Network Pharmacology-Based Prediction of the Active Compounds, Potential Targets, and Signaling Pathways Involved in Danshiliuhao Granule for Treatment of Liver Fibrosis

Joint Authors

Tao, Yueying
Tian, Kunming
Chen, Ji
Tan, Danfeng
Liu, Yan
Xiong, Yongai
Chen, Zehui
Tian, Yingbiao

Source

Evidence-Based Complementary and Alternative Medicine

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-07-03

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Medicine

Abstract EN

This study aims to predict the active ingredients, potential targets, signaling pathways and investigate the “ingredient-target-pathway” mechanisms involved in the pharmacological action of Danshiliuhao Granule (DSLHG) on liver fibrosis.

Pharmacodynamics studies on rats with liver fibrosis showed that DSLHG generated an obvious anti-liver fibrosis action.

On this basis, we explored the possible mechanisms underlying its antifibrosis effect using network pharmacology approach.

Information about compounds of herbs in DSLHG was collected from TCMSP public database and literature.

Furthermore, the oral bioavailability (OB) and drug-likeness (DL) were screened according to ADME features.

Compounds with OB≥30% and DL≥0.18 were selected as active ingredients.

Then, the potential targets of the active compounds were predicted by pharmacophore mapping approach and mapped with the target genes of the specific disease.

The compound-target network and Protein-Protein Interaction (PPI) network were built by Cytoscape software.

The core targets were selected by degree values.

Furthermore, GO biological process analysis and KEGG pathway enrichment analysis were carried out to investigate the possible mechanisms involved in the anti-hepatic fibrosis effect of DSLHG.

The predicted results showed that there were 108 main active components in the DSLHG formula.

Moreover, there were 192 potential targets regulated by DSLHG, of which 86 were related to liver fibrosis, including AKT1, EGFR, and IGF1R.

Mechanistically, the anti-liver fibrosis effect of DSLHG was exerted by interfering with 47 signaling pathways, such as PI3K-Akt, FoxO signaling pathway, and Ras signaling pathway.

Network analysis showed that DSLHG could generate the antifibrosis action by affecting multiple targets and multiple pathways, which reflects the multicomponent, multitarget, and multichannel characteristics of traditional Chinese medicine and provides novel basis to clarify the mechanisms of anti-liver fibrosis of DSLHG.

American Psychological Association (APA)

Tao, Yueying& Tian, Kunming& Chen, Ji& Tan, Danfeng& Liu, Yan& Xiong, Yongai…[et al.]. 2019. Network Pharmacology-Based Prediction of the Active Compounds, Potential Targets, and Signaling Pathways Involved in Danshiliuhao Granule for Treatment of Liver Fibrosis. Evidence-Based Complementary and Alternative Medicine،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1148999

Modern Language Association (MLA)

Tao, Yueying…[et al.]. Network Pharmacology-Based Prediction of the Active Compounds, Potential Targets, and Signaling Pathways Involved in Danshiliuhao Granule for Treatment of Liver Fibrosis. Evidence-Based Complementary and Alternative Medicine No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1148999

American Medical Association (AMA)

Tao, Yueying& Tian, Kunming& Chen, Ji& Tan, Danfeng& Liu, Yan& Xiong, Yongai…[et al.]. Network Pharmacology-Based Prediction of the Active Compounds, Potential Targets, and Signaling Pathways Involved in Danshiliuhao Granule for Treatment of Liver Fibrosis. Evidence-Based Complementary and Alternative Medicine. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1148999

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1148999