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Volume 21, Issue 1
  • ISSN: 1573-4099
  • E-ISSN: 1875-6697
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Abstract

Background

Sanguinarine (SAN) has been reported to have antioxidant, anti-inflammatory, and antimicrobial activities with potential for the treatment of osteoporosis (OP).

Objective

This work purposed to unravel the molecular mechanisms of SAN in the treatment of OP.

Methods

OP-related genes and SAN-related targets were predicted from public databases. Differential expression analysis and VennDiagram were adopted to detect SAN-related targets against OP. Protein-protein interaction (PPI) network was served for core target identification. Molecular docking and DeepPurpose algorithm were further adopted to investigate the binding ability between core targets and SAN. Gene pathway scoring of these targets was calculated utilizing gene set variation analysis (GSVA). Finally, we explored the effect of SAN on the expressions of core targets in preosteoblastic MC3T3-E1 cells.

Results

A total of 21 candidate targets of SAN against OP were acquired. Furthermore, six core targets were identified, among which CASP3, CTNNB1, and ERBB2 were remarkably differentially expressed in OP and healthy individuals. The binding energies of SAN with CASP3, CTNNB1, and ERBB2 were -6, -6.731, and -7.162 kcal/mol, respectively. Moreover, the GSVA scores of the Wnt/calcium signaling pathway were significantly lower in OP cases than in healthy individuals. In addition, the expression of CASP3 was positively associated with Wnt/calcium signaling pathway. CASP3 and ERBB2 were significantly lower expressed in SAN group than in DMSO group, whereas the expression of CTNNB1 was in contrast.

Conclusion

CASP3, CTNNB1, and ERBB2 emerge as potential targets of SAN in OP prevention and treatment.

© 2025 Bentham Science Publishers
© 2025 The Author(s). Published by Bentham Science Publishers. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
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Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology
Curr. Computeraided Drug Des. 21, 83 (2025); https://doi.org/10.2174/0115734099282231240214095025
/content/journals/cad/10.2174/0115734099282231240214095025
/content/journals/cad/10.2174/0115734099282231240214095025
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Supplementary material is available on the publisher’s website along with the published article. Supplementary Table 1. Targets for sanguinarine and osteoporosis-related genes were obtained from online databases. Supplementary Table 2. Differentially expressed genes between healthy individuals and osteoporosis cases in GSE7158 dataset. Supplementary Table 3. A total of 21 intersecting targets.

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  • Article Type:     Research Article
Keyword(s): deep learning technology; molecular docking; network pharmacology analysis; Osteoporosis; protein-protein interaction network; sanguinarine

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