肝癌是在肝脏表面或内部生长的恶性肿瘤。主要原因是乙型肝炎或丙型肝炎病毒的病毒感染。天然产物及其结构类似物在历史上为药物治疗做出了重大贡献,尤其是癌症。一系列研究证明了Bacopamonnieri对肝癌的治疗效果,但是精确的分子机制尚未被发现。这项研究结合了数据挖掘,网络药理学,和分子对接分析,通过确定有效的植物化学物质,可能彻底改变肝癌治疗。最初,有关B.monnieri的活性成分以及肝癌和B.monnieri的靶基因的信息从文献以及公开数据库中检索。根据B.monnieri潜在靶标与肝癌靶标之间的匹配结果,使用STRING数据库构建蛋白质-蛋白质相互作用(PPI)网络,并将其导入Cytoscape,用于根据hub基因的连接程度筛选hub基因.稍后,利用Cytoscape软件构建化合物与重叠基因之间的相互作用网络,分析B.monnieri对肝癌的网络药理学预期作用。hub基因的基因本体论(GO)和KEGG通路分析显示,这些基因参与癌症相关通路。最后,使用微阵列数据(GSE39791,GSE76427,GSE22058,GSE87630和GSE112790)分析核心靶标的表达水平.Further,使用GEPIA服务器和PyRx软件进行生存和分子对接分析,分别。总之,我们提出槲皮素,木犀草素,芹菜素,儿茶素,表儿茶素,豆甾醇,β-谷甾醇,celastrol,和betulic酸通过影响肿瘤蛋白53(TP53)抑制肿瘤生长,白细胞介素6(IL6),RAC-α丝氨酸/苏氨酸蛋白激酶1(AKT1),caspase-3(CASP3),肿瘤坏死因子(TNF),jun原癌基因(JUN),热射蛋白90AA1(HSP90AA1),血管内皮生长因子A(VEGFA),表皮生长因子受体(EGFR),和SRC原癌基因(SRC)。通过,微阵列数据分析,发现JUN和IL6的表达水平上调,而发现HSP90AA1的表达水平下调。Kaplan-Meier生存分析表明,HSP90AA1和JUN是有希望的候选基因,可以作为肝癌的诊断和预后生物标志物。此外,60ns的分子对接和分子动力学模拟很好地补充了化合物的结合亲和力,并揭示了预测化合物在对接位点的强稳定性。使用MMPBSA和MMGBSA计算结合自由能验证了化合物与HSP90AA1和JUN的结合袋之间的强结合亲和力。尽管如此,体内和体外研究是强制性的,以揭示药代动力学和生物安全性概况,以完全追踪B.monnieri在肝癌中的候选状态。
Liver cancer is a malignant tumor that grows on the surface or inside the liver. The leading cause is a viral infection with hepatitis B or C virus. Natural products and their structural analogues have historically made a major contribution to pharmacotherapy, especially for cancer. A list of studies evidences the therapeutic efficacy of Bacopa monnieri against liver cancer, but the precise molecular mechanism is yet to be discovered. This
study combines data mining, network pharmacology, and molecular docking analysis to potentially revolutionize liver cancer treatment by identifying effective phytochemicals. Initially, the information on active constituents of B. monnieri and target genes of both liver cancer and B. monnieri were retrieved from literature as well as from publicly available databases. Based on the matching results between B. monnieri potential targets and liver cancer targets, the protein-protein interaction (PPI) network was constructed using the STRING database and imported into Cytoscape for screening of hub genes based on their degree of connectivity. Later, the interactions network between compounds and overlapping genes was constructed using Cytoscape software to analyze the network pharmacological prospective effects of B. monnieri on liver cancer. Gene Ontology (GO) and KEGG pathway analysis of hub genes revealed that these genes are involved in the cancer-related pathway. Lastly, the expression level of core targets was analyzed using microarray data (GSE39791, GSE76427, GSE22058, GSE87630, and GSE112790). Further, the GEPIA server and PyRx software were used for survival and molecular docking analysis, respectively. In summary, we proposed that quercetin, luteolin, apigenin, catechin, epicatechin, stigmasterol, beta-sitosterol, celastrol, and betulic acid inhibit tumor growth by affecting tumor protein 53 (TP53), interleukin 6 (IL6), RAC-alpha serine/threonine protein kinases 1 (AKT1), caspase-3 (CASP3), tumor necrosis factor (TNF), jun proto-oncogene (JUN), heat shot protein 90 AA1 (HSP90AA1), vascular endothelial growth factor A (VEGFA), epidermal growth factor receptor (EGFR), and SRC proto-oncogene (SRC). Through, microarray data analysis, the expression level of JUN and IL6 were found to be upregulated while the expression level of HSP90AA1 was found to be downregulated. Kaplan-Meier survival analysis indicated that HSP90AA1 and JUN are promising candidate genes that can serve as diagnostic and prognostic biomarkers for liver cancer. Moreover, the molecular docking and molecular dynamic simulation of 60ns well complemented the binding affinity of the compound and revealed strong stability of predicted compounds at the docked site. Calculation of binding free energies using MMPBSA and MMGBSA validated the strong binding affinity between the compound and binding pockets of HSP90AA1 and JUN. Despite that, in vivo and in vitro studies are mandatory to unveil pharmacokinetics and biosafety profiles to completely track the candidature status of B. monnieri in liver cancer.