Evidence map›Paper›PMID 42283840›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2026

Identification of potential targets of kaempferol for the treatment of intervertebral disc degeneration based on network pharmacology and multi-omics analysis.

Wenqiang Cheng, Libin Yang, Lan Zhao, Jiekun Jian

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Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Wenqiang ChengZhejiang University of Traditional Chinese Medicine, Hangzhou, 310000, China.
Libin YangHangzhou Hospital of Traditional Chinese Medicine Zhejiang Chinese Medical University, Hangzhou, 310000, China. 719037820@qq.com.
Lan ZhaoHangzhou Hospital of Traditional Chinese Medicine Zhejiang Chinese Medical University, Hangzhou, 310000, China. 17326058655@163.com.
Jiekun JianThe First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310000, China. Albert1715209066@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intervertebral disc degeneration (IVDD) is a leading cause of chronic disabling musculoskeletal disorders, with its incidence rising annually among the aging global population. This degenerative process is strongly linked to persistent functional impairment and reduced quality of life in patients, while placing a growing socioeconomic burden on global healthcare systems. Previous studies have demonstrated that kaempferol exerts potent anti-inflammatory effects by modulating pro-inflammatory cytokine expression and attenuating extracellular matrix degradation in degenerated intervertebral discs. However, the precise molecular targets responsible for its therapeutic effects remain unclear. This study integrated network pharmacology, molecular docking, bulk and single-cell transcriptomics, and experimental validation to identify the therapeutic targets of kaempferol in IVDD. Potential targets of kaempferol were predicted using the TCMSP, SwissTargetPrediction, and PharmMapper databases. IVDD-related targets were retrieved from the GeneCards, OMIM, and MalaCards databases. A protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, followed by GO and KEGG enrichment analyses. Hub genes were identified via topological analysis. Molecular docking was conducted using AutoDock Vina. The expression patterns of core targets were validated using two GEO bulk RNA-seq datasets (GSE70362 and GSE147383), one single-cell RNA-seq dataset (GSE251686), and qRT-PCR in IL-1β-induced nucleus pulposus cells. Twenty-one common targets between kaempferol and IVDD were identified. Topological analysis identified three core hub genes-STAT1, CASP1, and NOX4-all significantly upregulated in IVDD tissues. Molecular docking revealed strong binding affinities between kaempferol and these targets, with binding energies ranging from - 6.7 to - 7.9 kcal/mol. Single-cell transcriptomics further confirmed their high expression in nucleus pulposus cells. qRT-PCR analysis demonstrated that kaempferol significantly downregulated STAT1, CASP1, and NOX4 mRNA expression; restored extracellular matrix components (COL2 and ACAN); and suppressed matrix-degrading enzymes (MMP3 and MMP13) in IL-1β-stimulated nucleus pulposus cells. These findings suggest that kaempferol exerts protective effects against IVDD by regulating STAT1, CASP1, and NOX4. The multi-target effects of kaempferol in IVDD provide novel insights and highlight its potential as a therapeutic candidate for IVDD treatment.

Indexed as

Intervertebral Disc DegenerationKaempferolsAnimalsHumansMolecular Docking SimulationNetwork PharmacologyProtein Interaction MapsRatsTranscriptomekaempferolKaempferolsIVDDKaempferolMolecular dockingNetwork pharmacology

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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.