LIU Liang-yu,YANG Yu-ke,WANG Jian-nong.Mechanism of Active Steroid Alkaloids from Solanum nigrum Against Non-small Cell Lung Cancer: Based on Network Pharmacology[J].Chinese Journal of Experimental Traditional Medical Formulae,2021,27(24):178-185.
LIU Liang-yu,YANG Yu-ke,WANG Jian-nong.Mechanism of Active Steroid Alkaloids from Solanum nigrum Against Non-small Cell Lung Cancer: Based on Network Pharmacology[J].Chinese Journal of Experimental Traditional Medical Formulae,2021,27(24):178-185. DOI: 10.13422/j.cnki.syfjx.20211418.
Mechanism of Active Steroid Alkaloids from Solanum nigrum Against Non-small Cell Lung Cancer: Based on Network Pharmacology
经过筛选得到6个SASN,包括澳洲茄碱、澳洲茄边碱、澳洲茄胺、毛叶冬珊瑚碱、龙葵次碱和氮甲基澳洲茄碱,对SASN和NSCLC全部靶点取交集后得到SASN抗NSCLC的潜在作用靶点共有96个,京都基因与基因组百科全书(KEGG)富集分析表明潜在靶点涉及的通路主要包括癌症通路、癌症蛋白聚糖通路和Forkhead box protein O (FoxO)通路等。PPI网络分析显示,蛋白激酶B1(Akt1),丝裂原活化蛋白激酶1(MAPK1),MAPK8,MAPK14,信号传导及转录激活蛋白3(STAT3)及原癌基因酪氨酸蛋白激酶(SRC)等15个靶点可能是SASN抗NSCLC的关键作用靶点;同时,Western blot结果显示龙葵生物碱可以显著下调Akt1,STAT3和SRC 3个关键蛋白的表达。
To explore the potential targets and pathways of steroid alkaloids
from
Solanum
nigrum
(SASN) in the treatment of non-small cell lung cancer (NSCLC) and analyze the possible mechanism.
Method
2
The active SASN against NSCLC were searched from literature. Then potential targets of SASN were screened through SwissTargetPrediction and PharmMapper, and those of NSCLC through GeneCards. Venny was employed to yield the common targets of the two, and Cytoscape to construct the 'medicinal-component-disease-target' network. Metascape was applied to enrich the Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the common targets, and STRING was used to generate the protein-protein interaction (PPI) network, followed by screening of key targets by Cytoscape. Finally, Western blot was used to verify the effects of the medicinal on key targets.
Result
2
A total of 6 active SASN were screened out: solasonine, solamargine, solasodine, solanocapsine, solanidine, and
N
-methylsolasodine, which had 96 potential anti-NSCLC targets. These targets mainly involved the pathways in cancer, proteoglycans in cancer, and Forkhead box protein O (FoxO) pathway. PPI network analysis demonstrated 15 key anti-NSCLC targets of SASN, such as mitogen-activated protein kinase (MAPK)1, MAPK8, MAPK14, protein kinase B (Akt1), signal transducer and activator of transcription 3 (STAT3), and proto-oncogene tyrosine protein kinase (SRC). Meanwhile, Western blot results showed that SASN could significantly down-regulate the expression of the key proteins Akt1, SRC, and STAT3.
Conclusion
2
We predicted the potential targets and pathways of SASN against NSCLC and obtained 15 key targets, from which we selected three key proteins for validation. The validation results were consistent with the prediction results. This paper is expected to lay a scientific basis for the subsequent in-depth study of the mechanisms of SASN against NSCLC.
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