Kaempferol inhibits osteoclast differentiation and bone resorption by targeting the TNF-α/NF-κB and SRC/PI3K/AKT signaling pathways

Abstract

Kaempferol exerts an important regulatory effect on osteoporosis, while its mechanism has not been fully elucidated. This study aimed to investigate the molecular mechanism underlying the anti-osteoporotic effect of kaempferol. Potential targets of kaempferol (197 genes) were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction databases. Meanwhile, osteoporosis-related targets (986 non-redundant genes) were compiled from disease-specific databases. Protein-protein interaction (PPI) network analysis was performed to identify 37 core targets. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed 3,295 biological processes and 205 signaling pathways, respectively. Molecular docking results demonstrated that kaempferol has high binding affinities with AKT, NF-κB, PI3K, SRC, and TNF-α. For experimental validation, RAW 264.7 cells were used: cell viability was assessed via the Cell Counting Kit 8 (CCK8) assay; osteoclast differentiation and bone resorption were evaluated through tartrate-resistant acid phosphatase (TRAP) staining and toluidine blue staining, respectively; oxidative stress markers (reactive oxygen species (ROS), superoxide dismutase (SOD), and malondialdehyde (MDA) were measured by enzyme-linked immunosorbent assay (ELISA); and molecular mechanisms were analyzed using quantitative real-time polymerase chain reaction (RT-qPCR) and Western blotting to detect osteoclast-related molecules (RANK, CSF1R, c-Fos, CTSK, and MMP-9) and signaling pathway proteins.​ Kaempferol significantly increased the viability of RAW 264.7 cells (P < 0.05). TRAP and toluidine blue staining showed dose-dependent decreases in osteoclast number and resorption area (P < 0.05). Additionally, kaempferol concentration-dependently reduced ROS and MDA levels while increasing SOD activity. It also significantly downregulated the expression of osteoclastogenesis-related genes (RANK, CSF1R, c-Fos, CTSK, and MMP-9; P < 0.05) and inhibited the activation of the TNF-α/NF-κB and SRC/PI3K/AKT signaling pathways.​ The predictions from network pharmacology were validated experimentally, confirming that kaempferol exerts dual inhibitory effects on osteoclast differentiation and oxidative stress. The coordinated inhibition of RANK/M-CSF signaling and its downstream TNF-α/NF-κB and SRC/PI3K/AKT pathways underpins the anti-resorptive activity of kaempferol.​.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-37688-4.

Introduction

Osteoporosis (OP) is a metabolic bone disorder characterized by reduced bone mass, deterioration of bone microarchitecture, and impaired bone mineral density, leading to increased fracture risk¹. In Traditional Chinese Medicine (TCM) theory, OP falls under the categories of “bone weakness” (gu xu) and “bone obstruction” (gu bi), with its primary pathogenesis attributed to kidney qi deficiency, qi-blood stagnation, and associated musculoskeletal pain or numbness. Studies have shown that various Chinese herbal medicines can effectively regulate the differentiation of bone marrow mesenchymal stem cells (BMSCs), thereby preventing or treating OP².​.

Osteoclasts (OCs), derived from the monocyte-macrophage lineage, play a pivotal role in bone resorption. During differentiation, OCs degrade the bone microstructure, compromising bone mechanical strength and increasing bone fragility, which in turn elevates fracture susceptibility^3,4. A critical step in osteoclastogenesis involves the interaction between receptor activator of nuclear factor kappa-B ligand (RANKL) and its receptor RANK; this interaction promotes OC formation, activation, and survival⁵. The RAW 264.7 is a murine monocyte/macrophage cell line, is widely used as an in vitro osteoclast model, as it can differentiate into functional OCs upon RANKL stimulation. Its simplicity, reliability, and reproducibility make it a preferred choice for studying OP-related osteoclast mechanisms⁶.​.

Traditional Chinese Medicine (TCM) has unique advantages in the prevention and treatment of osteoporosis. In clinical practice, medicinal materials such as Psoralea corylifolia L., Epimedium brevicornu Maxim., and Pueraria lobata (Willd.) Ohwi are often combined into formulas, including Zuogui Pill and Zhuanggu Formula. Studies have shown that these formulas can regulate the balance of bone metabolism through the effects of “tonifying the kidney to strengthen bones, activating blood circulation and dredging collaterals”^7,8. Modern pharmacological studies have demonstrated that the anti-osteoporotic effects of such TCMs are closely associated with their flavonoid active ingredients, among which kaempferol is one of the core effective components commonly found in these TCMs⁹. Existing studies have confirmed that kaempferol can affect the activities of osteoblasts and osteoclasts by regulating bone metabolism-related signaling pathways, serving as an important material basis for the bone-protective effects of TCM¹⁰. Kaempferol is a flavonoid active component widely present in various plants such as broccoli, tea, and raspberries. It exhibits multiple biological activities, including antioxidant, anti-inflammatory, antibacterial, anti-tumor, cardiovascular protective, neuroprotective, anti-diabetic, and estrogen-modulating effects^11–14. However, the specific molecular mechanisms underlying the anti-osteoporotic effects of kaempferol as an active component of TCM have not been fully elucidated to date. Therefore, this study aims to systematically investigate its mechanism of action by combining network pharmacology with in vitro experiments, so as to provide theoretical support for the modern interpretation and clinical application of TCM in the treatment of osteoporosis.

Preliminary network pharmacology studies by our team have identified potential common drug targets between kaempferol and osteoporosis. Additionally, existing research suggests that kaempferol may exert beneficial effects in the treatment of OP¹⁵. To further elucidate its mechanism, this study uses the RAW 264.7 cell line to investigate the regulatory effects of kaempferol on osteoclast differentiation and bone resorption activity. Our findings aim to provide theoretical support for the clinical application of kaempferol in OP management.

Materials and methods

Identification of Kaempferol target genes​

Targets associated with kaempferol were identified using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, https://old.tcmsp-e.com/index.php) and the SwissTargetPrediction database (http://www.swisstargetprediction.ch/)¹⁶. After screening, these targets were standardized by inputting them into the UniProt database (https://www.uniprot.org) to obtain their official gene names^17,18.​.

Screening of OP-related targets​

Using “osteoporosis” as the keyword and “Homo sapiens” as the species, OP-related targets were collected from the GeneCards (https://www.genecards.org/)¹⁹, Therapeutic Target Database (TDD, http://db.idrblab.net/ttd/), and Online Mendelian Inheritance in Man (OMIM, https://www.omim.org/) databases²⁰. Duplicate entries were removed to screen for unique osteoporosis-associated target genes.​.

Acquisition of Kaempferol-OP common targets and construction of the protein–protein interaction (PPI) network​

The intersection of kaempferol-related targets and OP-related targets was analyzed using the bioinformatics platform (http://www.bioinformatics.com.cn/). The resulting common targets were then uploaded to the STRING database (https://stringdb.org/) to identify the most significant core genes with high confidence²¹, with “Homo sapiens” specified as the target species for PPI network construction. Subsequently, the data were imported into Cytoscape 3.10.2 software for visual analysis. The CytoHubba plug-in was used to determine core targets based on the degree ranking of network nodes.​.

Gene ontology (GO) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis​

GO functional annotation and KEGG enrichment analysis of the common target genes were performed using the bioinformatics platform (http://www.bioinformatics.com.cn/)—a comprehensive web service for biomedical data analysis and visualization. The results were presented as bubble plots and network plots. Molecular pathway maps were retrieved from the KEGG database (https://www.kegg.jp)²².​.

Molecular Docking verification​

The chemical structure file of kaempferol was retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/)²³, and Open Babel 2.3.2 software was used to convert the Structure Data File (SDF) to Protein Data Bank (PDB) format²⁴. Receptor proteins were obtained from the PDB database. PyMOL 2.3.4 software was used to remove water molecules and coordinate bonds from the receptor proteins²⁵. AutoDockTools software was employed to modify the receptor proteins, and both the receptor proteins and ligand (kaempferol) were converted to PDBQT format²⁶. AutoDock Vina 1.1.2 was used to perform molecular docking between the receptor proteins and kaempferol, and Discovery Studio was used to analyze the docking results. PyMOL was utilized for visualizing the docking outcomes.

Drugs and reagents

RANKL (cat. no. HY-P73388) and kaempferol (cat. no. HY-14590) were purchased from MCE (MedChemExpress). The CCK8 Cell Proliferation and Cytotoxicity Assay Kit (cat. no. CA1210), Hematoxylin-Eosin (HE) Stain Kit (cat. no. G1120), Toluidine Blue O Solution (cat. no. G3668), and BCA Protein Assay Kit (cat. no. PC0020) were obtained from Solarbio. The Reactive Oxygen Species (ROS) ELISA Detection Kit (cat. no. CB10366-Mu), Superoxide Dismutase (SOD) ELISA Detection Kit (cat. no. CB10221-Mu), and Malondialdehyde (MDA) ELISA Detection Kit (cat. no. CB10205-Mu) were supplied by COIBO BIO.​Primary antibodies included: CSF1R Antibody (1:1000, cat. no. AF0080), c-Fos Antibody (1:1000, cat. no. AF5354), CTSK Antibody (1:1000, cat. no. DF6614), TNF-α Antibody (1:1000, cat. no. AF7014), Phospho-nuclear factor-κB (NF-κB) p105/p50 (Ser337) Antibody (1:1000, cat. no. AF3219), Phospho-NF-κB p100/p52 (Ser872) Antibody (1:1000, cat. no. AF3375), NFAT2 Antibody (1:1000, cat. no. DF6446), Phospho-Src (Tyr419) Antibody (1:1000, cat. no. AF3162), Src Antibody (1:1000, cat. no. AF6161), PI3K p85α Antibody (1:1000, cat. no. AF6241), Phospho-PI3K p85α (Tyr607) Antibody (1:1000, cat. no. AF3241), pan-AKT1/2/3 Antibody (1:1000, cat. no. AF6261), Phospho-AKT1/2/3 (Ser473) Antibody (1:1000, cat. no. AF0016), and GAPDH Antibody (1:1000, cat. no. AF7021), all from Affinity. The secondary antibody Goat Anti-Rabbit IgG (H + L) HRP (1:5000, cat. no. S0001) was also purchased from Affinity.​.

Cell culture and drug intervention​

Murine monocytic macrophage RAW 264.7 cells were obtained from Zhejiang Meisen Cell Technology Co., Ltd. Cells were maintained in Dulbecco’s Modified Eagle’s Medium (DMEM; Hyclone, Logan, UT, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS; Hyclone, Logan, UT, USA) and cultured at 37 °C in a humidified atmosphere containing 5% CO₂. For osteoclast differentiation induction, cells were cultured in α-Minimum Essential Medium (α-MEM; Gibco, Grand Island, NY, USA) supplemented with 10% FBS and 50 ng/mL recombinant mouse RANKL, with the culture maintained for 9 days.​.

CCK8 assay​

Cell viability was evaluated using the CCK8 assay. Briefly, RAW 264.7 cells were seeded at a density of 5 × 10³ cells per well in a 96-well plate. After seeding, cells were treated with kaempferol at different concentrations (0, 0.1, 1, 2.5, 5, and 10 µmol/L) and incubated for 24 h at 37 °C in a 5% CO₂ humidified atmosphere. Whereafter, 10% (v/v) CCK8 solution was added to each well, and the plate was further incubated for 2 h. The absorbance at 450 nm was measured using a microplate reader.​.

Tartrate-resistant acid phosphatase (TRAP) staining​

To induce osteoclast differentiation, RAW 264.7 cells were cultured in medium supplemented with 50 ng/mL RANKL and treated with kaempferol at concentrations of 2 µmol/L, 5 µmol/L, and 10 µmol/L, respectively. After 5 days of RANKL stimulation, cells were washed twice with phosphate-buffered saline (PBS) and fixed in 4% paraformaldehyde for 20 min at room temperature. TRAP staining was then performed according to the manufacturer’s instructions of the TRAP staining kit. Cells were defined as osteoclasts if they were TRAP-positive (stained wine red) and contained ≥ 3 nuclei. Osteoclasts were counted under an inverted light microscope, and images were captured for documentation.

Toluidine blue staining of bovine bone slices for osteoclast resorption

Bovine slices (Beijing Keruimei technology CO. LTD) were dipped in PBS and medium with 10-fold high concentration of streptomycin and penicillin for 12 h, respectively. RAW264.7 cells were seeded onto the slices at a density of 1 × 10⁵ cells/well with the inducing factors or coupled with kaempferol treatment. The medium was replaced every alternate day. After 10 days of culture, the slices were washed with PBS followed by fixation with 4% paraformaldehyde for 20 min. After this, cells were washed twice with PBS and removed from bone slices via ultrasonication in 0.25 M NH4OH for 3 times followed by distilled water. Resorption pit formation was stained by 0.1% toluidine blue (Amersco, USA) for 10 min at room temperature. The slices were then rinsed with distilled water more than 5 times to excluderesidues. Resorption pits are now stained in dark blue and images were taken via light microscopy.

The levels of ROS, SOD and MDA in the cells were detected by Elisa

The cell samples were lysed first, then coated with a reaction plate. Non-specific sites were blocked, followed by adding the samples and a specific antibody for incubation to allow their binding. The plate was washed, and an enzyme-labeled secondary antibody was added; after incubation, the plate was washed again. Finally, a substrate was added for color development, and the absorbance value was detected.

Western blot analysis

The cells were harvested, and total protein was extracted. The protein concentration of the supernatant was determined using the BCA Protein Assay kit. Total proteins were subjected to SDS-PAGE and transferred to PVDF membranes. Membranes were blocked with 5% skim milk in Tris-buffered saline containing 0.1% Tween 20 (TBST) for 1 h. Then, 1% skim milk powder was used according to a 1:1000 dilution of the primary antibody, CSF1R, c-Fos, CTSK, GAPDH, SRC, p-SRC, PI3K, p-PI3K, AKT, and p-AKT. The PVDF membrane was incubated with the primary antibody at 4 °C overnight. The appropriate secondary antibody, horseradish peroxidase (HRP), was coupled and incubated for 2 h at room temperature. After washing three times, the signal was detected by the enhanced luminescence method. The intensity of the protein bands was calculated using ImageJ software.

RT-qPCR for gene expression analysis

Total RNAs were extracted using the Trizol reagent according to the standard protocol. The cDNA was synthesized from 500 ng of total RNA using PrimeScript™ RT reagent Kit with gDNA Eraser (Takara, Dalian China) according to the manufacturer’ s instructions, and performed the analysis of gene expression using TB Green™ Ex Taq™ II (Tli RnaseH) from Takara on a Roche lightCycler 96 instrument with 0.4 µM gene-specific primer pairs respectively (Table 1); GAPDH amplification was used as an internal reference for each sample. The PCR reaction system was as follows: denaturation at 95 °C for 15 min, followed by cycling at 95 °C for 10 s, 50 °C for 31 s, and 72 °C for 30 s, for a total of 40 cycles. Finally, the expression levels were calculated using the 2^−ΔΔCt method.

Table 1.

q-PCR primer sequences.

Gene	Primer sequences
RANK	Forward: 5′-GTGGAATTGGGTCAATGATGC-3′
	Reverse: 5′-CTTTCAGTCCCGGTGAAACA-3′
CSF1R	Forward: 5′-GACATCGAGAACCTGCTGAAG-3′
	Reverse: 5′-TCCAGGATGATGATGATGGTG-3′
c-Fos	Forward: 5′-AGTGCCAACTTTATCCCCAC-3′
	Reverse: 5′-CTTGGAGTGTATCTGTCAGC-3′
CTSK	Forward: 5′-TGACACTCTCTATACCCCAG-3′
	Reverse: 5′-TCACACAGTCCACAAGATTCTG-3′
MMP-9	Forward: 5′-TCTGGATAAGTTGGGTCTAGG-3′
	Reverse: 5′-GTTTCCAGAGAACTCCTTATCC-3′
GAPDH	Forward: 5’-AGGTCGGTGTGAACGGATTTG-3’
	Reverse: 5’-TGTAGACCATGTAGTTGAGGTCA-3’

Statistical analysis

The data were graphed and statistically analyzed using GraphPad prism 8 and SPSS 22.0 software. Measurements were expressed as x ± s. One-way ANOVA was used for comparison of multiple samples, and LSD t-test was used for comparison of two samples.

Results

Network pharmacological screening of Kaempferol and co-acting targets for osteoporosis

In this study, we aimed to explore the potential therapeutic effects of kaempferol on OP. The molecular structure is illustrated in parts A of Fig. 1. Meanwhile, we utilized the TCMSP and SwissTargetPrediction databases to identify 197 target genes associated with kaempferol. We discovered 986 unique genes linked to osteoporosis through the Genecard, TTD, and OMIM databases. As depicted in Fig. 1B, by intersecting these datasets, we identified 56 target genes that are related to both kaempferol and osteoporosis. As shown in Fig. 1C, the interaction diagram of 56 gene-encoded proteins created by the STRING database, in which we filter key proteins with a confidence of 0.9, and get 37 nodes after excluding isolated proteins. In Fig. 2, we further analyzed these 37 nodes using Cytoscape 3.10.2, identifying five core nodes: SRC, PI3K, ESR1, AKT1, and TNF. These results indicate that SRC, PI3K, ESR1, AKT1, and TNF may play a role in the biological effects of kaempferol on osteoporosis.

Fig. 1.

Identification of essential genes associated with kaempferol and osteoporosis. (A)Molecular structure of kaempferol. (B) The relationship between kaempferol and genes associated with osteoporosis. (C) Maps showing protein interactions for genes with high confidence.

Fig. 2.

Visual representation using Cytoscape. In the figure, circles of different colors represent the category/criticality of core targets: Purple circle: Core hub target (SRC); Red circles: Key core targets (AKT1, ESR1, PIK3R1, TNF); Orange circles: Important associated targets (MMP9, CASP3, EGFR, MAPK8, RELA); Yellow circles: Secondary associated targets (all remaining targets). The lines between nodes represent the interaction relationships between target proteins.

GO functional annotation and KEGG signaling pathway enrichment analysis

To elucidate the biological processes and mechanisms associated with the target genes related to the disease, we conducted a GO functional annotation analysis. The findings are presented in Fig. 3, which includes three categories: biological process (BP), cellular component (CC), and molecular function (MF). GO and KEGG enrichment analysis identified 3295 biological processes and 205 KEGG pathways. In Fig. 3A, the BP analysis indicates that the target genes are involved in cellular responses to oxidative stress, including the management of reactive oxygen species and responses to both oxidative and chemical stress. Figure 3B reveals that in the CC category, these genes are predominantly found in membrane microdomain structures, such as membrane rafts. Additionally, the common targets in the MF category are linked to general initiation factors for DNA binding, including nuclear receptor activity and ligand-activated transcription factor activity (see Fig. 3C). Moreover, KEGG pathway enrichment analysis of 56 common targets indicated that these genes are significantly associated with pathways related to atherosclerosis, complications of diabetes, endocrine resistance, TNF signaling, small cell lung cancer, IL-17 signaling, and other pathways (refer to Fig. 4A-C).

Fig. 3.

Network diagram and bubble diagram analysis of GO functional annotation. (A) Biological Process. (B) Cellular Component. (C) Molecular Function.

Fig. 4.

Network diagram and bubble diagram analysis of KEGG signaling pathway. (A) Network diagram. (B) Bubble diagram. (C) TNF signaling pathway, the original image can be referred to the KEGG database (hsa04668)²².

Molecular Docking analysis

In this study, we extracted key molecules from the PPI network, including AKT, NF-κB, PI3K, SRC, and TNF. Subsequently, molecular docking analysis was performed between kaempferol and these proteins. The binding energy, which reflects the strength of molecular interactions, was evaluated. Generally, a binding energy below 0 kcal/mol indicates the presence of binding activity, while a value below − 5.0 kcal/mol signifies strong binding. Notably, a lower binding energy corresponds to a higher binding affinity. As shown in Fig. 5, the binding energies of kaempferol with AKT, NF-κB, PI3K, SRC, and TNF were − 9.54 kcal/mol, −6.94 kcal/mol, −8.04 kcal/mol, −8.61 kcal/mol, and − 6.70 kcal/mol, respectively. These results demonstrate that kaempferol exhibits significant and strong binding affinities with the aforementioned molecules. Thus, kaempferol may alleviate osteoporosis by modulating the signaling pathways mediated by these molecules. However, further experimental validation is required to confirm this hypothesis.

Fig. 5.

Molecular docking. (A) Heatmap of the binding energies between kaempferol and AKT, NF-κB, PI3K, SRC, and TNF proteins, respectively. (B) Three-dimensional (3D) molecular docking models of kaempferol bound to AKT, NF-κB, PI3K, SRC, and TNF proteins, respectively.

Effects of different concentrations of Kaempferol on osteoclast viability, differentiation and bone resorption

As shown in Figs. 6A-B, TRAP staining assay revealed that compared with the control group, low, medium, and high doses of kaempferol significantly reduced the number of osteoclasts, and the proportion of TRAP-positive stained areas also decreased (P < 0.05). These results indicate that kaempferol inhibits osteoclast differentiation of RAW 264.7 cells. Meanwhile, as presented in Fig. 6B, the CCK8 assay showed that low, medium, and high doses of kaempferol exhibited no cytotoxicity to the cells relative to the control group; notably, the cell viability in the high-dose group was significantly increased compared with that in the control group (P < 0.05). In addition, as illustrated in Fig. 6D, toluidine blue staining results demonstrated that, compared with the control group, kaempferol treatment significantly reduced the number and area of bone resorption lacunae formed by osteoclasts on the bone slices, with a dose-dependent inhibitory effect; the high-dose group exhibited the most pronounced inhibition. Collectively, these findings suggest that kaempferol can inhibit osteoclast differentiation and holds promise for development as a novel therapeutic agent or adjuvant therapy.

Fig. 6.

Kaempferol inhibited osteoclast viability, osteoclast differentiation and bone resorption in a concentration-dependent manner. (A) Cell viability assay. (B-C) TRAP staining, 50 μm. (D-E) Toluidine blue-stained bone resorption lacunae appear blue-violet; the reduction in the number of lacunae indicates that the bone resorption function of osteoclasts is inhibited. Scale bar: 50 μm. Compared with the control group, * P < 0.05, *** P < 0.001, ns P > 0.05.

Kaempferol inhibits oxidative stress and expression of osteoclastogenic genes

This study revealed the association between kaempferol and oxidative stress and key genes for osteoclast differentiation. Results, as shown in Figure. 7 A-C, indicated that there was no significant difference in ROS, SOD, and MDA levels between the low kaempferol treatment group and the control group. The levels of ROS and MDA in the medium and high concentration groups were significantly decreased (P < 0.05), and the high concentration group had the most significant inhibitory effect, indicating that the lipid peroxidation damage was alleviated. In addition, the level of SOD was significantly increased in the medium and high concentration groups (P < 0.05), especially in the high concentration group, indicating that the antioxidant capacity was enhanced. The expression of osteoclast differentiation key molecules, including RANK, CSF1R, c-Fos, CTSK, and MMP-9, was also detected. The results, shown in Fig. 7D-I, demonstrated that the expression of these genes was significantly reduced at low, medium, and high concentrations of kaempferol (P < 0.05). These results strongly suggest that kaempferol can inhibit oxidative stress by a concentration-dependent reduction of ROS and MDA, an increase of SOD, and down-regulation of the expression of RANK, CSF1R, c-Fos, CTSK, and MMP-9, which play a role in inhibiting osteoclast-related pathological processes.

Fig. 7.

Detection of oxidative stress-related indicators and osteoclast differentiation-related molecules. (A-C) ELISA was used to detect ROS, SOD, and MDA. (D-H) RT-qPCR was used to detect osteoclast differentiation-related genes, including RANK, CSF1R, c-Fos, CTSK, and MMP-9. (I) WB was used to detect the protein expression of CSF1R, c-Fos and CTSK. Compared with the control group, * P < 0.05, ** P < 0.01, *** P < 0.001, ns P > 0.05.

Kaempferol inhibits the TNF-α/NF-κB and SRC/PI3K/AKT signaling pathway

Previous network pharmacology and molecular docking results indicated that tumor necrosis factor-α (TNF-α), NF-κB, SRC, phosphatidylinositol 3-kinase (PI3K), and protein kinase B (AKT) might be important targets of kaempferol in osteoporosis. Therefore, we used Western blot to verify the effects of kaempferol on these proteins in the context of osteoporosis. As shown in Fig. 8A, compared with the control group, the protein levels of TNF-α, nuclear factor κB1 (p50), nuclear factor κB2 (p52), and nuclear factor of activated T-cells cytoplasmic 1 (NFATC1) were decreased in the low-, medium-, and high-dose kaempferol groups, with the most significant reduction observed in the high-dose group (P < 0.05). As presented in Fig. 8B, compared with the control group, there were no significant differences in the expression levels of total SRC, PI3K, and AKT proteins in the low-, medium-, and high-concentration kaempferol treatment groups (P > 0.05). However, the expression levels of phosphorylated p-Src, p-PI3K, and p-Akt were significantly decreased (P < 0.05), especially at the high concentration (10 µmol/L). These results suggest that kaempferol inhibits osteoclast differentiation, and the underlying mechanism may be associated with the TNF-α/NF-κB and SRC/PI3K/AKT pathways. Moreover, the inhibitory effect of kaempferol is more prominent at high concentrations.

Fig. 8.

Kaempferol inhibits osteoclast differentiation by inactivating the TNF-α/NF-κB and SRC/PI3K/AKT pathway. (A) Protein bands and statistical analysis of P50, P52, TNF-α, and NFATC1. (B) Protein bands and statistical analysis of SRC, PI3K, AKT, and their phosphorylated forms. Compared with the control group, * P < 0.05, ** P < 0.01, *** P < 0.001, ns P > 0.05.

Discussions

In recent years, the regulation of osteocyte function has received extensive attention in the field of osteoporosis research. Through the analysis of drug-related databases and disease-specific databases, this study identified that the key molecules mediating kaempferol’s effects on osteoporosis include TNF-α, NF-κB, SRC, PI3K, and AKT AKT. Molecular docking results demonstrated that kaempferol exhibits high binding affinities with the TNF-α, NF-κB, SRC, PI3K, and AKT proteins. Additionally, the PPI network analysis revealed SRC as a core target, suggesting that this molecule may play a critical role in mediating the anti-osteoporotic effects of kaempferol. This result is highly consistent with previous reports²⁷, which further confirms the reliability of the molecular docking and pathway validation results of this study. This finding thus warrants further in-depth investigation to clarify its underlying mechanisms.

First, RANKL stimulation was used to induce the differentiation of the mouse-derived RAW 264.7 cell line into mature OCs. When TRAP staining was performed on day 7, a large number of TRAP-positive cells were observed. These results confirmed that osteoclast differentiation could be successfully induced in vitro under the experimental conditions employed in this study. Second, TRAP staining and toluidine blue staining results showed that, compared with the control group, the low-, medium-, and high-dose kaempferol treatment groups exhibited a reduced number of OCs, a decreased proportion of TRAP-positive staining area, and a smaller area of bone resorption lacunae. This suggests that kaempferol inhibits OC differentiation and attenuates OC-mediated bone resorptive function in a concentration-dependent manner.

Kaempferol exerts a complex mechanism of action that promotes osteogenesis while inhibiting bone resorption. Previous studies have shown that kaempferol enhances the expression of osterix (Osx) and osteocalcin (OCN) genes in osteoblasts by activating the c-Jun N-terminal kinase (JNK) signaling pathway, thereby promoting osteoblast proliferation, mineralization, and osteogenic differentiation^28,29. Additionally, kaempferol has been reported to alleviate dexamethasone-induced osteoblast cycle arrest and apoptosis; it also mitigates titanium wear particle-induced inflammatory osteolysis and osteoclast activation by regulating the expression of multiple proteins via activation of the JNK/p38/mitogen-activated protein kinase (MAPK) signaling pathway^30,31. This suggests that kaempferol may also serve as a potential alternative therapeutic agent for the prevention and treatment of periprosthetic osteolysis and aseptic loosening.

It is well established that the significant decline in estrogen levels resulting from reduced ovarian function in postmenopausal women poses a serious threat to bone health. Notably, kaempferol has been shown to ameliorate the disorganized bone structure induced by estrogen deficiency in rats³². This indicates that kaempferol could also be used as a nutritional supplement to prevent the development of bone structural disorders and osteoporosis. However, the exact molecular mechanisms underlying kaempferol’s protective effects in estrogen-deficient bone remain to be fully elucidated.

Kaempferol has been shown to inhibit the activation of the JNK/JUN signaling pathway by downregulating Jun expression, reducing inflammation, and blocking osteoclast formation³³. In this study, kaempferol could regulate oxidative stress to reduce the inflammatory response by affecting ROS, MDA, and SOD. Kaempferol can also downregulate the expression of RANK, CSF1R, NFATc1, c-Fos, CTSK, and MMP-9, induce the apoptosis of osteoclast precursor cells, and inhibit their differentiation. It was also demonstrated that kaempferol inhibited osteoclast differentiation by inhibiting the SRC/PI3K/AKT pathways in a concentration-dependent manner, suggesting its potential value in the prevention and treatment of osteoporosis.

Kaempferol can affect the proliferation, differentiation, and apoptosis of osteocyte lines through multiple signaling pathways, including Wnt/β-catenin³⁴, RANKL/RANK⁹, and BMP/Smad³⁵, which play a central role in bone metabolism. The mechanism of action of kaempferol suggests that it may participate in the formation and maintenance of bone tissue through a variety of pathways. It has been reported that kaempferol has bidirectional regulatory effects, especially on the PI3K/Akt, MAPK, and extracellular regulated protein kinase (ERK) pathways³⁶, which reveals its complex mechanism of action in maintaining bone balance. Therefore, the anti-osteoporosis effect of kaempferol may not only depend on the regulation of a single signaling pathway but also be the result of the interaction and influence of multiple signaling pathways. As the dominant pathways, Wnt/β-catenin and RANKL/RANK construct a complex regulatory network together with other signaling pathways and are involved in the regulation of osteogenic and osteoclast activity^37,38. TNF-α/NF-κB is a well-known inflammatory signaling pathway closely related to osteoporosis³⁹, and RANKL and TNF-α activate NF-κB, c-Fos, and NFATc1 through similar pathways^40,41. In our previous study, we performed network pharmacology analysis to extract the intersection targets between kaempferol and osteoporosis, including SRC and TNF factors. In addition, in vitro treatment of RAW 264.7 cells with different concentrations of kaempferol led to a downregulated expression of the SRC/PI3K/AKT signaling molecules. These results suggest that the inhibitory effect of kaempferol on OC differentiation and bone resorption may be achieved by activating the SRC/PI3K/AKT pathway. This may provide theoretical support for the clinical development of new traditional Chinese medicine.

In addition, this study still has several limitations.The mild pro-proliferative effect of 10 µmol/L kaempferol on RAW 264.7 cells requires further validation with a larger sample size. Since the experiment was solely based on the in vitro RAW 264.7 cell model, the regulatory mechanisms of kaempferol at different concentrations in the in vivo bone metabolic microenvironment remain to be verified using an ovariectomized osteoporosis animal model. Second, this study focused on the SRC/PI3K/AKT and TNF-α/NF-κB pathways, but did not further explore the crosstalk mechanism between these pathways and core signaling cascades such as Wnt/β-catenin. Moreover, siRNA silencing and antagonist intervention experiments were lacking to further verify the underlying mechanisms. In addition, the relationship between kaempferol and phosphorylated proteins related to the SRC/PI3K/Akt pathway, as well as its influence on downstream molecules, still requires further verification through subsequent experiments. Third, the in vivo pharmacokinetic characteristics of the compound were not evaluated, which to a certain extent limited the translation of in vitro results into clinical practice. Nevertheless, the application of artificial intelligence technology in the field of network pharmacology presents distinct advantages. Machine learning algorithms can be leveraged to rapidly screen the association between active components of traditional Chinese medicine and disease targets, thereby improving the accuracy and efficiency of target prediction. Deep learning models can optimize the workflows of protein-protein interaction network construction and signaling pathway enrichment analysis, providing a more systematic technical support for elucidating the multi-component and multi-target synergistic mechanism of traditional Chinese medicine.

Conclusion

Kaempferol can inhibit the formation and function of osteoclasts and induce the changes in a series of cytokines. The mechanism may be related to the TNF-α/NF-κB and SRC/PI3K/AKT signaling pathway.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

Q.T.Y. Z.Y.G. Conceptualization, Q.T.Y. T.P.J. Y.P.Z. Formal analysis and investigation, Q.T.Y. Writing - original draft preparation, Z.M.L. Z.Y.G. Writing - review and editing Funding acquisition, Q.T.Y. Resources and Supervision, Q.T.Y. T.P.J. Y.P. Z. Acquisition of data, Q.T.Y. Y.P. Z. Statistical analysis.

Funding

The study was supported by the National Natural Science Foundation (Grant numbers: 82360938).

Data availability

Data will be made available on request.

Declarations

Competing interests

The authors declare no competing interests.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.