Predicting Active Components of Chinese Herbal Medicines for Treating Bone Aging Based on Reverse Network Pharmacology and Molecular Docking

Lirong GUO; Xiang LIU; Jiahao LI; Ying ZHANG

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Lirong GUO, Xiang LIU, Jiahao LI, Ying ZHANG. Predicting Active Components of Chinese Herbal Medicines for Treating Bone Aging Based on Reverse Network Pharmacology and Molecular Docking[J]. Journal of Kunming Medical University.

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Predicting Active Components of Chinese Herbal Medicines for Treating Bone Aging Based on Reverse Network Pharmacology and Molecular Docking

Lirong GUO¹,
Xiang LIU²,
Jiahao LI³,
Ying ZHANG^{1, 4
,
,}

1.
School of Nursing，Kunming Medical University，Kunming Yunnan 650500
2.
Department of Orthopedics，Yunnan First People’s Hospital，Kunming Yunnan 650032
3.
Department of Intensive Care Medicine，The First Affiliated Hospital of Guangxi Medical University，Nanning Guangxi 530021
4.
Department of Basic Medicine of Chuxiong Medical College，Chuxiong Yunnan 675005，China

Received Date: 2025-07-17

Abstract

Abstract

Objective To explore potential active components of Chinese herbal medicines （CHMs） for treating bone aging and their mechanisms of action using reverse network pharmacology and molecular docking techniques, with preliminary experimental validation. Methods Transcriptomic data were obtained from the GEO database. GEO2R was used to analyze differentially expressed genes, identifying a characteristic bone aging gene set. A Protein-Protein Interaction （PPI） network was constructed to identify key targets, followed by Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses. Core disease targets were identified by intersecting results from three algorithms （Degree, MCC, and Stress）. These core targets were used to reversely identify CHMs with potential anti-bone aging effects, followed by drug activity analysis. Molecular docking was performed between active components and core disease targets to further screen representative compounds. Senescent bone cell models and animal models were established for preliminary efficacy verification. Cell experiments were divided into 4 groups: control group （Control）, bone aging group （D-Gal）, quercetin + bone aging group （Que+D-Gal）, and quercetin group （Que）. An aging bone cell model was constructed using D-galactose （10 g/L）, and quercetin （10 µM） was used to treat D-Gal-induced senescent cells. Cellular senescence was observed by SA-β-Gal staining, and p53 protein expression was detected by immunofluorescence and Western blot. Twenty-four C57BL/6J mice were randomly divided into 4 groups （6 mice per group） with the same grouping as cells. A bone aging mouse model was established via subcutaneous injection of D-galactose （500 mg/kg） on the dorsal neck, and quercetin （50 mg/kg） was administered by gavage. HE staining of femoral sections was used to observe bone protective effects. Results A total of 669 characteristic bone aging genes were identified, primarily enriched in as PI3K-AKT, MAPK, osteoclast differentiation, and longevity regulation pathways. Core targets were TP53, HSPA4, ESR1, ERBB2, GSK3B, and STAT1. Reverse screening identified CHMs acting on all six core targets: Ardisia japonica , Artemisia argyi , Zingiber officinale, Glycine max , Carthamus tinctorius , Cannabis sativa , and Smilax glabra. The main active components included β-sitosterol, stigmasterol, quercetin, and luteolin. Molecular docking between the six core targets and the active components revealed that stigmasterol, quercetin, and luteolin exhibited strong binding （binding energy ≤ -7 kcal/mol） to all six core targets. Considering both binding energy and oral bioavailability, quercetin was selected as the representative drug for this study. SA-β-Gal staining showed that the positive area of senescent cells in the Que+D-Gal group was significantly reduced compared to the D-Gal group（P < 0.01）. Immunofluorescence and Western blot confirmed that that p53 fluorescence signal intensity （P < 0.01） and p53 protein expression （P < 0.001） were significantly decreased in the Que+D-Gal group compared to the D-Gal group. Conclusion Through reverse network pharmacology, this study screened active components from traditional Chinese herbs such as Ardisia japonica and Artemisia argyi from large databases. Components like stigmasterol, quercetin, and luteolin may regulate the key aging target TP53 and synergize with genes in bone metabolism-related pathways （e.g., ESR1, GSK3B）, thereby exerting bone protective effects.
- Bone aging,
- Osteoporosis,
- Network pharmacology,
- Molecular docking simulation,
- Quercetin

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References(49)

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