Exploration in the Mechanism of Ginsenoside Rg5 for the Treatment of Osteosarcoma by Network Pharmacology and Molecular Docking

Objective Osteosarcoma is a primary malignancy originating from mesenchymal tissue characterized by rapid growth, early metastasis and poor prognosis. Ginsenoside Rg5 (G‐Rg5) is a minor ginsenoside extracted from Panax ginseng C.A. Meyer which has been discovered to possess anti‐tumor properties. Th...

Full description

Saved in:
Bibliographic Details
Published inOrthopaedic surgery Vol. 16; no. 2; pp. 462 - 470
Main Authors Liu, Ming‐yang, Jiang, Dong‐xin, Zhao, Xiang, Zhang, Liang, Zhang, Yu, Liu, Zhen‐dong, Liu, Run‐ze, Li, Hai‐jun, Rong, Xiao‐yu, Gao, Yan‐zheng
Format Journal Article
LanguageEnglish
Published Melbourne John Wiley & Sons Australia, Ltd 01.02.2024
John Wiley & Sons, Inc
Wiley
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Objective Osteosarcoma is a primary malignancy originating from mesenchymal tissue characterized by rapid growth, early metastasis and poor prognosis. Ginsenoside Rg5 (G‐Rg5) is a minor ginsenoside extracted from Panax ginseng C.A. Meyer which has been discovered to possess anti‐tumor properties. The objective of current study was to explore the mechanism of G‐Rg5 in the treatment of osteosarcoma by network pharmacology and molecular docking technology. Methods Pharmmapper, SwissTargetPrediction and similarity ensemble approach databases were used to obtain the pharmacological targets of G‐Rg5. Related genes of osteosarcoma were searched for in the GeneCards, OMIM and DrugBank databases. The targets of G‐Rg5 and the related genes of osteosarcoma were intersected to obtain the potential target genes of G‐Rg5 in the treatment of osteosarccoma. The STRING database and Cytoscape 3.8.2 software were used to construct the protein–protein interaction (PPI) network, and the Database for Annotation, Visualization and Integrated Discovery (DAVID) platform was used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. AutoDock vina software was used to perform molecular docking between G‐Rg5 and hub targets. The hub genes were imported into the Kaplan–Meier Plotter online database for survival analysis. Results A total of 61 overlapping targets were obtained. The related signaling pathways mainly included PI3K‐Akt signaling pathway, Proteoglycans in cancer, Lipid and atherosclerosis and Kaposi sarcoma‐associated herpesvirus infection. Six hub targets including PIK3CA, SRC, TP53, MAPK1, EGFR, and VEGFA were obtained through PPI network and targets‐pathways network analyses. The results of molecular docking showed that the binding energies were all less than –7 kcal/mol. And the results of survival analysis showed TP53 and VEGFA affect the prognosis of sarcoma patients. Conclusion This study explored the possible mechanism of G‐Rg5 in the treatment of osteosarcoma using network pharmacology method, suggesting that G‐Rg5 has the characteristics of multi‐targets and multi‐pathways in the treatment of osteosarcoma, which lays a foundation for the follow‐up experimental and clinical researches on the therapeutic effects of G‐Rg5 on osteosarcoma. The pharmacological targets of Rg5 were selected from the Pharmmapper, SwissTargetPrediction and similarity ensemble approach databases. The osteosarcoma genes were found from the GeneCards, OMIM, and drugbank databases.The targets of G‐Rg5 and the related genes of osteosarcoma were intersected to obtain the potential target genes of G‐Rg5 against osteosarcoma. The STRING database and Cytoscape 3.8.2 software were used to construct the protein–protein interaction (PPI) network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were identified by the DAVID database. Hub genes were obtained through PPI network and targets‐pathways network analyses. AutoDock vina software was used to perform molecular docking between G‐Rg5 and hub targets. The hub genes were then imported into the Kaplan–Meier Plotter online database for survival analysis.
ISSN:1757-7853
1757-7861
DOI:10.1111/os.13971