Evidence map›Paper›PMID 40421218›Full record

ArticleFrontiers in pharmacology2025

Exploring the mechanisms and targets of proton pump inhibitors-induced osteoporosis through network toxicology, molecular docking, and molecular dynamics simulations.

Yaqi Mu, Yaqi Zhou, Xinan Zhang, Yiming Shao

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Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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9citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yaqi MuDepartment of Pharmacy, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Yaqi ZhouDepartment of Orthopedics, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Xinan ZhangDepartment of Orthopedics, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Yiming ShaoCenter of Stem Cell and Regenerative Medicine, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Proton pump inhibitors (PPIs) are widely used for the treatment of acid-related disorders, but long-term use has been increasingly associated with an elevated risk of osteoporosis. However, the underlying molecular mechanisms and specific targets of PPIs-induced bone loss remain poorly understood. This study aimed to explore the molecular mechanisms and key genes of PPIs-induced osteoporosis using network toxicology, molecular docking, and molecular dynamics simulations. Methods: We identified common targets of four widely used PPIs (omeprazole, lansoprazole, pantoprazole, and rabeprazole) and osteoporosis by screening large-scale biological databases. A protein-protein interaction network was constructed, and key hub genes were determined based on topological parameters such as degree, betweenness centrality, and closeness centrality. Enrichment analysis was performed to explore the biological processes, cellular components, molecular functions, and KEGG pathways associated with the overlapping targets. Molecular docking was conducted to evaluate the binding affinities between PPIs and their potential targets, and molecular dynamics simulations were employed to assess the stability of these interactions over time. Results: We identified 35 potential targets for omeprazole-induced osteoporosis, 39 for lansoprazole, 29 for pantoprazole, and 29 for rabeprazole. Topological analysis of the protein-protein interaction networks revealed the hub genes for each PPI: epidermal growth factor receptor (EGFR) for omeprazole, estrogen receptor 1 (ESR1) for lansoprazole, EGFR for pantoprazole, and Proto-oncogene tyrosine-protein kinase SRC for rabeprazole. Molecular docking demonstrated strong and stable binding affinities between PPIs and their respective targets, with binding energies all below -5 kcal/mol. Molecular dynamics simulations confirmed the structural stability of these complexes, characterized by low root mean square deviation and root mean square fluctuation values and consistent hydrogen bond formation. Conclusion: This study identified EGFR, ESR1, and SRC as key regulatory genes in PPIs-induced osteoporosis, highlighting their roles in bone metabolism. The stable interactions between PPIs and these targets suggest their involvement in bone loss, providing a foundation for future experimental validation.

Indexed as

molecular dockingmolecular dynamics simulationnetwork toxicologyosteoporosisproton pump inhibitor

Identifiers

PMID40421218
PMCPMC12104171

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.