Ning Li1,
Keixin Liu2,
Mai Yu2,
Mingjuan Liu2,
Shani Li2,
Wei Cai2,
Aiping Tian1 
For correspondence:- Aiping Tian Email: aipingtian@126.com
Accepted: 27 April 2022 Published: 31 May 2022
Citation: Li N, Liu K, Yu M, Liu M, Li S, Cai W, et al. Systematic elucidation of the traditional Chinese medicine prescription Danxiong particles via network pharmacology and molecular docking. Trop J Pharm Res 2022; 21(5):981-987 doi: 10.4314/tjpr.v21i5.11
© 2022 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..
Purpose: To investigate the pharmacological effect of the traditional Chinese medicine (TCM) prescription Danxiong particles (TDX105) and its mechanism of action.
Methods: The active compound and targets of TDX105 were investigated via network pharmacology. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were enriched, and protein-protein interaction network (PPI) was constructed. A network of ‘components-targets-pathways’ was developed with Cytoscape 3.8.0 software, while the formation of molecular docking analysis was conducted using Autodock vina software.
Results: There were 304 compounds and 482 targets identified in total. Genes with degree ≥ mean node values were selected as the crucial targets, and string database was to be combined to 64 targets identified with cytoscape so as to draw a protein interaction map. A total of 137 pathways were enriched from 64 targets involving mainly 10 pathways, for example, PI3K-Akt signaling pathway, pathways in cancer, human cytomegalovirus infection and focal adhesion. Then, compound-target and compound-target-pathways were constructed using cytoscape (3.8.0). Finally, the five most active compounds, viz, quercetin, myricetin, luteolin, ellagic acid and kaempferol, and the top ten targets AKT1, GAPDH, TP53, ALB, EGFR, MAPK3, JUN, MAPK1, SRC and ESR1 were selected for molecular docking. These targets and compounds had strong interactions through a combination of hydrogen bonds and hydrophobic forces.
Conclusion: The mechanism of action of TDX105 has been successfully explained using the combination of network pharmacology and molecular docking. This may offer a solid foundation to the clinical use of TDX105, and further strengthen the prospects of its development for clinical use.
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