Zhang Yajing, Zhao Zirui, Li Wenlong, Tang Yuanhu, Wang Shujie
College of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China.
Curr Issues Mol Biol. 2023 Aug 7;45(8):6564-6582. doi: 10.3390/cimb45080414.
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.
紫杉烷类是用于治疗肺癌的天然化合物，但其作用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，研究了紫杉烷类治疗肺癌的靶点和途径机制。通过PubChem数据库确定紫杉烷类靶点，并构建有效化合物 - 靶点网络。利用GeneCards数据库确定肺癌的疾病靶点，得到化合物靶点与疾病靶点的交集。分析交集靶点的蛋白质 - 蛋白质相互作用（PPI）网络，并使用Cytoscape 3.6.0软件构建PPI网络。根据度值筛选出枢纽靶点，并通过分子对接验证紫杉烷类与枢纽靶点之间的结合活性。结果表明，筛选出8种紫杉烷类活性化合物和444个相应靶点，与肺癌疾病靶点映射后得到131个交集靶点。通过PPI分析得到的枢纽靶点为TP53、EGFR和AKT1。基因本体（GO）生物功能富集分析得到1795个生物过程（BP）术语、101个细胞成分（CC）术语和164个分子功能（MF）术语。通过京都基因与基因组百科全书（KEGG）通路富集分析得到179条信号通路。筛选出20条信号通路，主要是癌症中的通路、癌症通路中的蛋白聚糖、癌症通路中的微小RNA等。分子对接表明，8种紫杉烷类与TP53、EGFR和AKT1靶点的结合能小于-8.8 kcal/mol，紫杉烷类通过癌症中的通路、癌症通路中的蛋白聚糖和癌症通路中的微小RNA作用于TP53、EGFR和AKT1靶点，并在蛋白质结合、酶结合和同蛋白结合等生物学功能中发挥治疗肺癌的作用。
