT signaling pathway. The results of molecular docking proved that the bound of the ingredients with potential key targets was excellent. The results in this study provided a novel insight in the exploration of the mechanism of action of PG against LC.
采用超高效液相色谱-四极杆飞行时间串联质谱(UPLC-Q-TOF-MS/MS)技术、网络药理学和分子对接技术,探讨桔梗(PG)治疗肺癌(LC)的潜在分子机制。运用UPLC-Q-TOF-MS/MS技术分析PG的成分,并从中药系统药理学数据库及分析平台(TCMSP)、GeneCards等数据库中获取潜在的LC靶点。额外使用STRING 11.0构建药物-疾病靶点相互作用网络。利用Metascape中的基因本体论(GO)和京都基因与基因组百科全书(KEGG)进行通路富集分析,然后使用Cytoscape v3.7.1构建“药物-成分-靶点-通路-疾病”(D-I-T-P-D)网络。最后,使用Discovery Studio 2016(DS)软件评估分子对接。鉴定出PG中的47种化合物,包括三萜皂苷、甾体皂苷和黄酮类化合物,并筛选出包括桔梗皂苷D在内的9种主要生物活性成分。按照数据挖掘方法,收集了545个潜在药物靶点和2664个疾病相关靶点。拓扑分析结果显示包括半胱天冬酶3(CASP3)和前列腺素内过氧化物合酶2(PTGS2)在内的20个核心靶点,提示PG治疗LC可能涉及的潜在信号通路包括MAPK信号通路和P13K-AKT信号通路。分子对接结果证明成分与潜在关键靶点的结合良好。本研究结果为探索PG抗LC的作用机制提供了新的见解。