Exploring the Mechanism of Myrrh in the Treatment of Breast Cancer Based on Network Pharmacology and Cell Experiments

This study aimed to investigate the mechanism of action of myrrh in breast cancer (BC) treatment and identify its effective constituents. Data on the compounds and targets of myrrh were collected from the TCMSP, PubChem, and Swiss Target Prediction databases. BC-related targets were obtained from the Genecard database. A protein-protein interaction (PPI) analysis, gene ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted on the intersecting targets of the disease and drug. The key targets of myrrh in BC treatment were identified based on the PPI network. The active constituents of myrrh were determined through reverse-screening using the top 20 KEGG pathways. Macromolecular docking studies, molecular dynamic (MD) simulations, and cell assays were utilized to validate the active constituents and critical targets. Network pharmacology indicated that VEGFA, TP53, ESR1, EGFR, and AKT1 are key targets of myrrh. Pelargonidin chloride, Quercetin, and Naringenin were identified as the active constituents of myrrh. Macromolecular docking showed that Quercetin and Naringenin have strong docking capabilities with ESR1. The results of MD simulation experiments align with those of molecular docking experiments. Cell and western blot assays demonstrated that Quercetin and Naringenin could inhibit MCF-7 cells and significantly reduce the expression of ESR1 protein. The findings reveal the active constituents, key targets, and molecular mechanisms of myrrh in BC treatment, providing scientific evidence that supports the role of myrrh in BC therapy. Furthermore, the results suggest that network pharmacology predictions require experimental validation for reliability.

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Journal
Chemical Biology & Drug Design
Published
2024-08-01
DOI
https://doi.org/10.1111/cbdd.14604
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.36

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article

Exploring the Mechanism of Myrrh in the Treatment of Breast Cancer Based on Network Pharmacology and Cell Experiments

Mingqi Qiao, YU Xufeng, Jieqiong Wang, Tao Wu et al.
1 citations
Chemical Biology & Drug Design
Computational Drug Discovery Methods
0.36
article

Exploring the Mechanism of Myrrh in the Treatment of Breast Cancer Based on Network Pharmacology and Cell Experiments

Mingqi Qiao, YU Xufeng, Jieqiong Wang, Tao Wu, Xianmei Chen, Qu Mengrou
article en
1 citations

Abstract

This study aimed to investigate the mechanism of action of myrrh in breast cancer (BC) treatment and identify its effective constituents. Data on the compounds and targets of myrrh were collected from the TCMSP, PubChem, and Swiss Target Prediction databases. BC-related targets were obtained from the Genecard database. A protein-protein interaction (PPI) analysis, gene ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted on the intersecting targets of the disease and drug. The key targets of myrrh in BC treatment were identified based on the PPI network. The active constituents of myrrh were determined through reverse-screening using the top 20 KEGG pathways. Macromolecular docking studies, molecular dynamic (MD) simulations, and cell assays were utilized to validate the active constituents and critical targets. Network pharmacology indicated that VEGFA, TP53, ESR1, EGFR, and AKT1 are key targets of myrrh. Pelargonidin chloride, Quercetin, and Naringenin were identified as the active constituents of myrrh. Macromolecular docking showed that Quercetin and Naringenin have strong docking capabilities with ESR1. The results of MD simulation experiments align with those of molecular docking experiments. Cell and western blot assays demonstrated that Quercetin and Naringenin could inhibit MCF-7 cells and significantly reduce the expression of ESR1 protein. The findings reveal the active constituents, key targets, and molecular mechanisms of myrrh in BC treatment, providing scientific evidence that supports the role of myrrh in BC therapy. Furthermore, the results suggest that network pharmacology predictions require experimental validation for reliability.

Chemical Biology & Drug DesignVol. 104(2)
Shandong University of Traditional Chinese Medicine (CN), Innovation Team (China) (HK)
Jinan Science and Technology Bureau
Good health and well-being
Openalex Percentile: Top 37%
Computational Drug Discovery Methods
0.36
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