A network pharmacology approach to explore active compounds and pharmacological mechanisms of a patented Chinese herbal medicine in the treatment of endometriosis

采用网络药理学方法探索专利中药治疗子宫内膜异位症的有效成分和药理机制

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作者:Yan Wu, Yuhang Zhu, Ningning Xie, Hui Wang, Fangfang Wang, Jue Zhou, Fan Qu

Conclusion

The network pharmacological strategy integrates molecular docking to unravel the molecular mechanism by which QUF protects against endometriosis. Our findings not only confirm the clinical effectiveness of QUF but also provide a foundation for further experimental study.

Methods

A QUF target and endometriosis-related gene set was identified by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) databases and five disease-gene databases. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed, and a protein-protein interaction (PPI) network was established to discover the potential mechanism. MalaCards was searched for targets and signaling pathways related to endometriosis, and the search

Objective

Endometriosis is a common benign disease in women of reproductive age. Qu's formula (QUF) is a patented Chinese herbal medicine for treating endometriosis that has been proven to be effective in treating and preventing the recurrence of endometriosis. This study is aimed to discover its molecular mechanism and to explore the potential drug targets.

Results

A compound-target network with 117 nodes (94 genes and 23 active compounds) and 224 edges was generated. The results of GO and KEGG analyses indicated that QUF could act by regulating the immune response, apoptosis and proliferation, oxidative stress, and angiogenesis. VEGFA, CXCL8, CCL2, IL1B and PTGS2 were selected for molecular docking analysis from two critical subnetworks with high correlation scores in MalaCards, and the active compounds of QUF had binding potential and high affinity for them. The mRNA expression levels of CCL2, IL1B and PTGS2 significantly decreased after treatment with quercetin. MD simulations showed that the combinations of quercetin and these proteins were relatively stable.

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