Integration of UPLC-MS and Quantitative Proteomics Reveals Key Bioactive Components and Osteoactive Targets of Liuwei Dihuang Wan in Bone Metabolism Modulation

Integration of UPLC-MS and Quantitative Proteomics Reveals Key Bioactive Components and Osteoactive Targets of Liuwei Dihuang Wan in Bone Metabolism Modulation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Integration of UPLC-MS and Quantitative Proteomics Reveals Key Bioactive Components and Osteoactive Targets of Liuwei Dihuang Wan in Bone Metabolism Modulation Zhongliao Zeng, Kaifeng Lin, Yuyi Li, Jianxiong Ma, Jinkun Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6396213/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: Liu Wei Di Huang Wan(LWDHW) is a classic traditional Chinese medicine widely used in preventing and treating osteoporosis associated with kidney yin deficiency, with proven clinical benefits. However, its active ingredients, targets, and synergistic mechanisms remain unclear. This study aims to identify the key factors and mechanisms by which LWDHW treats osteoporosis using proteomics, serum pharmacochemistry, molecular docking, pharmacokinetics, and in vitro validation. Methods: Healthy male rat were randomly assigned to a saline control group or an LWDHW-treated group. After seven days of intervention, serum samples were collected to assess bone metabolism by measuring PINP and β-CTX levels via ELISA. Active compounds in the serum were identified using UPLC-MS. Differentially expressed proteins (DEPs) were analyzed through quantitative proteomics, and key targets were determined using GO and KEGG enrichment analyses, molecular docking. Western blot analysis was performed to verify the expression trends of these key proteins. Results: Compared with the control group, the LWDHW group showed a significant increase in PINP levels (P < 0.01) and a significant decrease in β-CTX levels (P < 0.001), indicating that LWDHW not only suppresses bone resorption but also promotes bone formation. Seven categories of active compounds were detected, including glycosides, triterpenoids and derivatives, phenolics, organic acids, fatty acids and lipids, carbohydrates, and others. Proteomic analysis identified 173 DEPs, with 63 proteins upregulated and 114 downregulated in the treated group. Bioinformatics analysis highlighted PTPN11, SRC, GLUL, and ALOX12 as key targets, and molecular docking revealed that compounds such as linolenic acid, Alisol B, adenosine, and swertiamarin had strong binding affinities (all binding energies below –5) with these targets. Moreover, Western blot results confirmed that high concentrations of LWDHW-containing serum significantly inhibited the AKT, ERK1/2, and IκBα pathways (P < 0.05) while markedly increasing osteocalcin (OCN) expression (P < 0.05). Conclusion: LWDHW promotes osteogenic differentiation and effectively treats osteoporosis through multiple synergistic pathways. Biological sciences/Plant sciences/Plant molecular biology Health sciences/Medical research/Drug development Health sciences/Medical research/Outcomes research Health sciences/Health care/Fracture repair Health sciences/Health care/Disease prevention/Nutritional supplements Health sciences/Health care/Disease prevention/Preventive medicine Health sciences/Health care/Geriatrics Liu Wei Di Huang Wan ELISA Proteomics UPLC-MS Molecular Docking Bone Metabolism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Bone metabolism is a core biological process essential for maintaining bone homeostasis. It is regulated by a dynamic balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, which ensures bone strength, remodeling, and repair 1,2 . Osteoblasts secrete the bone matrix and promote its mineralization, continuously constructing new bone tissue, while osteoclasts degrade bone minerals and collagen fibers in an acidic environment, clearing old or damaged bone. This finely tuned "bidirectional balance" not only affects the structure and function of the skeletal system but is also closely related to calcium-phosphorus metabolism 3 , endocrine regulation, and other systems. However, when this balance is disrupted due to aging, hormonal imbalances chronic inflammation, or genetic factors, bone resorption significantly outweighs bone formation 4,5 . This leads to reduced bone mass, disrupted bone microstructure, and increased bone fragility, ultimately resulting in metabolic bone diseases such as osteoporosis (OP). Osteoporosis, often referred to as a "silent epidemic," is characterized by decreased bone mass and the degeneration of bone tissue microstructure, which increases the risk of brittle fractures 6 . It has become a significant global public health challenge. Statistics show that more than 1.5 million fractures occur annually worldwide due to osteoporosis 7 , with the one-year mortality rate for patients with hip fractures reaching up to 20% 8–10 . OP is often accompanied by pain and functional limitations, significantly affecting daily life and self-care abilities 11 . While traditional Western medicine can partially improve bone density, long-term use often faces challenges such as drug side effects (e.g., bisphosphonates increasing the risk of jaw necrosis 12 ) or diminished efficacy over time (e.g., the limited treatment course of teriparatide 13 ). This highlights the need for new intervention strategies based on multiple targets and holistic regulation, which aligns well with the holistic approach in traditional Chinese medicine (TCM). Liu Wei Di Huang Wan (LWDHW), originating from the "Pediatric Medicine Evidence" by Qian Yi, is composed of six traditional Chinese herbs: Rehmannia glutinosa, Cornus officinalis, Dioscorea opposita, Alisma orientalis, Paeonia lactiflora, and Poria cocos. It is a classic formulation used to nourish yin, strengthen the kidneys, enrich the essence, and fortify the bones 14,15 . Modern pharmacological research has explored LWDHW's role in preventing and treating osteoporosis, but most studies have focused on single-target or individual active ingredients rather than the compound's synergistic effects, resulting in limited findings. Research suggests that LWDHW may exert its effects in osteoporosis prevention and treatment through mechanisms such as inhibiting bone resorption and promoting bone formation 16,17 , but the specific mechanisms and active components remain unclear. To further investigate the foundational components of LWDHW's effect on bone metabolism, we first conducted ELISA tests on serum samples from rat to analyze changes in bone metabolism indicators (β-CTX and PINP) and verify LWDHW’s regulatory effect on bone metabolism. Active compounds in the serum were identified using UPLC-MS to determine its effective ingredients. Quantitative proteomics was used to analyze differentially expressed proteins (DEPs) in the serum, identifying the targets of LWDHW's active components. Additionally, bioinformatics methods, including GO and KEGG pathway enrichment analysis, molecular docking, and molecular dynamics simulations, were employed to analyze and verify the interactions between drug components and targets. Finally, Western blotting was used to validate the expression trends of key proteins, revealing the synergistic mechanism of LWDHW's components and targets and exploring how it alters bone metabolism to prevent and treat osteoporosis. This study provides theoretical foundations and data support for future research in this area. Materials and Methods 2.1 Preparation of Liu Wei Di Huang Wan (LWDHW) Solution The preparation of LWDHW followed previously reported methods. Rehmannia glutinosa, Cornus officinalis, Dioscorea opposita, Alisma plantago-aquatica, Paeonia suffruticosa, and Poria cocos were mixed in a classical ratio of 8:4:4:3:3:3 (total weight: 525g). The mixture was soaked in distilled water for 30 minutes and decocted twice for 1 hour each. The filtrates were collected, combined, and concentrated to 1 g/mL. The final solution was stored at −20°C until use 18 . 2.2 Animal Maintenance Eight-week-old male Sprague-Dawley (SD) rat were used. All animals were housed and maintained according to the Guidelines for the Care and Use of Laboratory Animals of Zhejiang Chinese Medical University (Animal license number: SYXK (Zhe) 2021-0012), with approval from the Institutional Animal Care and Use Committee (IACUC) (Approval No. 20220913-23). Before the experiment, twelve rat were acclimated for 2 weeks in a temperature-controlled room (22 ± 2°C) with 55 ± 10% relative humidity and free access to standard chow and water. 2.3 Serum Preparation Rat were randomly divided into the experimental and control groups (n = 6 per group). The experimental group was administered the LWDHW extract prepared in section 2.1 via oral gavage at a dose of 0.7 mL/100 g body weight daily, while the control group received normal saline for 7 consecutive days. Two hours after the final gavage, the rats were anesthetized via intraperitoneal injection of Zoletil®50 (50 mg/kg) and acetaminophen (100 mg/kg), followed by blood collection through cardiac puncture. Blood samples were allowed to stand for 30 minutes, then centrifuged at 3,000 rpm for 15 minutes. The supernatant (3 mL) was collected and filtered through a 0.22 μm microporous membrane to obtain serum, which was stored at −80°C for further analysis. 2.4 Serum ELISA After centrifugation, serum samples were thawed at 4°C, diluted, and analyzed for β-CTX and PINP levels using commercial ELISA kits (CTX-1: CUSABIO, CSB-E12776r; PINP: CUSABIO, CSB-E12774r), following the manufacturer’s protocols. Optical density (OD) was measured at 450 nm, and standard curves were generated to calculate sample concentrations. β-CTX was used as a marker for osteoclast activity and PINP as a marker for osteoblast function 19 . Their combined evaluation provides a reliable indication of bone turnover and osteoporosis. 2.5 Proteomic Analysis Tandem Mass Tag (TMT) labeling was performed for proteomic quantification. After trypsin digestion, peptide mixtures were fractionated by HPLC and analyzed using LC-MS/MS. Mass spectrometry data were annotated using UniProt-GOA (GO function), Pfam (protein domains), KEGG (pathways), BLAST (sequence homology), eggNOG (homolog classification), and PSORTb/WoLF PSORT (subcellular localization). Differentially expressed proteins (DEPs) between groups were identified based on fold-change >1.3 or <1/1.3 with a T-test p < 0.05. Proteins were classified as upregulated or downregulated accordingly. GO and KEGG analyses were performed to explore potential biological functions and pathways. 2.6 Serum Metabolomics via Mass Spectrometry LWDHW-medicated serum was mixed with 80% methanol (v/v, 1:3), sonicated (40 kHz, 30 min), centrifuged (12,000 × g, 10 min), and filtered through a 0.22 μm organic membrane for HPLC-MS analysis. A ZenoTOF™ 7600 system (SCIEX, USA) was used. Mobile phases were 0.1% formic acid in water (A) and acetonitrile (B) with a gradient: 0–3 min 5% B; 3–20 min 5%–95% B; 20–25 min 95% B; re-equilibration for 3 min. Column temperature was 35°C, flow rate 0.3 mL/min, injection volume 5 μL. ESI was used in both positive and negative ion modes.MS parameters: spray voltage 3.8 kV, capillary temperature 320°C, auxiliary gas 45 Arb, sheath gas 50 Arb, Full MS resolution 70,000, dd-MS² resolution 17,500, scan range m/z 100–1500, HCD collision energy set to 25/35/45 eV. Compound identification was supported by literature retrieval from CNKI, PubMed, Web of Science, HERB, and TCMSP. Identified compounds were verified using ChemSpider, ChemicalBook, and PubChem. 2.7 Network Pharmacology Based on Metabolomics Identified compounds were compared with herbal ingredient databases (HERB, TCMSP). SMILES formats were retrieved from PubChem and targets predicted using SwissTargetPrediction. Osteoporosis-related targets were identified using GeneCards, DrugBank, and OMIM with median filtering. After de-duplication, final OP-related targets were obtained. 2.8 Integration of DEPs and Network Targets DEPs from Section 2.5 were converted to human orthologs using UniProt. Venn analysis using Venny 2.1.0 identified overlapping targets between serum compound targets, disease targets, and DEPs. Overlapping targets were considered potential therapeutic targets for OP. 2.9 GO and KEGG Pathway Analysis Common targets were submitted to DAVID for GO term and KEGG pathway enrichment analysis. 2.10 Molecular Docking Molecular docking was performed using AutoDock Vina (v1.5.6). The 3D structures of PTPN11 (PDB: 4h1o), SRC (PDB: 2SRC), GLUL (PDB: 2OJW), and ALOX12 (PDB: 3D3L) were downloaded from the PDB. Ligands including swertiamarin (PubChem CID: 442435), adenosine (CID: 60961), Alisol B (CID: 15558620), and linolenic acid (CID: 5280934) were obtained from PubChem. Ligand structures were optimized using PyMol (hydrogenation, protonation, energy minimization), and docking simulations were conducted with AutoDock Vina. Binding affinity and interaction modes were visualized with PyMol. 2.11 Cell Culture MC3T3-E1 mouse preosteoblasts (ATCC) were cultured in α-MEM supplemented with 10% fetal bovine serum and antibiotics (100 mg/mL streptomycin, 100 U/mL penicillin, Gibco) at 37°C in a 5% CO₂ incubator 20 . Cells at passage 3 were used4.For induction, cells were seeded at 2 × 10⁵/well in 6-well plates and cultured until 70% confluency. Osteogenic medium (2 mL/well) containing 10 nM dexamethasone, 10 mM β-glycerophosphate, and 50 μg/mL ascorbic acid was added. Medium was changed every 2 days 21 . Experimental groups:Control: induced with normal mouse serum + FBS、Treatment: 2%, 8%, and 14% LWDHW-medicated serum added, cultured for 14 days. 2.12 Real-Time Cell Analysis (RTCA) for Proliferation The xCELLigence system (Agilent) was used to monitor real-time proliferation. First, 50 μL of medium was added to each well of an E-plate 16. After baseline measurement, 100 μL of cell suspension was added. Plates were incubated at room temperature for 20 minutes before insertion into the RTCA device 22 . Impedance was continuously monitored. Each assay included replicates for reliability. 2.13 Western Blot After 14 days of induction, cells were washed with PBS and lysed in 1× lysis buffer containing 1 mM PMSF. Samples were boiled at 95°C for 10 minutes and separated by SDS-PAGE (12%). Proteins were transferred to PVDF membranes and blocked with QuickBlock buffer (PS108, Epizyme Biotech) for 20 minutes at room temperature. Membranes were incubated overnight at 4°C with primary antibodies, then washed and incubated with secondary antibodies for 1 hour. Bands were detected using the Tanon 5500 system and quantified using ImageJ. Each experiment was repeated at least three times. 2.14 Statistical Analysis All experiments were conducted at least in triplicate. Data were analyzed using GraphPad Prism 8. ELISA data were assessed with the Mann–Whitney test. Unpaired t-tests were used for proteomics comparisons, and one-way or two-way ANOVA was used for multiple group comparisons. *p < 0.05, **p < 0.01, ***p < 0.001 indicated statistical significance, while 'ns' denoted non-significance. Results 3.1LWDHW Significantly Modulates Bone Metabolism Markers Serum levels of bone metabolism markers were measured in both experimental and control rat using ELISA. The results demonstrated that the levels of PINP and β-CTX were significantly altered in the LWDHW-treated group compared to the control group (P < 0.01, P < 0.001, respectively). Specifically, the PINP level was significantly increased, while the β-CTX level was markedly decreased in the experimental group. These findings indicate that LWDHW significantly regulates bone metabolic processes by promoting bone formation and inhibiting bone resorption ( Figure 1)(Table 1) ( Supporting Information S1). Table 1: The table displays the concentration data of two biomarkers, PINP and β - CTX, for the Case and Control groups Group（n=6） PINP（pg/mL） β-CTX（pg/mL） Case 525.1(98.8，748.2) 11.68（9.45 ，15.02） Control 457.2 (417.1，520.9) 25.84（20.31，30.55） 3.2 LWDHW on the Mechanism of Action in Rat and Proteomics Analysis A total of 173 Differentially Expressed Proteins (DEPs, as shown in the figure.2A) were identified when comparing the experimental group with the control group. To further demonstrate the significance of the differences, a volcano plot was generated by performing a -Log10 transformation of the p-values from the significance tests (as shown in the figure.2B). Compared to the control group, a total of 63 upregulated proteins and 114 downregulated proteins were detected in the experimental group. For these differential proteins, we conducted further functional annotations, including COG, GO (Gene Ontology), and KEGG pathway analysis. The results revealed that these differential proteins are involved in several biological processes, including energy production and conversion, signal transduction mechanisms, intracellular transport, secretion and vesicle trafficking, as well as cytoskeletal construction (as shown in the figure.2C-G). To better illustrate the differences in protein abundance between the two groups, we performed hierarchical clustering analysis of the differentially expressed proteins (DEPs). This analysis helps reveal the functional correlations of the DEPs. KEGG pathway analysis results showed that the DEPs are involved in several important signaling pathways, including the Rap1 signaling pathway, PI3K-Akt signaling pathway, Ras signaling pathway, MAPK signaling pathway, nitrogen metabolism, ammonia metabolism, and reactive oxygen species (ROS) metabolism(as shown in the figure.3A-F). Downregulated proteins enriched in these pathways include Hspa8, Rap1b, Src, Tln1, Ywhab, and Ptpn11（Please refer to Attachment 2 for details）. These data suggest that LWDHW may exert its protective and therapeutic effects on osteoporosis by promoting the differentiation and proliferation of osteoblasts, or by altering bone metabolism through antioxidant stress mechanisms. 3.3 Analysis of Bioactive Components of LWDHW in Serum UPLC-MS analysis of LWDHW-medicated serum identified a total of seven major categories of compounds（Figure 4）. These primarily included glycosides, triterpenoids and their derivatives, and phenolic compounds. Specifically, 30 glycosides, 19 triterpenoids and their derivatives, 14 phenolic compounds and derivatives, 12 organic acids, 7 fatty acids and lipids, 9 sugars and sugar derivatives, and 14 compounds from other categories were detected. Detailed classification and distribution are shown in Figure 5A. 3.4.1 Analysis of Serum-Derived Compounds and Their Targets of LWDHW A total of 105 compounds were identified in serum following the administration of LWDHW（Table 2）. After filtering disease-related targets for osteoporosis using median-based criteria, 2,300 relevant targets were retrieved. Using the Venny 2.1.0 tool (https://bioinfogp.cnb.csic.es/tools/venny/index.html), four overlapping targets were identified between the LWDHW-related compounds, osteoporosis-associated targets, and differentially expressed proteins (DEPs): PTPN11, SRC, GLUL, and ALOX12 (Figure 5B). These targets are likely to play critical roles in mediating the therapeutic effects of LWDHW on bone metabolism. 3.4.2 GO and KEGG Pathway Analysis of Core Targets To further explore the biological roles of these core targets, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID database (https://davidbioinformatics.nih.gov/). This functional enrichment analysis provided insights into the biological processes, cellular components, and molecular functions associated with the overlapping targets, as well as the signaling pathways they may be involved in. To visualize the results, GO bar charts and KEGG bubble plots were generated using the Bioinformatics platform (https://www.bioinformatics.com.cn/plot_basic_line_stack_plot_060). The analyses revealed that the core targets are involved in biological processes such as immune response, inflammatory regulation, and cytokine-mediated signaling. KEGG enrichment results showed significant involvement in pathways such as the C-type lectin receptor signaling pathway and the Toll-like receptor signaling pathway, both of which are closely associated with inflammation modulation. These findings suggest that LWDHW may alter bone metabolism by mitigating inflammatory responses or enhancing immune function (Figure 6A–B). 3.4.3 Molecular Docking Analysis To further evaluate the binding affinity between bioactive serum compounds and potential pharmacological targets, molecular docking was performed based on the intersection results from the Venn diagram. Four key targets—PTPN11, SRC, GLUL, and ALOX12—were selected due to their known involvement in bone metabolism and their potential role in mediating the effects of LWDHW Using reverse target prediction through network pharmacology, we docked these targets with candidate compounds. Binding energy was used as an indicator of interaction strength, with lower values representing stronger and more stable binding. As shown in the results, all selected compound–target pairs exhibited binding energies below −5 kcal/mol, suggesting favorable spontaneous interactions and high binding stability. (as shown in Table 3)( Figure 7.A-D. Visualization of Molecular Docking). Table 3. Binding affinities between key ligands and their corresponding protein targets (receptors). Target gene PDB ID Compound Autodockenergy(kcal/mol) PTPN11 4h1o 442435 -7.1 SRC 2src 60961 -7.3 GLUL 2ojw 15558620 -7.09 ALOX12 3d3l 5280934 -6.5 3.5 Real-Time Cell Analysis (RTCA) RTCA results demonstrated that treatment with LWDHW-medicated serum significantly promoted the proliferation of MC3T3-E1 cells within 36 hours. Although no significant differences were observed among the various concentrations, all treatment groups showed a clear increase in cell proliferation compared to the control group. These findings indicate that LWDHW serum effectively enhances the growth and proliferation of MC3T3-E1 cells without exhibiting cytotoxic effects across the tested concentrations.( Figure 8) ( Supporting Information S2). 3.6Western Blot Analysis of Osteogenic Pathway Activation To investigate the underlying mechanisms by which LWDHW promotes osteogenic differentiation, we examined the activation of signaling pathways related to the core target genes using Western blot analysis. MC3T3-E1 cells were induced for osteogenic differentiation and treated with LWDHW-medicated serum. Previous studies have highlighted the roles of SHPTP2, AKT, and IκBα in osteogenic differentiation 23–25 . As shown in the results( Figure 9, Supporting Information S3), several phosphorylated proteins showed a decreasing trend after treatment with LWDHW serum. Specifically, treatment with 14% LWDHW-medicated serum significantly reduced the ratios of phosphorylated to total protein for P-IκBα/IκBα (P < 0.05), P-AKT/AKT (P < 0.05), P-ERK1/2/ERK1/2 (P < 0.005), and P-P65/P65 (P < 0.05), compared to the control group. In contrast, the expression of Osteocalcin (OCN), a key marker of osteogenic differentiation, was significantly increased at both 8% and 14% serum concentrations (P < 0.05), indicating that LWDHW promotes osteogenic differentiation in a dose-dependent manner. Interestingly, although P-SHPTP2/SHPTP2 showed a downward trend, the change did not reach statistical significance. Similarly, no significant change was observed in the P-SRC/SRC ratio. However, the downward trend of P-SHPTP2 was consistent with the reduction of PTPN11 observed in the proteomic analysis. In addition, downstream molecules of ALOX12, including IκBα and P65, also exhibited suppressed phosphorylation, further supporting its involvement in LWDHW-mediated signaling. These findings suggest that LWDHW promotes osteogenic differentiation and exhibits significant regulatory effects at both medium (8%) and high (14%) concentrations. At higher concentrations, LWDHW notably suppressed the ERK1/2, AKT, and IκBα signaling pathways, which may contribute to its pro-differentiation effects.Previous studies have shown that AKT and ERK1/2 are associated with cell proliferation, and their activation typically promotes growth 26 . The observed suppression of these pathways by LWDHW may shift the cells from a proliferative state toward differentiation, thereby enhancing osteogenic activity. This supports the hypothesis that LWDHW facilitates osteogenic differentiation through coordinated modulation of multiple signaling pathways. Among the four intersection genes identified, we validated three (PTPN11, SRC, and ALOX12). The GLUL gene was not included in this validation due to the widespread presence of glutamine in standard culture media, making it difficult to determine whether its effects were directly attributable to components of LWDHW. Discussion LWDHW is a classical traditional Chinese herbal formula with clinical evidence supporting its efficacy in treating osteoporosis and regulating bone metabolism. However, the specific bioactive compounds and underlying mechanisms responsible for these effects remain poorly defined. Due to the multi-component and multi-target nature of traditional Chinese medicine, clinical outcomes alone often fall short in explaining the molecular basis of its therapeutic effects.In this study, ELISA analysis in rat demonstrated that LWDHW significantly altered serum biomarkers of bone metabolism, consistent with its reported clinical benefits. Building on this, quantitative proteomic analysis revealed that LWDHW may influence osteoblast differentiation and bone formation through several key pathways, including Rap1, PI3K-Akt, Ras, and MAPK signaling, as well as nitrogen metabolism, ammonia metabolism, and oxidative stress-related processes.UPLC-MS analysis identified 105 chemical constituents in the serum following administration of LWDHW. By integrating these data with network pharmacology, as well as GO and KEGG enrichment analysis of differentially expressed proteins, we identified four core therapeutic targets—PTPN11, SRC, GLUL, and ALOX12. Molecular docking studies further confirmed strong binding affinities between these proteins and LWDHW-derived compounds. Western blot analysis showed that LWDHW modulates downstream signaling pathways of PTPN11, SRC, and ALOX12, inhibiting the activation of ERK1/2, AKT, and IκBα, while promoting the expression of the osteogenic marker OCN. These findings suggest a coordinated mechanism through which LWDHW enhances osteoblast differentiation and exerts protective effects against osteoporosis. Serum analysis revealed that, compared to controls, rat treated with LWDHW exhibited significantly elevated levels of P1NP and reduced levels of β-CTX markers indicative of increased bone formation and decreased bone resorption, respectively. This suggests that LWDHW exerts a dual regulatory effect on bone metabolism by promoting osteoblast activity while inhibiting osteoclast function. Proteomic results showed enrichment of differentially expressed proteins in several signaling pathways, including Rap1, PI3K-Akt, Ras, MAPK, and reactive oxygen species (ROS)-related signaling. Notably, Rap1 is a small GTPase involved in cell adhesion, junction formation, and polarity, all of which are essential in bone cell function. Prior studies have demonstrated that activation of the Rap1 pathway promotes osteogenesis and inhibits osteoclastogenesis in vivo 27 . Additionally, Talin1 and Rap1 are known to regulate osteoclast adhesion and bone resorption. Disruption of this axis impairs integrin signaling, leading to reduced bone resorption and, in some cases, a high bone mass phenotyp 28 .In our study, Talin1 (Tln1) was significantly downregulated following LWDHW treatment, indicating that the formula may suppress osteoclast differentiation and function via the Talin1–Rap1 signaling axis, thereby contributing to the observed reduction in β-CTX and increase in P1NP.Another key finding was the downregulation of Hspa8, which encodes the heat shock protein HSC70. Reduced HSC70 levels have been shown to prevent lysosomal degradation of PRL2, a tyrosine phosphatase highly expressed in bone marrow monocytes. Loss of PRL2 leads to excessive activation of Rac1 and hyperphosphorylation of the MAPK and NF-κB pathways, accelerating osteoclast differentiation and bone resorption 29 . In this context, decreased HSC70 may stabilize PRL2, ultimately restraining osteoclast activity.Together, these findings suggest that LWDHW modulates bone metabolism through complementary mechanisms: promoting osteoblast differentiation while simultaneously inhibiting osteoclastogenesis. The involvement of Talin1-Rap1 signaling and HSC70-mediated regulation of PRL2 offers new mechanistic insights and potential therapeutic targets for the treatment of osteoporosis. Alisol-B, a bioactive compound isolated from Alisma orientale, has been shown to inhibit osteoclastogenesis both in vitro and in vivo. Firstly, Alisol-B suppresses RANKL-induced phosphorylation of JNK, a key signaling molecule in osteoclast differentiation. In addition, it inhibits the expression of NFATc1 and c-Fos, both critical transcription factors downstream of RANKL, thereby blocking the differentiation of osteoclast precursors. Finally, Alisol-B disrupts the actin ring structure of mature osteoclasts and suppresses the formation of bone resorption pits, indicating its direct inhibitory effect on osteoclastic bone resorption 30 .Another study reported that linolenic acid intake is associated with reduced fracture risk. Dietary α-linolenic acid (ALA) improves osteoporosis progression by targeting multiple inflammatory cascades. High ALA intake (>1.39 g/day) was significantly associated with a decreased risk of hip fractures in older adults (HR = 0.46) 31 . Additional evidence suggests that ALA may exert indirect antioxidant effects by replacing arachidonic acid (AA) in phospholipids of the cell membrane, thereby reducing the accumulation of lipid peroxidation products such as malondialdehyde (MDA). This preservation of mitochondrial function contributes to decreased bone resorption. Adenosine, derived from Rehmannia glutinosa and Poria cocos, is an endogenous nucleotide known to play a crucial role in bone homeostasis 32 . High concentrations of adenosine can activate A2 receptors to promote bone remodeling. In mouse models, adenosine significantly improved bone structure and strength, accompanied by increased expression of ALP, osteocalcin, and osteoprotegerin 32,33 . Collectively, current evidence suggests that Alisol-B, linolenic acid, and adenosine can suppress osteoclast development, control inflammation and oxidative stress, and may share overlapping mechanisms with LWDHW. These findings warrant further experimental validation. Molecular docking was employed to validate the findings of the network pharmacology analysis. The docking results demonstrated that the active compounds in LWDHW exhibited favorable binding affinities with key targets, indicating that LWDHW may regulate bone metabolism through pharmacological targeting of proteins such as PTPN11, SRC, GLUL, and ALOX12. These interactions may contribute to the dual regulatory effects of promoting osteogenesis and inhibiting bone resorption. Western blot analysis further revealed that LWDHW suppresses the activity of the SHPTP2 pathway during osteogenic differentiation. SHPTP2, encoded by PTPN11, is a non-receptor type protein tyrosine phosphatase that plays a central role in the RAS-MAPK and PI3K-AKT-mTOR signaling pathways by modulating the phosphorylation status of adaptor proteins Gab1/2. Upon phosphorylation, Gab1/2 recruits the Grb2-SOS complex, while SHPTP2 dephosphorylates Gab1/2, releasing SOS (Son of Sevenless), a guanine nucleotide exchange factor that catalyzes the conversion of GDP to GTP on RAS (RAS-GTP), thereby activating the RAF kinase family. Phosphorylated RAF activates MEK1/2, which in turn phosphorylates ERK1/2. Activated ERK1/2 subsequently phosphorylates ribosomal S6 kinase (RSK1), leading to destabilization of the TSC1-TSC2 complex and regulation of downstream mTOR activity 34–36 .Studies have shown that inhibition of p-SHPTP2 activity results in sustained phosphorylation of critical tyrosine residues on Gab1/2 (Y627/Y659), thereby attenuating the RAS-MAPK/mTOR signaling cascade 37 . Another study demonstrated that suppression of mTOR signaling alleviates its inhibitory effect on osteogenic transcription factors RUNX2 and Osterix, markedly enhancing osteocalcin (OCN) expression and promoting mineralized nodule formation in vitro 38 .Interestingly, our Western blot results suggest that LWDHW may act via a similar mechanism. The current evidence indicates that LWDHW reduces SHPTP2 activity and downstream ERK1/2 phosphorylation, thereby promoting osteogenic differentiation. Additional data suggest that LWDHW at high concentrations may inhibit inflammatory interference by suppressing the NF-κB pathway and cooperatively inhibit AKT and ERK, facilitating cell cycle exit and upregulating OCN expression to further enhance osteogenesis 39,40 . From the perspective of drug-target signaling pathways, LWDHW and its active components regulate bone metabolism through a multi-pathway, multi-target synergistic mechanism. LWDHW suppresses the activity of SHPTP2 encoded by PTPN11, thereby promoting OCN expression and enhancing osteoblast differentiation. At the same time, it downregulates the Talin1–Rap1 axis to inhibit osteoclast adhesion and bone resorption. Alisol-B targets key nodes in the RANKL signaling pathway such as JNK, c-Fos, and NFATc1, thereby blocking osteoclast differentiation and function. Linolenic acid indirectly modulates the MAPK/NF-κB signaling pathways by inhibiting reactive oxygen species (ROS) and inflammatory cascades, thereby alleviating bone resorption. Adenosine, by activating the A2A receptor, promotes osteogenesis via the PI3K-Akt and BMP-related pathways. These four compounds converge on several key signaling pathways—including MAPK, PI3K-Akt, NF-κB, and mTOR—and exhibit overlapping targets, collectively contributing to the homeostatic regulation of bone metabolism by enhancing osteogenesis and suppressing osteoclastogenesis. However, there are several limitations in this study that require further investigation. Firstly, the rat used in this study were not osteoporotic model rat, which may affect the comprehensiveness of the therapeutic effect of LWDHW. The group of active compounds may not be fully represented in this model. Although clinical and animal studies have already demonstrated the therapeutic effect of LWDHW on osteoporosis, the full spectrum of active compounds still needs to be confirmed. Secondly, in vivo experiments in animals are lacking to verify the results. Nevertheless, this study also has several strengths. First, male rat were selected as the research subjects, which reduces the physiological effects of hormonal cycle variations. Second, the genes of rat are highly similar to those of humans, and the use of mouse-derived differential proteins mapped to human proteins ensures safety and reliability. Finally, further research is needed to better elucidate the mechanisms of these active compounds. Conclusion LWDHW significantly impacts bone metabolism, and its active components may synergistically promote osteogenic differentiation through Linolenic acid, Alisol-B, Adenosine, and Swertiamarin. These components regulate key targets such as PTPN11, SRC, GLUL, and ALOX12, through pathways involving SHPTP2, AKT, ERK1/2, and IκBα, thereby influencing bone metabolism. However, this study still has some limitations and requires further research to confirm the exact mechanisms involved. Declarations Data availability The datasets generated during the current study are available from the corresponding author upon reasonable request. Acknowledgements We would like to express our sincere gratitude to the laboratory of the Second Clinical College of Zhejiang Chinese Medical University for their invaluable support in conducting the experiments for this study. Their assistance and resources were crucial in the successful completion of this research. Funding This study was funded by the National Natural Science Foundation of China (Project No. 81803902). Author Contributions Zhongliao Zeng and Kaifeng Lin proposed hypotheses and designed experiments.Zhongliao Zeng, Yuyi Li, Jianxiong Ma, and Jinkun Li conducted animal and in vitro experiments. Bochen Liang, Zhongliao Zeng, Yifeng Yuan, and Min Li analyzed the data and wrote the initial draft. All authors have reviewed and agreed to the manuscript's final version. Ethics declarations. Ethical Approval The animal study was approved by the Institutional Animal Care and Use Committee of Zhejiang Chinese Medical University (Approval No. 20220913-23). Consent for publication All authors unanimously agree to publish. Competing interests The authors declare that they have no conflict of interest. Animal Declaration This study is reported in accordance with the ARRIVE guidelines (Version 2.0) (https://arriveguidelines.org). This experiment has been approved by the Institutional Animal Management and Ethics Committee (IACUC) of Zhejiang University of Traditional Chinese Medicine (Approval No. 20220913-23) References Fonseca, H., Moreira-Gonçalves, D., Coriolano, H.-J. A. & Duarte, J. A. Bone quality: the determinants of bone strength and fragility. Sports Med 44 , 37–53 (2014). Agas, D., Sabbieti, M. G. & Marchetti, L. Endocrine disruptors and bone metabolism. Arch Toxicol 87 , 735–751 (2013). Ciosek, Ż., Kot, K., Kosik-Bogacka, D., Łanocha-Arendarczyk, N. & Rotter, I. The Effects of Calcium, Magnesium, Phosphorus, Fluoride, and Lead on Bone Tissue. Biomolecules 11 , 506 (2021). Levin, V. A., Jiang, X. & Kagan, R. Estrogen therapy for osteoporosis in the modern era. Osteoporos Int 29 , 1049–1055 (2018). Kasher, M. et al. Insights into the pleiotropic relationships between chronic back pain and inflammation-related musculoskeletal conditions: rheumatoid arthritis and osteoporotic abnormalities. Pain 164 , e122–e134 (2023). Xu, W. et al. Ferrostatin-1 inhibits osteoclast differentiation and prevents osteoporosis by suppressing lipid peroxidation. J Orthop Surg Res 20 , 117 (2025). Clynes, M. A. et al. The epidemiology of osteoporosis. Br Med Bull 133 , 105–117 (2020). Wells, G. A. et al. Risedronate for the primary and secondary prevention of osteoporotic fractures in postmenopausal women. Cochrane Database Syst Rev 5 , CD004523 (2022). Gates, M. et al. Screening for the primary prevention of fragility fractures among adults aged 40 years and older in primary care: systematic reviews of the effects and acceptability of screening and treatment, and the accuracy of risk prediction tools. Syst Rev 12 , 51 (2023). Sing, C.-W. et al. Global Epidemiology of Hip Fractures: Secular Trends in Incidence Rate, Post-Fracture Treatment, and All-Cause Mortality. J Bone Miner Res 38 , 1064–1075 (2023). Barker, K. L. et al. Exercise or manual physiotherapy compared with a single session of physiotherapy for osteoporotic vertebral fracture: three-arm PROVE RCT. Health Technol Assess 23 , 1–318 (2019). Kuroshima, S., Al-Omari, F. A., Sasaki, M. & Sawase, T. Medication-related osteonecrosis of the jaw: A literature review and update. Genesis 60 , e23500 (2022). Lindsay, R., Krege, J. H., Marin, F., Jin, L. & Stepan, J. J. Teriparatide for osteoporosis: importance of the full course. Osteoporos Int 27 , 2395–2410 (2016). Zhao, J. et al. Liuwei Dihuang Pills Enhance Osteogenic Differentiation in MC3T3-E1 Cells through the Activation of the Wnt/β-Catenin Signaling Pathway. Pharmaceuticals (Basel) 17 , 99 (2024). Perry, B., Zhang, J., Saleh, T. & Wang, Y. Liuwei Dihuang, a traditional Chinese herbal formula, suppresses chronic inflammation and oxidative stress in obese rats. J Integr Med 12 , 447–454 (2014). Liu, M. M. et al. Therapeutic potential of Liuwei Dihuang pill against KDM7A and Wnt/β-catenin signaling pathway in diabetic nephropathy-related osteoporosis. Biosci Rep 40 , BSR20201778 (2020). Liang, B. et al. Liuwei Dihuang pills attenuate ovariectomy-induced bone loss by alleviating bone marrow mesenchymal stem cell (BMSC) senescence via the Yes-associated protein (YAP)-autophagy axis. Pharm Biol 62 , 42–52 (2024). Xia, B. et al. The effects of Liuwei Dihuang on canonical Wnt/β-catenin signaling pathway in osteoporosis. Journal of Ethnopharmacology 153 , 133–141 (2014). Eastell, R. & Szulc, P. Use of bone turnover markers in postmenopausal osteoporosis. Lancet Diabetes Endocrinol 5 , 908–923 (2017). S, C. et al. Luteolin rescues postmenopausal osteoporosis elicited by OVX through alleviating osteoblast pyroptosis via activating PI3K-AKT signaling. Phytomedicine : international journal of phytotherapy and phytopharmacology 128 , (2024). J, W. et al. Curculigo orchioides polysaccharide COP70-1 stimulates osteogenic differentiation of MC3T3-E1 cells by activating the BMP and Wnt signaling pathways. International journal of biological macromolecules 248 , (2023). D, K. et al. Application of xCELLigence RTCA Biosensor Technology for Revealing the Profile and Window of Drug Responsiveness in Real Time. Biosensors 5 , (2015). Yang, J. et al. Siwu decoction exerts a phytoestrogenic osteoprotective effect on postmenopausal osteoporosis via the estrogen receptor/phosphatidylinositol 3-kinase/serine/threonine protein kinase pathway. J Ethnopharmacol 332 , 118366 (2024). Kaneshiro, S. et al. IL-6 negatively regulates osteoblast differentiation through the SHP2/MEK2 and SHP2/Akt2 pathways in vitro. J Bone Miner Metab 32 , 378–392 (2014). Ja, E., J, L. & Lc, C. The evolution of phosphatidylinositol 3-kinases as regulators of growth and metabolism. Nature reviews. Genetics 7 , (2006). Wei, L. et al. Integrin β3 promotes cardiomyocyte proliferation and attenuates hypoxia-induced apoptosis via regulating the PTEN/Akt/mTOR and ERK1/2 pathways. Int J Biol Sci 16 , 644–654 (2020). L, H. et al. MiR-1224-5p modulates osteogenesis by coordinating osteoblast/osteoclast differentiation via the Rap1 signaling target ADCY2. Experimental & molecular medicine 54 , (2022). Zou, W. et al. Talin1 and Rap1 are critical for osteoclast function. Mol Cell Biol 33 , 830–844 (2013). Li, Q. et al. HSC70 mediated autophagic degradation of oxidized PRL2 is responsible for osteoclastogenesis and inflammatory bone destruction. Cell Death Differ 30 , 647–659 (2023). Lee, J.-W. et al. Alisol-B, a novel phyto-steroid, suppresses the RANKL-induced osteoclast formation and prevents bone loss in rat. Biochem Pharmacol 80 , 352–361 (2010). Ek, F. et al. Dietary intakes of arachidonic acid and alpha-linolenic acid are associated with reduced risk of hip fracture in older adults. The Journal of nutrition 141 , (2011). He, W. & Cronstein, B. The roles of adenosine and adenosine receptors in bone remodeling. Front Biosci (Elite Ed) 3 , 888–895 (2011). Pizzino, G. et al. Adenosine Receptor Stimulation Improves Glucocorticoid-Induced Osteoporosis in a Rat Model. Front Pharmacol 8 , 558 (2017). Ae, K. & Ra, W. Ras oncogenes: split personalities. Nature reviews. Molecular cell biology 9 , (2008). M, M. & M, B. RAS oncogenes: the first 30 years. Nature reviews. Cancer 3 , (2003). Im, A., K, H., D, B.-S. & Mr, P. Regulating the regulator: post-translational modification of RAS. Nature reviews. Molecular cell biology 13 , (2011). Qiu, W.-Q. et al. Polygala saponins inhibit NLRP3 inflammasome-mediated neuroinflammation via SHP-2-Mediated mitophagy. Free Radic Biol Med 179 , 76–94 (2022). Lv, C. et al. Glucosamine promotes osteoblast proliferation by modulating autophagy via the mammalian target of rapamycin pathway. Biomed Pharmacother 99 , 271–277 (2018). Han, J. & Wang, W. Effects of tanshinol on markers of bone turnover in ovariectomized rats and osteoblast cultures. PLoS One 12 , e0181175 (2017). Miao, Y. et al. Caffeine regulates both osteoclast and osteoblast differentiation via the AKT, NF-κB, and MAPK pathways. Front Pharmacol 15 , 1405173 (2024). Table Table 2 is available in the Supplementary Files section Additional Declarations No competing interests reported. Supplementary Files differentialprotein.xlsx Stripimage.pptx SupportingInformationS1elisa.xlsx SupportingInformationS2RTCA.xlsx SupportingInformationS3WBDevelopedimage.zip SupportingInformationS3Originalfilmcuttingimage.zip SupportingInformationS3Filmcuttinginstructiondiagram.pptx Table2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6396213","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":464161088,"identity":"fb7ed9bd-ba00-47e9-8e57-e6a5d714033b","order_by":0,"name":"Zhongliao Zeng","email":"","orcid":"","institution":"Second Clinical Medical College, Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhongliao","middleName":"","lastName":"Zeng","suffix":""},{"id":464161089,"identity":"afd6a725-896a-43fa-bea6-d881efb622a6","order_by":1,"name":"Kaifeng Lin","email":"","orcid":"","institution":"Second Clinical Medical College, Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kaifeng","middleName":"","lastName":"Lin","suffix":""},{"id":464161090,"identity":"8d8476a4-86ea-47ff-926f-76f6b359731f","order_by":2,"name":"Yuyi Li","email":"","orcid":"","institution":"Second Clinical Medical College, Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuyi","middleName":"","lastName":"Li","suffix":""},{"id":464161092,"identity":"f54f8359-371c-4bb7-a0d3-fead076146c5","order_by":3,"name":"Jianxiong Ma","email":"","orcid":"","institution":"Department of Nephrology, the First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine)","correspondingAuthor":false,"prefix":"","firstName":"Jianxiong","middleName":"","lastName":"Ma","suffix":""},{"id":464161094,"identity":"d025d9ef-6133-4316-a0d4-43d678ad42a3","order_by":4,"name":"Jinkun Li","email":"","orcid":"","institution":"Second Clinical Medical College, Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinkun","middleName":"","lastName":"Li","suffix":""},{"id":464161096,"identity":"917c9363-d531-49e1-8221-17e98424f85d","order_by":5,"name":"Yifeng Yuan","email":"","orcid":"","institution":"The Second Affiliated Hospital (Xinhua Hospital), Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yifeng","middleName":"","lastName":"Yuan","suffix":""},{"id":464161100,"identity":"f2378f38-6bc3-4438-958a-4320a1f945cb","order_by":6,"name":"Min Li","email":"","orcid":"","institution":"The Second Affiliated Hospital (Xinhua Hospital), Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Li","suffix":""},{"id":464161103,"identity":"8ed3826d-62eb-4100-9106-42ca517259cb","order_by":7,"name":"Bochen Liang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxklEQVRIiWNgGAWjYBACAwYGNhAtB+UzE6/FmHQtiQ1EazFnb3724OOO2vT57afTJBgqrBMb2M8ewKvFsueYueHMM8dzG3tyt0kwnElPbODJS8DvsBs5bNK8bcdymyV4t0kwth1ObJDgMSCs5W/bsXQ2sJZ/xGphbKtJ4AFraSBCC9AvZpK9bQcMZ/DkbrZIOJZu3MaTg18LKMQkfrbVycu3n91440ONtWw/+xn8WqDgMIRKYIBGExGgjkh1o2AUjIJRMCIBAM4uQNw+SS2eAAAAAElFTkSuQmCC","orcid":"","institution":"The Second Affiliated Hospital (Xinhua Hospital), Zhejiang Chinese Medical University","correspondingAuthor":true,"prefix":"","firstName":"Bochen","middleName":"","lastName":"Liang","suffix":""}],"badges":[],"createdAt":"2025-04-07 16:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6396213/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6396213/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83836732,"identity":"750dc5d5-fec9-408b-b071-741628820710","added_by":"auto","created_at":"2025-06-03 13:20:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23849,"visible":true,"origin":"","legend":"\u003cp\u003eCompared to the control group, the PINP level in the case group was significantly increased (**P \u0026lt; 0.01), and the β-CTX level was significantly decreased (***P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/ad691728251a9c72732b826a.png"},{"id":83836736,"identity":"168db073-2a77-4f49-a450-ecc952760f02","added_by":"auto","created_at":"2025-06-03 13:20:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":143365,"visible":true,"origin":"","legend":"\u003cp\u003ePanel A shows the number of differentially expressed proteins (DEPs). Panel B displays the relative quantification values of proteins on the x-axis, with the values log2-transformed, and the -Log10-transformed p-values of the significance test on the y-axis. In the figure, red dots represent significantly upregulated proteins, and blue dots represent significantly downregulated proteins. Panel C shows the Biological Process category. Panel D shows the Cellular Component category. Panel E shows the Molecular Function category. To interpret the biological roles of the proteins from different perspectives, we performed enrichment analysis of the DEPs in the three major categories of GO classification. Panel F shows the KEGG functional enrichment. Panel G displays the enrichment analysis of protein domains.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/ee54a5129d01b4005afcd90f.png"},{"id":83836735,"identity":"ed6275bc-abb5-4d0a-ae82-dca97ead1bc2","added_by":"auto","created_at":"2025-06-03 13:20:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":286499,"visible":true,"origin":"","legend":"\u003cp\u003ewe conducted enrichment analyses of differentially expressed proteins (DEPs) across comparison groups, focusing on Gene Ontology (GO) classifications, KEGG pathways, and protein domains. To explore the functional relationships among DEPs, we performed hierarchical clustering based on the enrichment p-values obtained from Fisher’s exact test. The resulting heatmap visually groups related functions across different comparison groups.Horizontally, the heatmap represents enrichment results for each group, while the vertical axis lists the enriched functional categories, including GO terms (Biological Process, Cellular Component, and Molecular Function), KEGG pathways, and protein domains. Specifically, Panel A presents a bar chart summarizing the hierarchical clustering of DEPs. Panel B shows the heatmap of enriched protein domains. Panels C, D, and E illustrate enrichment heatmaps for Biological Process, Cellular Component, and Molecular Function, respectively. Panel F displays the KEGG pathway enrichment heatmap.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/5acb97d31ab1eaa9e3acafac.png"},{"id":83837913,"identity":"603b5fe2-9cf5-408d-951b-f5c3781846a6","added_by":"auto","created_at":"2025-06-03 13:28:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":84514,"visible":true,"origin":"","legend":"\u003cp\u003ePositive and negative ion mode serum mass spectrometry profiles of Liuwei Dihuang Wan (LWDHW).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/4dc0797deca302d10e4595ed.png"},{"id":83837914,"identity":"0152d930-427d-4189-b576-0b9c8700068a","added_by":"auto","created_at":"2025-06-03 13:28:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41861,"visible":true,"origin":"","legend":"\u003cp\u003epresents the component composition of LWDHW identified in serum (A) and the intersection of drug targets, disease targets, and DEPs involved in bone metabolism (B).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/9cda243e0bd828cb2e4bab64.png"},{"id":83837915,"identity":"fa4a46c3-2fe8-48ba-83ef-a0d0858eaef5","added_by":"auto","created_at":"2025-06-03 13:28:08","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":36717,"visible":true,"origin":"","legend":"\u003cp\u003efunctional enrichment analysis was performed on the four overlapping core targets (PTPN11, SRC, GLUL, and ALOX12) to better understand their biological significance. Panel A presents the Gene Ontology (GO) enrichment results, which are categorized into three domains: Biological Process, Cellular Component, and Molecular Function. The analysis revealed that these targets are primarily involved in processes such as immune response, regulation of inflammation, and cytokine activity, suggesting their relevance in bone remodeling and pathological bone loss.\u003c/p\u003e\n\u003cp\u003ePanel B displays the KEGG pathway enrichment bubble plot, which highlights several significantly enriched signaling pathways. Notably, the C-type lectin receptor signaling pathway and the Toll-like receptor signaling pathway were among the top enriched pathways. Both are known to play key roles in regulating inflammatory and immune responses. These findings support the hypothesis that LWDHW may exert therapeutic effects on bone metabolism through modulation of inflammation and immune signaling, providing a potential mechanistic explanation for its anti-osteoporotic properties.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/023a4e576a1f758b445da44e.png"},{"id":83836741,"identity":"437b9391-e9de-4b87-9391-2cf8b738f6f4","added_by":"auto","created_at":"2025-06-03 13:20:08","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":154327,"visible":true,"origin":"","legend":"\u003cp\u003e(A–D) Molecular docking visualization of the four overlapping core targets with their respective ligands:(A) PTPN11, (B) SRC, (C) GLUL, and (D) ALOX12.Each panel displays the binding conformation and interaction mode between the compound and the target protein.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/0f4d00438408da9c6835bf19.png"},{"id":83836737,"identity":"68b1b555-460b-44d5-b6e4-460e8f4b2809","added_by":"auto","created_at":"2025-06-03 13:20:08","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":22836,"visible":true,"origin":"","legend":"\u003cp\u003eProliferation of MC3T3-E1 cells over 80 hours following treatment with LWDHW-containing serum.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6396213/v1/9ef9e6c713fcee96229a86e1.png"},{"id":83836744,"identity":"587b5e5a-dcc3-42e7-b7d7-5c86c46f5246","added_by":"auto","created_at":"2025-06-03 13:20:08","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":125375,"visible":true,"origin":"","legend":"\u003cp\u003e(A) Representative Western blot images showing the expression levels of key signaling proteins in MC3T3-E1 cells treated with different concentrations of LWDHW-containing serum: P-P65, P65, P-IKBα, IKBα, P-AKT, AKT, P-SRC, SRC, P-ERK1/2, ERK1/2, P-SHPTP2, SHPTP2, OCN, GAPDH, and Histone H3.(B, C) Quantitative analysis of protein expression ratios (n ≥ 3). Data are presented as mean ± SD from at least three independent experiments. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, unless otherwise specified. 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It is regulated by a dynamic balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, which ensures bone strength, remodeling, and repair\u003csup\u003e1,2\u003c/sup\u003e. Osteoblasts secrete the bone matrix and promote its mineralization, continuously constructing new bone tissue, while osteoclasts degrade bone minerals and collagen fibers in an acidic environment, clearing old or damaged bone. This finely tuned \"bidirectional balance\" not only affects the structure and function of the skeletal system but is also closely related to calcium-phosphorus metabolism\u003csup\u003e3\u003c/sup\u003e, endocrine regulation, and other systems. However, when this balance is disrupted due to aging, hormonal imbalances chronic inflammation, or genetic factors, bone resorption significantly outweighs bone formation\u003csup\u003e4,5\u003c/sup\u003e. This leads to reduced bone mass, disrupted bone microstructure, and increased bone fragility, ultimately resulting in metabolic bone diseases such as osteoporosis (OP).\u003c/p\u003e\n\u003cp\u003eOsteoporosis, often referred to as a \"silent epidemic,\" is characterized by decreased bone mass and the degeneration of bone tissue microstructure, which increases the risk of brittle fractures\u003csup\u003e6\u003c/sup\u003e. It has become a significant global public health challenge. Statistics show that more than 1.5 million fractures occur annually worldwide due to osteoporosis\u003csup\u003e7\u003c/sup\u003e, with the one-year mortality rate for patients with hip fractures reaching up to 20%\u003csup\u003e8–10\u003c/sup\u003e. OP is often accompanied by pain and functional limitations, significantly affecting daily life and self-care abilities\u003csup\u003e11\u003c/sup\u003e. While traditional Western medicine can partially improve bone density, long-term use often faces challenges such as drug side effects (e.g., bisphosphonates increasing the risk of jaw necrosis\u003csup\u003e12\u003c/sup\u003e) or diminished efficacy over time (e.g., the limited treatment course of teriparatide\u003csup\u003e13\u003c/sup\u003e). This highlights the need for new intervention strategies based on multiple targets and holistic regulation, which aligns well with the holistic approach in traditional Chinese medicine (TCM).\u003c/p\u003e\n\u003cp\u003eLiu Wei Di Huang Wan (LWDHW), originating from the \"Pediatric Medicine Evidence\" by Qian Yi, is composed of six traditional Chinese herbs: Rehmannia glutinosa, Cornus officinalis, Dioscorea opposita, Alisma orientalis, Paeonia lactiflora, and Poria cocos. It is a classic formulation used to nourish yin, strengthen the kidneys, enrich the essence, and fortify the bones\u003csup\u003e14,15\u003c/sup\u003e. Modern pharmacological research has explored LWDHW's role in preventing and treating osteoporosis, but most studies have focused on single-target or individual active ingredients rather than the compound's synergistic effects, resulting in limited findings. Research suggests that LWDHW may exert its effects in osteoporosis prevention and treatment through mechanisms such as inhibiting bone resorption and promoting bone formation\u003csup\u003e16,17\u003c/sup\u003e, but the specific mechanisms and active components remain unclear.\u003c/p\u003e\n\u003cp\u003eTo further investigate the foundational components of LWDHW's effect on bone metabolism, we first conducted ELISA tests on serum samples from rat to analyze changes in bone metabolism indicators (β-CTX and PINP) and verify LWDHW’s regulatory effect on bone metabolism. Active compounds in the serum were identified using UPLC-MS to determine its effective ingredients. Quantitative proteomics was used to analyze differentially expressed proteins (DEPs) in the serum, identifying the targets of LWDHW's active components. Additionally, bioinformatics methods, including GO and KEGG pathway enrichment analysis, molecular docking, and molecular dynamics simulations, were employed to analyze and verify the interactions between drug components and targets. Finally, Western blotting was used to validate the expression trends of key proteins, revealing the synergistic mechanism of LWDHW's components and targets and exploring how it alters bone metabolism to prevent and treat osteoporosis. This study provides theoretical foundations and data support for future research in this area.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Preparation of Liu Wei Di Huang Wan (LWDHW) Solution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe preparation of LWDHW followed previously reported methods. Rehmannia glutinosa, Cornus officinalis, Dioscorea opposita, Alisma plantago-aquatica, Paeonia suffruticosa, and Poria cocos were mixed in a classical ratio of 8:4:4:3:3:3 (total weight: 525g). The mixture was soaked in distilled water for 30 minutes and decocted twice for 1 hour each. The filtrates were collected, combined, and concentrated to 1 g/mL. The final solution was stored at −20°C until use\u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Animal Maintenance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEight-week-old male Sprague-Dawley (SD) rat were used.\u0026nbsp;All animals were housed and maintained according to the Guidelines for the Care and Use of Laboratory Animals of Zhejiang Chinese Medical University (Animal license number: SYXK (Zhe) 2021-0012), with approval from the Institutional Animal Care and Use Committee (IACUC) (Approval No. 20220913-23). Before the experiment, twelve rat were acclimated for 2 weeks in a temperature-controlled room (22 ± 2°C) with 55 ± 10% relative humidity and free access to standard chow and water.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Serum Preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRat were randomly divided into the experimental and control groups (n = 6 per group). The experimental group was administered the LWDHW extract prepared in section 2.1 via oral gavage at a dose of 0.7 mL/100 g body weight daily, while the control group received normal saline for 7 consecutive days. Two hours after the final gavage, the rats were anesthetized via intraperitoneal injection of Zoletil®50 (50 mg/kg) and acetaminophen (100 mg/kg), followed by blood collection through cardiac puncture. \u0026nbsp;Blood samples were allowed to stand for 30 minutes, then centrifuged at 3,000 rpm for 15 minutes. The supernatant (3 mL) was collected and filtered through a 0.22 μm microporous membrane to obtain serum, which was stored at −80°C for further analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Serum ELISA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter centrifugation, serum samples were thawed at 4°C, diluted, and analyzed for β-CTX and PINP levels using commercial ELISA kits (CTX-1: CUSABIO, CSB-E12776r; PINP: CUSABIO, CSB-E12774r), following the manufacturer’s protocols. Optical density (OD) was measured at 450 nm, and standard curves were generated to calculate sample concentrations. β-CTX was used as a marker for osteoclast activity and PINP as a marker for osteoblast function\u003csup\u003e19\u003c/sup\u003e. Their combined evaluation provides a reliable indication of bone turnover and osteoporosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Proteomic Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTandem Mass Tag (TMT) labeling was performed for proteomic quantification. After trypsin digestion, peptide mixtures were fractionated by HPLC and analyzed using LC-MS/MS. Mass spectrometry data were annotated using UniProt-GOA (GO function), Pfam (protein domains), KEGG (pathways), BLAST (sequence homology), eggNOG (homolog classification), and PSORTb/WoLF PSORT (subcellular localization).\u003c/p\u003e\n\u003cp\u003eDifferentially expressed proteins (DEPs) between groups were identified based on fold-change \u0026gt;1.3 or \u0026lt;1/1.3 with a T-test p \u0026lt; 0.05. Proteins were classified as upregulated or downregulated accordingly. GO and KEGG analyses were performed to explore potential biological functions and pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 Serum Metabolomics via Mass Spectrometry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLWDHW-medicated serum was mixed with 80% methanol (v/v, 1:3), sonicated (40 kHz, 30 min), centrifuged (12,000 × g, 10 min), and filtered through a 0.22 μm organic membrane for HPLC-MS analysis. A ZenoTOF™ 7600 system (SCIEX, USA) was used. Mobile phases were 0.1% formic acid in water (A) and acetonitrile (B) with a gradient: 0–3 min 5% B; 3–20 min 5%–95% B; 20–25 min 95% B; re-equilibration for 3 min. Column temperature was 35°C, flow rate 0.3 mL/min, injection volume 5 μL. ESI was used in both positive and negative ion modes.MS parameters: spray voltage 3.8 kV, capillary temperature 320°C, auxiliary gas 45 Arb, sheath gas 50 Arb, Full MS resolution 70,000, dd-MS² resolution 17,500, scan range m/z 100–1500, HCD collision energy set to 25/35/45 eV.\u003c/p\u003e\n\u003cp\u003eCompound identification was supported by literature retrieval from CNKI, PubMed, Web of Science, HERB, and TCMSP. Identified compounds were verified using ChemSpider, ChemicalBook, and PubChem.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Network Pharmacology Based on Metabolomics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIdentified compounds were compared with herbal ingredient databases (HERB, TCMSP). SMILES formats were retrieved from PubChem and targets predicted using SwissTargetPrediction. Osteoporosis-related targets were identified using GeneCards, DrugBank, and OMIM with median filtering. After de-duplication, final OP-related targets were obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.8 Integration of DEPs and Network Targets\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDEPs from Section 2.5 were converted to human orthologs using UniProt. Venn analysis using Venny 2.1.0 identified overlapping targets between serum compound targets, disease targets, and DEPs. Overlapping targets were considered potential therapeutic targets for OP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.9 GO and KEGG Pathway Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCommon targets were submitted to DAVID for GO term and KEGG pathway enrichment analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.10 Molecular Docking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking was performed using AutoDock Vina (v1.5.6). The 3D structures of PTPN11 (PDB: 4h1o), SRC (PDB: 2SRC), GLUL (PDB: 2OJW), and ALOX12 (PDB: 3D3L) were downloaded from the PDB. Ligands including swertiamarin (PubChem CID: 442435), adenosine (CID: 60961), Alisol B (CID: 15558620), and linolenic acid (CID: 5280934) were obtained from PubChem.\u003c/p\u003e\n\u003cp\u003eLigand structures were optimized using PyMol (hydrogenation, protonation, energy minimization), and docking simulations were conducted with AutoDock Vina. Binding affinity and interaction modes were visualized with PyMol.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.11 Cell Culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMC3T3-E1 mouse preosteoblasts (ATCC) were cultured in α-MEM supplemented with 10% fetal bovine serum and antibiotics (100 mg/mL streptomycin, 100 U/mL penicillin, Gibco) at 37°C in a 5% CO₂ incubator\u003csup\u003e20\u003c/sup\u003e. Cells at passage 3 were used4.For induction, cells were seeded at 2 × 10⁵/well in 6-well plates and cultured until 70% confluency. Osteogenic medium (2 mL/well) containing 10 nM dexamethasone, 10 mM β-glycerophosphate, and 50 μg/mL ascorbic acid was added. Medium was changed every 2 days\u003csup\u003e21\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eExperimental groups:Control: induced with normal mouse serum + FBS、Treatment: 2%, 8%, and 14% LWDHW-medicated serum added, cultured for 14 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.12 Real-Time Cell Analysis (RTCA) for Proliferation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe xCELLigence system (Agilent) was used to monitor real-time proliferation. First, 50 μL of medium was added to each well of an E-plate 16. After baseline measurement, 100 μL of cell suspension was added. Plates were incubated at room temperature for 20 minutes before insertion into the RTCA device\u003csup\u003e22\u003c/sup\u003e. Impedance was continuously monitored. Each assay included replicates for reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.13 Western Blot\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter 14 days of induction, cells were washed with PBS and lysed in 1× lysis buffer containing 1 mM PMSF. Samples were boiled at 95°C for 10 minutes and separated by SDS-PAGE (12%). Proteins were transferred to PVDF membranes and blocked with QuickBlock buffer (PS108, Epizyme Biotech) for 20 minutes at room temperature.\u003c/p\u003e\n\u003cp\u003eMembranes were incubated overnight at 4°C with primary antibodies, then washed and incubated with secondary antibodies for 1 hour. Bands were detected using the Tanon 5500 system and quantified using ImageJ. Each experiment was repeated at least three times.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.14 Statistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experiments were conducted at least in triplicate. Data were analyzed using GraphPad Prism 8. ELISA data were assessed with the Mann–Whitney test. Unpaired t-tests were used for proteomics comparisons, and one-way or two-way ANOVA was used for multiple group comparisons. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001 indicated statistical significance, while 'ns' denoted non-significance.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e3.1LWDHW Significantly Modulates Bone Metabolism Markers\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum levels of bone metabolism markers were measured in both experimental and control rat using ELISA. The results demonstrated that the levels of PINP and \u0026beta;-CTX were significantly altered in the LWDHW-treated group compared to the control group (P \u0026lt; 0.01, P \u0026lt; 0.001, respectively). Specifically, the PINP level was significantly increased, while the \u0026beta;-CTX level was markedly decreased in the experimental group. These findings indicate that LWDHW significantly regulates bone metabolic processes by promoting bone formation and inhibiting bone resorption ( Figure 1)(Table 1) ( Supporting Information S1).\u003c/p\u003e\n\u003cp\u003eTable 1: The table displays the concentration data of two biomarkers, PINP and \u0026beta; - CTX, for the Case and Control groups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eGroup（n=6）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003ePINP（pg/mL）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003e\u0026beta;-CTX（pg/mL）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eCase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003e525.1(98.8，748.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003e11.68（9.45 ，15.02）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003e457.2 (417.1，520.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 184px;\"\u003e\n \u003cp\u003e25.84（20.31，30.55）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 LWDHW on the Mechanism of Action in Rat and Proteomics Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 173 Differentially Expressed Proteins (DEPs, as shown in the figure.2A) were identified when comparing the experimental group with the control group. To further demonstrate the significance of the differences, a volcano plot was generated by performing a -Log10 transformation of the p-values from the significance tests (as shown in the figure.2B). Compared to the control group, a total of 63 upregulated proteins and 114 downregulated proteins were detected in the experimental group.\u003c/p\u003e\n\u003cp\u003eFor these differential proteins, we conducted further functional annotations, including COG, GO (Gene Ontology), and KEGG pathway analysis. The results revealed that these differential proteins are involved in several biological processes, including energy production and conversion, signal transduction mechanisms, intracellular transport, secretion and vesicle trafficking, as well as cytoskeletal construction (as shown in the figure.2C-G).\u003c/p\u003e\n\u003cp\u003eTo better illustrate the differences in protein abundance between the two groups, we performed hierarchical clustering analysis of the differentially expressed proteins (DEPs). This analysis helps reveal the functional correlations of the DEPs. KEGG pathway analysis results showed that the DEPs are involved in several important signaling pathways, including the Rap1 signaling pathway, PI3K-Akt signaling pathway, Ras signaling pathway, MAPK signaling pathway, nitrogen metabolism, ammonia metabolism, and reactive oxygen species (ROS) metabolism(as shown in the figure.3A-F). Downregulated proteins enriched in these pathways include Hspa8, Rap1b, Src, Tln1, Ywhab, and Ptpn11（Please refer to Attachment 2 for details）. These data suggest that LWDHW may exert its protective and therapeutic effects on osteoporosis by promoting the differentiation and proliferation of osteoblasts, or by altering bone metabolism through antioxidant stress mechanisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Analysis of Bioactive Components of LWDHW in Serum\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUPLC-MS analysis of LWDHW-medicated serum identified a total of seven major categories of compounds（Figure 4）. These primarily included glycosides, triterpenoids and their derivatives, and phenolic compounds. Specifically, 30 glycosides, 19 triterpenoids and their derivatives, 14 phenolic compounds and derivatives, 12 organic acids, 7 fatty acids and lipids, 9 sugars and sugar derivatives, and 14 compounds from other categories were detected. Detailed classification and distribution are shown in Figure 5A.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.1 Analysis of Serum-Derived Compounds and Their Targets of LWDHW\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 105 compounds were identified in serum following the administration of LWDHW（Table 2）. After filtering disease-related targets for osteoporosis using median-based criteria, 2,300 relevant targets were retrieved. Using the Venny 2.1.0 tool (https://bioinfogp.cnb.csic.es/tools/venny/index.html), four overlapping targets were identified between the LWDHW-related compounds, osteoporosis-associated targets, and differentially expressed proteins (DEPs): PTPN11, SRC, GLUL, and ALOX12 (Figure 5B). These targets are likely to play critical roles in mediating the therapeutic effects of LWDHW on bone metabolism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.2 GO and KEGG Pathway Analysis of Core Targets\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further explore the biological roles of these core targets, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the DAVID database (https://davidbioinformatics.nih.gov/). This functional enrichment analysis provided insights into the biological processes, cellular components, and molecular functions associated with the overlapping targets, as well as the signaling pathways they may be involved in.\u003c/p\u003e\n\u003cp\u003eTo visualize the results, GO bar charts and KEGG bubble plots were generated using the Bioinformatics platform (https://www.bioinformatics.com.cn/plot_basic_line_stack_plot_060). The analyses revealed that the core targets are involved in biological processes such as immune response, inflammatory regulation, and cytokine-mediated signaling. KEGG enrichment results showed significant involvement in pathways such as the C-type lectin receptor signaling pathway and the Toll-like receptor signaling pathway, both of which are closely associated with inflammation modulation. These findings suggest that LWDHW may alter bone metabolism by mitigating inflammatory responses or enhancing immune function (Figure 6A\u0026ndash;B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.3 Molecular Docking Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further evaluate the binding affinity between bioactive serum compounds and potential pharmacological targets, molecular docking was performed based on the intersection results from the Venn diagram. Four key targets\u0026mdash;PTPN11, SRC, GLUL, and ALOX12\u0026mdash;were selected due to their known involvement in bone metabolism and their potential role in mediating the effects of LWDHW\u003c/p\u003e\n\u003cp\u003eUsing reverse target prediction through network pharmacology, we docked these targets with candidate compounds. Binding energy was used as an indicator of interaction strength, with lower values representing stronger and more stable binding. As shown in the results, all selected compound\u0026ndash;target pairs exhibited binding energies below \u0026minus;5 kcal/mol, suggesting favorable spontaneous interactions and high binding stability. (as shown in Table 3)(\u0026nbsp;Figure 7.A-D. Visualization of Molecular Docking).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Binding affinities between key ligands and their corresponding protein targets (receptors).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eTarget gene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003ePDB ID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eAutodockenergy(kcal/mol)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003ePTPN11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4h1o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e442435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e-7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;SRC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2src\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e60961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e-7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026nbsp;GLUL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e2ojw\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e15558620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e-7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003eALOX12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e3d3l\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e5280934\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003e-6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Real-Time Cell Analysis (RTCA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRTCA results demonstrated that treatment with LWDHW-medicated serum significantly promoted the proliferation of MC3T3-E1 cells within 36 hours. Although no significant differences were observed among the various concentrations, all treatment groups showed a clear increase in cell proliferation compared to the control group. These findings indicate that LWDHW serum effectively enhances the growth and proliferation of MC3T3-E1 cells without exhibiting cytotoxic effects across the tested concentrations.( Figure 8) ( Supporting Information S2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6Western Blot Analysis of Osteogenic Pathway Activation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the underlying mechanisms by which LWDHW promotes osteogenic differentiation, we examined the activation of signaling pathways related to the core target genes using Western blot analysis. MC3T3-E1 cells were induced for osteogenic differentiation and treated with LWDHW-medicated serum. Previous studies have highlighted the roles of SHPTP2, AKT, and I\u0026kappa;B\u0026alpha; in osteogenic differentiation\u003csup\u003e23\u0026ndash;25\u003c/sup\u003e. As shown in the results( Figure 9, Supporting Information S3), several phosphorylated proteins showed a decreasing trend after treatment with LWDHW serum.\u003c/p\u003e\n\u003cp\u003eSpecifically, treatment with 14% LWDHW-medicated serum significantly reduced the ratios of phosphorylated to total protein for P-I\u0026kappa;B\u0026alpha;/I\u0026kappa;B\u0026alpha; (P \u0026lt; 0.05), P-AKT/AKT (P \u0026lt; 0.05), P-ERK1/2/ERK1/2 (P \u0026lt; 0.005), and P-P65/P65 (P \u0026lt; 0.05), compared to the control group. In contrast, the expression of Osteocalcin (OCN), a key marker of osteogenic differentiation, was significantly increased at both 8% and 14% serum concentrations (P \u0026lt; 0.05), indicating that LWDHW promotes osteogenic differentiation in a dose-dependent manner.\u003c/p\u003e\n\u003cp\u003eInterestingly, although P-SHPTP2/SHPTP2 showed a downward trend, the change did not reach statistical significance. Similarly, no significant change was observed in the P-SRC/SRC ratio. However, the downward trend of P-SHPTP2 was consistent with the reduction of PTPN11 observed in the proteomic analysis. In addition, downstream molecules of ALOX12, including I\u0026kappa;B\u0026alpha; and P65, also exhibited suppressed phosphorylation, further supporting its involvement in LWDHW-mediated signaling.\u003c/p\u003e\n\u003cp\u003eThese findings suggest that LWDHW promotes osteogenic differentiation and exhibits significant regulatory effects at both medium (8%) and high (14%) concentrations. At higher concentrations, LWDHW notably suppressed the ERK1/2, AKT, and I\u0026kappa;B\u0026alpha; signaling pathways, which may contribute to its pro-differentiation effects.Previous studies have shown that AKT and ERK1/2 are associated with cell proliferation, and their activation typically promotes growth\u003csup\u003e26\u003c/sup\u003e. The observed suppression of these pathways by LWDHW may shift the cells from a proliferative state toward differentiation, thereby enhancing osteogenic activity. This supports the hypothesis that LWDHW facilitates osteogenic differentiation through coordinated modulation of multiple signaling pathways.\u003c/p\u003e\n\u003cp\u003eAmong the four intersection genes identified, we validated three (PTPN11, SRC, and ALOX12). The GLUL gene was not included in this validation due to the widespread presence of glutamine in standard culture media, making it difficult to determine whether its effects were directly attributable to components of LWDHW.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLWDHW is a classical traditional Chinese herbal formula with clinical evidence supporting its efficacy in treating osteoporosis and regulating bone metabolism. However, the specific bioactive compounds and underlying mechanisms responsible for these effects remain poorly defined. Due to the multi-component and multi-target nature of traditional Chinese medicine, clinical outcomes alone often fall short in explaining the molecular basis of its therapeutic effects.In this study, ELISA analysis in rat demonstrated that LWDHW significantly altered serum biomarkers of bone metabolism, consistent with its reported clinical benefits. Building on this, quantitative proteomic analysis revealed that LWDHW may influence osteoblast differentiation and bone formation through several key pathways, including Rap1, PI3K-Akt, Ras, and MAPK signaling, as well as nitrogen metabolism, ammonia metabolism, and oxidative stress-related processes.UPLC-MS analysis identified 105 chemical constituents in the serum following administration of LWDHW. By integrating these data with network pharmacology, as well as GO and KEGG enrichment analysis of differentially expressed proteins, we identified four core therapeutic targets—PTPN11, SRC, GLUL, and ALOX12. Molecular docking studies further confirmed strong binding affinities between these proteins and LWDHW-derived compounds. Western blot analysis showed that LWDHW modulates downstream signaling pathways of PTPN11, SRC, and ALOX12, inhibiting the activation of ERK1/2, AKT, and IκBα, while promoting the expression of the osteogenic marker OCN. These findings suggest a coordinated mechanism through which LWDHW enhances osteoblast differentiation and exerts protective effects against osteoporosis.\u003c/p\u003e\n\u003cp\u003eSerum analysis revealed that, compared to controls, rat treated with LWDHW exhibited significantly elevated levels of P1NP and reduced levels of β-CTX markers indicative of increased bone formation and decreased bone resorption, respectively. This suggests that LWDHW exerts a dual regulatory effect on bone metabolism by promoting osteoblast activity while inhibiting osteoclast function.\u003c/p\u003e\n\u003cp\u003eProteomic results showed enrichment of differentially expressed proteins in several signaling pathways, including Rap1, PI3K-Akt, Ras, MAPK, and reactive oxygen species (ROS)-related signaling. Notably, Rap1 is a small GTPase involved in cell adhesion, junction formation, and polarity, all of which are essential in bone cell function. Prior studies have demonstrated that activation of the Rap1 pathway promotes osteogenesis and inhibits osteoclastogenesis in vivo\u003csup\u003e27\u003c/sup\u003e. Additionally, Talin1 and Rap1 are known to regulate osteoclast adhesion and bone resorption. Disruption of this axis impairs integrin signaling, leading to reduced bone resorption and, in some cases, a high bone mass phenotyp\u003csup\u003e28\u003c/sup\u003e.In our study, Talin1 (Tln1) was significantly downregulated following LWDHW treatment, indicating that the formula may suppress osteoclast differentiation and function via the Talin1–Rap1 signaling axis, thereby contributing to the observed reduction in β-CTX and increase in P1NP.Another key finding was the downregulation of Hspa8, which encodes the heat shock protein HSC70. Reduced HSC70 levels have been shown to prevent lysosomal degradation of PRL2, a tyrosine phosphatase highly expressed in bone marrow monocytes. Loss of PRL2 leads to excessive activation of Rac1 and hyperphosphorylation of the MAPK and NF-κB pathways, accelerating osteoclast differentiation and bone resorption\u003csup\u003e29\u003c/sup\u003e. In this context, decreased HSC70 may stabilize PRL2, ultimately restraining osteoclast activity.Together, these findings suggest that LWDHW modulates bone metabolism through complementary mechanisms: promoting osteoblast differentiation while simultaneously inhibiting osteoclastogenesis. The involvement of Talin1-Rap1 signaling and HSC70-mediated regulation of PRL2 offers new mechanistic insights and potential therapeutic targets for the treatment of osteoporosis.\u003c/p\u003e\n\u003cp\u003eAlisol-B, a bioactive compound isolated from Alisma orientale, has been shown to inhibit osteoclastogenesis both in vitro and in vivo. Firstly, Alisol-B suppresses RANKL-induced phosphorylation of JNK, a key signaling molecule in osteoclast differentiation. In addition, it inhibits the expression of NFATc1 and c-Fos, both critical transcription factors downstream of RANKL, thereby blocking the differentiation of osteoclast precursors. Finally, Alisol-B disrupts the actin ring structure of mature osteoclasts and suppresses the formation of bone resorption pits, indicating its direct inhibitory effect on osteoclastic bone resorption\u003csup\u003e30\u003c/sup\u003e.Another study reported that linolenic acid intake is associated with reduced fracture risk. Dietary α-linolenic acid (ALA) improves osteoporosis progression by targeting multiple inflammatory cascades. High ALA intake (\u0026gt;1.39 g/day) was significantly associated with a decreased risk of hip fractures in older adults (HR = 0.46)\u003csup\u003e31\u003c/sup\u003e. Additional evidence suggests that ALA may exert indirect antioxidant effects by replacing arachidonic acid (AA) in phospholipids of the cell membrane, thereby reducing the accumulation of lipid peroxidation products such as malondialdehyde (MDA). This preservation of mitochondrial function contributes to decreased bone resorption.\u003c/p\u003e\n\u003cp\u003eAdenosine, derived from Rehmannia glutinosa and Poria cocos, is an endogenous nucleotide known to play a crucial role in bone homeostasis\u003csup\u003e32\u003c/sup\u003e. High concentrations of adenosine can activate A2 receptors to promote bone remodeling. In mouse models, adenosine significantly improved bone structure and strength, accompanied by increased expression of ALP, osteocalcin, and osteoprotegerin\u003csup\u003e32,33\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCollectively, current evidence suggests that Alisol-B, linolenic acid, and adenosine can suppress osteoclast development, control inflammation and oxidative stress, and may share overlapping mechanisms with LWDHW. These findings warrant further experimental validation.\u003c/p\u003e\n\u003cp\u003eMolecular docking was employed to validate the findings of the network pharmacology analysis. The docking results demonstrated that the active compounds in LWDHW exhibited favorable binding affinities with key targets, indicating that LWDHW may regulate bone metabolism through pharmacological targeting of proteins such as PTPN11, SRC, GLUL, and ALOX12. These interactions may contribute to the dual regulatory effects of promoting osteogenesis and inhibiting bone resorption.\u003c/p\u003e\n\u003cp\u003eWestern blot analysis further revealed that LWDHW suppresses the activity of the SHPTP2 pathway during osteogenic differentiation. SHPTP2, encoded by PTPN11, is a non-receptor type protein tyrosine phosphatase that plays a central role in the RAS-MAPK and PI3K-AKT-mTOR signaling pathways by modulating the phosphorylation status of adaptor proteins Gab1/2. Upon phosphorylation, Gab1/2 recruits the Grb2-SOS complex, while SHPTP2 dephosphorylates Gab1/2, releasing SOS (Son of Sevenless), a guanine nucleotide exchange factor that catalyzes the conversion of GDP to GTP on RAS (RAS-GTP), thereby activating the RAF kinase family. Phosphorylated RAF activates MEK1/2, which in turn phosphorylates ERK1/2. Activated ERK1/2 subsequently phosphorylates ribosomal S6 kinase (RSK1), leading to destabilization of the TSC1-TSC2 complex and regulation of downstream mTOR activity\u003csup\u003e34–36\u003c/sup\u003e.Studies have shown that inhibition of p-SHPTP2 activity results in sustained phosphorylation of critical tyrosine residues on Gab1/2 (Y627/Y659), thereby attenuating the RAS-MAPK/mTOR signaling cascade\u003csup\u003e37\u003c/sup\u003e. Another study demonstrated that suppression of mTOR signaling alleviates its inhibitory effect on osteogenic transcription factors RUNX2 and Osterix, markedly enhancing osteocalcin (OCN) expression and promoting mineralized nodule formation in vitro\u003csup\u003e38\u003c/sup\u003e.Interestingly, our Western blot results suggest that LWDHW may act via a similar mechanism. The current evidence indicates that LWDHW reduces SHPTP2 activity and downstream ERK1/2 phosphorylation, thereby promoting osteogenic differentiation. Additional data suggest that LWDHW at high concentrations may inhibit inflammatory interference by suppressing the NF-κB pathway and cooperatively inhibit AKT and ERK, facilitating cell cycle exit and upregulating OCN expression to further enhance osteogenesis\u003csup\u003e39,40\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFrom the perspective of drug-target signaling pathways, LWDHW and its active components regulate bone metabolism through a multi-pathway, multi-target synergistic mechanism. LWDHW suppresses the activity of SHPTP2 encoded by PTPN11, thereby promoting OCN expression and enhancing osteoblast differentiation. At the same time, it downregulates the Talin1–Rap1 axis to inhibit osteoclast adhesion and bone resorption.\u003c/p\u003e\n\u003cp\u003eAlisol-B targets key nodes in the RANKL signaling pathway such as JNK, c-Fos, and NFATc1, thereby blocking osteoclast differentiation and function. Linolenic acid indirectly modulates the MAPK/NF-κB signaling pathways by inhibiting reactive oxygen species (ROS) and inflammatory cascades, thereby alleviating bone resorption. Adenosine, by activating the A2A receptor, promotes osteogenesis via the PI3K-Akt and BMP-related pathways.\u003c/p\u003e\n\u003cp\u003eThese four compounds converge on several key signaling pathways—including MAPK, PI3K-Akt, NF-κB, and mTOR—and exhibit overlapping targets, collectively contributing to the homeostatic regulation of bone metabolism by enhancing osteogenesis and suppressing osteoclastogenesis.\u003c/p\u003e\n\u003cp\u003eHowever, there are several limitations in this study that require further investigation. Firstly, the rat used in this study were not osteoporotic model rat, which may affect the comprehensiveness of the therapeutic effect of LWDHW. The group of active compounds may not be fully represented in this model. Although clinical and animal studies have already demonstrated the therapeutic effect of LWDHW on osteoporosis, the full spectrum of active compounds still needs to be confirmed. Secondly, in vivo experiments in animals are lacking to verify the results.\u003c/p\u003e\n\u003cp\u003eNevertheless, this study also has several strengths. First, male rat were selected as the research subjects, which reduces the physiological effects of hormonal cycle variations. Second, the genes of rat are highly similar to those of humans, and the use of mouse-derived differential proteins mapped to human proteins ensures safety and reliability. Finally, further research is needed to better elucidate the mechanisms of these active compounds.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eLWDHW significantly impacts bone metabolism, and its active components may synergistically promote osteogenic differentiation through Linolenic acid, Alisol-B, Adenosine, and Swertiamarin. These components regulate key targets such as PTPN11, SRC, GLUL, and ALOX12, through pathways involving SHPTP2, AKT, ERK1/2, and IκBα, thereby influencing bone metabolism. However, this study still has some limitations and requires further research to confirm the exact mechanisms involved.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to the laboratory of the Second Clinical College of Zhejiang Chinese Medical University for their invaluable support in conducting the experiments for this study. Their assistance and resources were crucial in the successful completion of this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the National Natural Science Foundation of China (Project No. 81803902).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZhongliao Zeng and Kaifeng Lin proposed hypotheses and designed experiments.Zhongliao Zeng, Yuyi Li, Jianxiong Ma, and Jinkun Li conducted animal and in vitro experiments. Bochen Liang, Zhongliao Zeng, Yifeng Yuan, and Min Li analyzed the data and wrote the initial draft. All authors have reviewed and agreed to the manuscript's final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal study was approved by the Institutional Animal Care and Use Committee of Zhejiang Chinese Medical University (Approval No. 20220913-23).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors unanimously agree to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is reported in accordance with the ARRIVE guidelines (Version 2.0) (https://arriveguidelines.org).\u003c/p\u003e\n\u003cp\u003eThis experiment has been approved by the Institutional Animal Management and Ethics Committee (IACUC) of Zhejiang University of Traditional Chinese Medicine (Approval No. 20220913-23)\u003c/p\u003e"},{"header":" References","content":"\u003col\u003e\n\u003cli\u003eFonseca, H., Moreira-Gon\u0026ccedil;alves, D., Coriolano, H.-J. 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Effects of tanshinol on markers of bone turnover in ovariectomized rats and osteoblast cultures. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, e0181175 (2017).\u003c/li\u003e\n\u003cli\u003eMiao, Y. \u003cem\u003eet al.\u003c/em\u003e Caffeine regulates both osteoclast and osteoblast differentiation via the AKT, NF-\u0026kappa;B, and MAPK pathways. \u003cem\u003eFront Pharmacol\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1405173 (2024).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Liu Wei Di Huang Wan, ELISA, Proteomics, UPLC-MS, Molecular Docking, Bone Metabolism","lastPublishedDoi":"10.21203/rs.3.rs-6396213/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6396213/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLiu Wei Di Huang Wan(LWDHW) is a classic traditional Chinese medicine widely used in preventing and treating osteoporosis associated with kidney yin deficiency, with proven clinical benefits. However, its active ingredients, targets, and synergistic mechanisms remain unclear. This study aims to identify the key factors and mechanisms by which LWDHW treats osteoporosis using proteomics, serum pharmacochemistry, molecular docking, pharmacokinetics, and in vitro validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003cbr\u003e\nHealthy male rat were randomly assigned to a saline control group or an LWDHW-treated group. After seven days of intervention, serum samples were collected to assess bone metabolism by measuring PINP and β-CTX levels via ELISA. Active compounds in the serum were identified using UPLC-MS. Differentially expressed proteins (DEPs) were analyzed through quantitative proteomics, and key targets were determined using GO and KEGG enrichment analyses, molecular docking. Western blot analysis was performed to verify the expression trends of these key proteins.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with the control group, the LWDHW group showed a significant increase in PINP levels (P \u0026lt; 0.01) and a significant decrease in β-CTX levels (P \u0026lt; 0.001), indicating that LWDHW not only suppresses bone resorption but also promotes bone formation. Seven categories of active compounds were detected, including glycosides, triterpenoids and derivatives, phenolics, organic acids, fatty acids and lipids, carbohydrates, and others. Proteomic analysis identified 173 DEPs, with 63 proteins upregulated and 114 downregulated in the treated group. Bioinformatics analysis highlighted PTPN11, SRC, GLUL, and ALOX12 as key targets, and molecular docking revealed that compounds such as linolenic acid, Alisol B, adenosine, and swertiamarin had strong binding affinities (all binding energies below –5) with these targets. Moreover, Western blot results confirmed that high concentrations of LWDHW-containing serum significantly inhibited the AKT, ERK1/2, and IκBα pathways (P \u0026lt; 0.05) while markedly increasing osteocalcin (OCN) expression (P \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\nLWDHW promotes osteogenic differentiation and effectively treats osteoporosis through multiple synergistic pathways.\u003c/p\u003e","manuscriptTitle":"Integration of UPLC-MS and Quantitative Proteomics Reveals Key Bioactive Components and Osteoactive Targets of Liuwei Dihuang Wan in Bone Metabolism Modulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-03 13:20:03","doi":"10.21203/rs.3.rs-6396213/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"70e9fd57-e587-4b24-a0f5-ce9b0e18a37c","owner":[],"postedDate":"June 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49287468,"name":"Biological sciences/Plant sciences/Plant molecular biology"},{"id":49287469,"name":"Health sciences/Medical research/Drug development"},{"id":49287470,"name":"Health sciences/Medical research/Outcomes research"},{"id":49287471,"name":"Health sciences/Health care/Fracture repair"},{"id":49287472,"name":"Health sciences/Health care/Disease prevention/Nutritional supplements"},{"id":49287473,"name":"Health sciences/Health care/Disease prevention/Preventive medicine"},{"id":49287474,"name":"Health sciences/Health care/Geriatrics"}],"tags":[],"updatedAt":"2025-06-20T07:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-03 13:20:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6396213","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6396213","identity":"rs-6396213","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}