PDF(Pubmed)
Abstract：
Taxanes are natural compounds for the treatment of lung cancer, but the molecular mechanism behind the effects is unclear. In the present study, through network pharmacology and molecular docking, the mechanism of the target and pathway of taxanes in the treatment of lung cancer was studied. The taxanes targets were determined by PubChem database, and an effective compounds-targets network was constructed. The GeneCards database was used to determine the disease targets of lung cancer, and the intersection of compound targets and disease targets was obtained. The Protein-Protein Interaction (PPI) network of the intersection targets was analyzed, and the PPI network was constructed by Cytoscape 3.6.0 software. The hub targets were screened according to the degree value, and the binding activity between taxanes and hub targets was verified by molecular docking. The results showed that eight taxane-active compounds and 444 corresponding targets were screened out, and 131 intersection targets were obtained after mapping with lung cancer disease targets. The hub targets obtained by PPI analysis were TP53, EGFR, and AKT1. Gene Ontology (GO) biological function enrichment analysis obtained 1795 biological process (BP) terms, 101 cellular component (CC) terms, and 164 molecular function (MF) terms. There were 179 signaling pathways obtained by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Twenty signaling pathways were screened out, mainly pathways in cancer, proteoglycans in cancer pathway, microRNAs in cancer pathway, and so on. Molecular docking shows that the binding energies of eight taxanes with TP53, EGFR, and AKT1 targets were less than -8.8 kcal/mol, taxanes acts on TP53, EGFR, and AKT1 targets through pathways in cancer, proteoglycans in cancer pathway and microRNAs in cancer pathway, and plays a role in treating lung cancer in biological functions such as protein binding, enzyme binding, and identical protein binding.
摘要：
紫杉烷是治疗肺癌的天然化合物,但这种效应背后的分子机制尚不清楚。在本研究中,通过网络药理学和分子对接，研究紫杉烷类药物治疗肺癌的作用靶点和途径机制。紫杉烷目标由PubChem数据库确定，构建了有效的化合物-靶标网络。GeneCards数据库用于确定肺癌的疾病目标，并获得了复合靶点与疾病靶点的交集。分析了交叉靶标的蛋白质-蛋白质相互作用（PPI）网络，PPI网络由Cytoscape3.6.0软件构建。根据学位值对枢纽目标进行了筛选，通过分子对接验证了紫杉烷与hub靶标之间的结合活性。结果表明,筛选出8个紫杉烷活性化合物和444个相应的靶标,与肺癌疾病靶标作图后获得131个交叉靶标。通过PPI分析获得的枢纽靶标是TP53，EGFR，AKT1。基因本体论(GO)生物功能富集分析获得1795个生物过程(BP)术语,101个蜂窝组件(CC)术语，和164个分子功能(MF)项。通过京都基因和基因组百科全书(KEGG)途径富集分析获得了179个信号通路。筛选出20条信号通路,主要是癌症的途径，蛋白聚糖在癌症通路中，癌症通路中的microRNAs，等等。分子对接显示八种紫杉烷与TP53、EGFR、AKT1目标小于-8.8kcal/mol，紫杉烷作用于TP53，EGFR，和AKT1通过癌症通路靶向，蛋白聚糖在癌症途径和microRNA在癌症途径，并在蛋白质结合等生物学功能方面发挥治疗肺癌的作用，酶结合，和相同的蛋白质结合。
