Ginsenoside Rb1 prevents lipopolysaccharide-induced depressive-like behavior by inhibiting inflammation and neural dysfunction and F2 elicits a novel antidepressant-like effect: A metabolite-based network pharmacology study

Objective: Lingzhu San (LZS) is a traditional Chinese medicine (TCM) prescription which can be effective in treating febrile seizures (FS) and has few researches on the mechanisms. In order to better guide the clinical use of LZS, we used the research ideas and methods of network pharmacology to find the potential core compounds, targets and pathways of LZS in the complex TCM system for the treatment of FS, and predict the mechanism. Materials and Methods: Databases such as BATMAN, TCMSP, TCMID, and SWISS TARGET are used to mine the active compounds and targets of LZS, and the target information of FS was obtained through GENECARDS and OMIM. Using Venny2.1.0 and Cytoscape software to locked the potential core compounds and targets of FS. The R language and ClusterProfiler software package were adopt to enrich and analyze the KEGG and GO pathways of the core targets and the biological processes and potential mechanisms of the core targets were revealed. Results: 187 active compounds and 2113 target proteins of LZS were collected. And 38 potential core compounds, 35 core targets and 775 metabolic and functional pathways were screened which involved in mediating FS. Finally, the role of the core compounds, targets and pivotal pathways of LZS regulated FS in the pathogenesis and therapeutic mechanism of FS was discussed and clarified. Conclusions: In this paper, the multi-compounds, multi-targets and multi-pathways mechanism of LZS in the treatment of FS was preliminarily revealed through the analysis of network pharmacology data, which is consistent with the principle of multi-compounds compatibility of TCM prescriptions and unified treatment of diseases from multiple angles, and it provides a new way for TCM to treat complex diseases caused by multiple factors.

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Network Pharmacology of Ayurveda Formulation Triphala with Special Reference to Anti-Cancer Property

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207318666151019093606 ◽

2015 ◽

Vol 18 (9) ◽

pp. 846-854 ◽

Cited By ~ 25

Author(s):

Uma Chandran ◽

Neelay Mehendale ◽

Girish Tillu ◽

Bhushan Patwardhan

Keyword(s):

Special Reference ◽

Network Pharmacology ◽

Anti Cancer

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Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190717124507 ◽

2019 ◽

Vol 22 (6) ◽

pp. 411-420 ◽

Cited By ~ 5

Author(s):

Xian-Jun Wu ◽

Xin-Bin Zhou ◽

Chen Chen ◽

Wei Mao

Keyword(s):

Cardiovascular Disease ◽

Cardiovascular Diseases ◽

Signaling Pathway ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Therapeutic Effects ◽

Pathway Enrichment ◽

Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

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Exploring the Potential of Capsaicin Against Cancer Metastasis Based on TGF-β Signaling Modulation Through Module-based Network Pharmacology Approach

Current Drug Discovery Technologies ◽

10.2174/1570163816666190515104041 ◽

2020 ◽

Vol 17 (5) ◽

pp. 647-660 ◽

Cited By ~ 1

Author(s):

Shivananda Kandagalla ◽

Sharath Belenahalli Shekarappa ◽

Gollapalli Pavan ◽

Umme Hani ◽

Manjunatha Hanumanthappa

Keyword(s):

Amino Acid ◽

Amino Acid Composition ◽

Signaling Pathway ◽

Acid Composition ◽

Protein Interaction ◽

Cancer Metastasis ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Mode Analysis ◽

Network Pharmacology

Background: Capsaicin is an active alkaloid /principal component of red pepper responsible for the pungency of chili pepper. Capsaicin by changing the intracellular redox homeostasis regulate a variety of signaling pathways ultimately producing a divergent cellular outcome. Several reports showed the potential of capsaicin against cancer metastasis, however unexplored molecular mechanism is still an active part of the research. Several growth factors have a critical role during cancer metastasis among them TGF- β signaling play a vital role. Methods: The present study aimed at analyzing capsaicin modulation of TGF-β signaling using network pharmacology approach. The chemical and protein interaction data of capsaicin was curated and abstracted using STITCH4.0, PubChem and ChEMBL database. Further, the compiled data set was subjected to the pathway and functional enrichment analysis using Protein Analysis THrough Evolutionary Relationship (PANTHER) and, Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Meanwhile, the pattern of amino acid composition across the capsaicin targets was analyzed using the EMBOSS Pepstat tool. Capsaicin targets involved in TGF- β were identified and their Protein-Protein Interaction (PPI) network constructed using STRING v10 and Cytoscape (v 3.2.1). From the above-constructed network, the clusters were mined using the MCODE clustering algorithm and finally binding affinity of capsaicin with its targets involved in TGF-β signaling pathway was analyzed using Autodock Vina. Results: The analysis explored capsaicin targets and, their associated functional and pathway annotations. Besides, the analysis also provides a detailed distinct pattern of amino acid composition across the capsaicin targets. The capsaicin targets described as MAPK14, JUN, SMAD3, MAPK3, MAPK1 and MYC involved in TGF-β signaling pathway through pathway enrichment analysis. The binding mode analysis of capsaicin with its targets has shown high affinity with MAPK3, MAPK1, JUN and MYC. Conclusion: The study explores the potential of capsaicin as a potent modulator of TGF-β signaling pathway during cancer metastasis and proposes new methodology and mechanism of action of capsaicin against TGF- β signaling pathway.

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Network Pharmacology Approach uncovering Pathways involved in targeting Hsp90 through Curcumin and Epigallocatechin to control Inflammation.

Current Drug Discovery Technologies ◽

10.2174/1570163816666191210145652 ◽

2019 ◽

Vol 16 ◽

Author(s):

Umme Hani ◽

Shivananda Kandagalla ◽

B.S. Sharath ◽

K Jyothsna. ◽

H Manjunatha.

Keyword(s):

Gene Ontology ◽

Molecular Chaperones ◽

Curcuma Longa ◽

Interaction Network ◽

Network Pharmacology ◽

Heme Oxygenase 1 ◽

Nrf2 Pathway ◽

Functional Behavior ◽

Inflammatory Proteins ◽

Prime Target

: Hsp90 are molecular chaperones of chronic inflammatory proteins and have emerged as prime target for treatment of inflammation. Principal components from Curcuma longa and Camellia sinensis, Curcumin and EGC respectively possesses anti-inflammatory properties inhibiting cytokines responsible for inflammation. Both act on common pathways in upregulation of heme oxygenase 1 through Pkcδ-Nrf2 pathway and downregulation of Tlr4, which in turn suppress expression of Hsp90. Curcumin and EGC were also found to bind -N and -C terminal domain of Hsp90 respectively. Based on this, work was designed with network pharmacological approach. Hsp90 associated gene targets of Curcumin and EGC were collected from databases, and gene ontology studies were done. PPI were obtained from string database for specific genes involved in Pkcδ-Nrf2 and Tlr4 pathway. Protein interaction network was constructed by cytoscape, and networks of Hsp90, Curcumin and EGC were merged to get common genes involved in Pkcδ-Nrf2 and Tlr4 pathway. Cluego analysis was done for obtained common genes to identify functional behavior in human diseases. Main proteins involved were identified as key regulators in Pkcδ-Nrf2 and Tlr4 pathway for controlling expression of Hsp90 from Curcumin and EGC in inflammation. Docking was performed on main proteins, Hsp90, Pkcδ and Tlr4 with Curcumin and EGC, significant binding energy was obtained for docked complexes. Combinatorial effects of Curcumin and EGC were observed in Pkcδ-Nrf2 and Tlr4pathway. Present study is an attempt to unravel common pathways mediated in intervention of Curcumin and EGC for suppression of Hsp90 associated with inflammation.

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Preliminary Study on the Mechanism of Carvacrol Regulating Hepatocellular Carcinoma Based on Network Pharmacology

Letters in Drug Design & Discovery ◽

10.2174/1570180816666190516105906 ◽

2019 ◽

Vol 16 (11) ◽

pp. 1286-1295

Author(s):

Sha Li ◽

Haixia Zhao ◽

Lidao Bao

Keyword(s):

Hepatocellular Carcinoma ◽

Western Blot ◽

Target Prediction ◽

Network Pharmacology ◽

Literature Mining ◽

Active Compounds ◽

Prediction Server ◽

Preliminary Study ◽

Alignment Analysis ◽

Endogenous Interactions

Objective: To predict and analyze the target of anti-Hepatocellular Carcinoma (HCC) in the active constituents of Safflower by using network pharmacology. Methods: The active compounds of safflower were collected by TCMSP, TCM-PTD database and literature mining methods. The targets of active compounds were predicted by Swiss Target Prediction server, and the target of anti-HCC drugs was collected by DisGeNET database. The target was subjected to an alignment analysis to screen out Carvacrol, a target of safflower against HCC. The mouse HCC model was established and treated with Carvacrol. The anti-HCC target DAPK1 and PPP2R2A were verified by Western blot and co-immunoprecipitation. Results: A total of 21 safflower active ingredients were predicted. Carvacrol was identified as a possible active ingredient according to the five principles of drug-like medicine. According to Carvacrol's possible targets and possible targets of HCC, three co-targets were identified, including cancer- related are DAPK1 and PPP2R2A. After 20 weeks of Carvacrol treated, Carvacrol group significantly increased on DAPK1 levels and decreased PPP2R2A levels in the model mice by Western blot. Immunoprecipitation confirmed the endogenous interaction between DAPK1 and PPP2R2A. Conclusion: Safflower can regulate the development of HCC through its active component Carvacrol, which can affect the expression of DAPK1 and PPP2R2A proteins, and the endogenous interactions of DAPK1 and PPP2R2A proteins.

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