Molecular Docking
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2021 ◽  
Vol 12 ◽  
Author(s):  
Dan He ◽  
Qiang Li ◽  
Guangli Du ◽  
Guofeng Meng ◽  
Jijia Sun ◽  
...  

Background: Guizhi has the pharmacological activity of anti-inflammatory. However, the effect mechanism of Guizhi against nephrotic syndrome (NS) remains unclear. A network pharmacological approach with experimental verification in vitro and in vivo was performed to investigate the potential mechanisms of Guizhi to treat NS.Methods: Active compounds and potential targets of Guizhi, as well as the related targets of NS were obtained from the public databases. The intersecting targets of Guizhi and NS were obtained through Venny 2.1.0. The key targets and signaling pathways were determined by protein-protein interaction (PPI), genes ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analysis. And the overall network was constructed with Cytoscape. Molecular docking verification was carried out by AutoDock Vina. Finally, in vitro and in vivo experiments were performed to verify the mechanism of Guizhi to treat NS.Results: 63 intersecting targets were obtained, and the top five key targets mainly involed in NF- Kappa B and MAPK signaling pathway. In the overall network, cinnamaldehyde (CA) was the top one active compound with the highest degree value. The molecular docking showed that the top five key targets were of good binding activity with the active components of Guizhi. To in vitro experiment, CA, the main active component of Guizhi, inhibited the secretion of IL-1β, IL-6, TNF-α in LPS challenged RAW264.7 cells, and down regulated the protein expression of p-NF-κB p65 and p-p38 MAPK in LPS challenged RAW264.7 cells. In vitro experiment showed that, 24 urinary protein and renal function were increased in ADR group. To western blot, CA down regulated the protein expression of p-p38 MAPK in rats of adriamycin-induced nephropathy.Conclusion: CA might be the main active component of Guizhi to treat NS, and the underlying mechanism might mainly be achieved by inhibiting MAPK signaling pathway.


2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ying Qu ◽  
Xiangyang Yang ◽  
Jingxiang Li ◽  
Shuxin Zhang ◽  
Shiying Li ◽  
...  

Objective. This study aimed to investigate the possible mechanism of the Zhishi and Baizhu herb pair in the treatment of gastric cancer by means of network pharmacology and molecular docking and to provide a theoretical basis for experiments and clinical application of traditional Chinese medicine for treating gastric cancer. Methods. The main active chemical components of Zhishi and Baizhu were screened through Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and selected by using the thresholds of oral bioavailability ≥30% and drug-likeness ≥18%. The targets of Zhishi and Baizhu were obtained from TCMSP, Therapeutic Targets Database (TTD), and the DrugBank database. The corresponding genes of the targets were retrieved from the UniProt database, and the gastric cancer targets were obtained from the GeneCards database and TTD. Subsequently, the networks were built between the main drug components, drug targets, and gastric cancer targets. Then, the enrichment analyses of GO and KEGG were applied to predict the potential roles of gastric cancer pathogenesis via the R package clusterProfiler. Finally, molecular docking was used to determine the affinity between the targets and components. Results. Twenty-seven main active components were predicted from the Zhishi-Baizhu herb pair, and a total of 120 intersection genes were screened from 303 potential medicine genes and 1,839 disease genes. The enrichment included the PI3K-Akt and IL-17 signaling pathways, and the network analysis showed that the Zhishi-Baizhu herb pair acted on seven key targets, namely, AKT1, MMP9, IL-6, CCND1, BCL2, MTOR, and MDM2 (where they played a role in treating gastric cancer). Molecular docking showed that luteolin and naringenin could stably bind to the targets. Conclusion. The possible mechanisms of the components of the Zhishi-Baizhu herb pair in treating gastric cancer might be related to luteolin and naringenin, which intervened with the targets AKT1, MMP9, IL-6, CCND1, BCL2, MTOR, and MDM2, and are linked with the PI3K-Akt and IL-17 signaling pathways. This knowledge will lay a solid foundation for further experimental and clinical studies.


2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Xie ◽  
Jun Wu ◽  
Sihui Yang ◽  
Huaijun Zhou

Background. Aloe vera has long been considered an anticancer herb in different parts of the world. Objective. To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. Methods. The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. Results. By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. Conclusion. This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.


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