Asthma is a chronic airway inflammatory disease characterized by airway inflammation, mucus hypersecretion, airway hyper-reactivity. Sanzi Yangqin Decoction (SZYQD) is widely prescribed for asthma treatment. Its anti-asthma activities have been reported in animal model, but the exact mechanism and targets of SZYQD in asthma treatment have not been fully elucidated.A network pharmacological approach was used to predict the active components, targets, and signalling pathways of SZYQD in asthma, including potential target prediction, protein‒protein interaction (PPI) network construction and analysis, and Gene Ont (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The active ingredients were identified from the SZYQD, and were molecular docked according to the results of network pharmacology. A mouse model of asthma induced by ovalbumin (OVA) and lipopolysaccharide (LPS) was constructed to evaluate the therapeutic effect of SZYQD. Furthermore, the effects of SZYQD and its active ingredients were tested in vitro for regulating inflammation and MUC5AC expression  in macrophages and airway epithelial cells by using Real-time PCR and western blotting.A total of 28 active ingredients and 111 HUB genes were screened in the relevant databases, including three key ingredients  and nine core target genes . KEGG and GO analysis indicated that the potential anti-asthmatic mechanisms of SZYQD were related to PI3K-Akt signalling pathway and response to lipopolysaccharide, etc. In the in vivo asthmatic model, our findings demonstrated that SZYQD exerted a protective effect against asthmatic mice induced by OVA and LPS through the inhibition of inflammation and mucus overproduction. Consistently, cell experiments showed that the SZYQD extract or the key active ingredients luteolin significantly decreased lipopolysaccharide (LPS)-induced IL-6 expression and activation of the NF-κB pathway in macrophages. In addition, SZYQD extract or luteolin inhibited activation of the AKT pathway and expression of MUC5AC induced by EGF in airway epithelial cells.The anti-asthmatic mechanism of SZYQD might be associated with inhibiting inflammation and airway mucus hypersecretion by regulating the NF-κB and AKT signalling pathways as predicted by network pharmacology, which provides more evidence for the application of SZYQD in asthma treatment.The online version contains supplementary material available at 10.1186/s12906-023-04272-6. Asthma is a global disease, with more than 339 million cases according to the 2016 global disease burden study .Fructose Perillae, Semen Raphani, and Semen Sinapis Albae. This prescription has gained widespread recognition and is frequently employed for the treatment of asthma [Clinically, traditional Chinese medicine has good curative effect in treating asthma . The orif asthma –9. For ef asthma . Yang etNetwork pharmacology refers to the selection of specific nodes, multiple targets, and multiple signalling pathways based on the theory of systems biology and biological system networks , 11. It http://tcmspw.com/tcmsp.php) was used to query the components of SZYQD, including Perilla frutescens,Semen sinapis,Semen raphani to obtain the corresponding compounds. OB  > = 30% and DL (drug-like property) > = 0.18 were used as thresholds to screen the active compounds from the TCMSP. Furthermore, as supported by the available literature, additional compounds presented in SZYQD that potentially possessed therapeutic properties, but did not meet the aforementioned criteria of OB and DL, were included for comprehensive analysis [https://www.uniprot.org/). Humans were used as the research object, and a target protein library of key drugs was established.The TCMSP database  and OMIM database (https://omim.org/) to obtain related genes.We searched “asthma” through the Gene Cards database  was established by the Kanehisa laboratory in 1995 and is commonly used for pathway analysis and annotation in network pharmacology [Key targets were entered into the Metascape database for GO enrichment analysis, with the initial parameters defaulted. GO enrichment analysis was mainly divided into three biological aspects: biological processes, cellular components, and molecular functions. It was mainly applied to the functional classification of genes and target prediction in biology. The KEGG database , All experimental procedures complied with the International Standards of Animal Welfare and were approved by the Institute Animal Care and Use Committee of Shanghai University of Traditional Chinese Medicine . The animals were randomly divided into 4 groups(n = 6–7): Normal group (N), asthma (OVA + LPS) group (A), asthma + SZYQD low dose group (A + SL) and asthma + SZYQD high dose (A + SH). On days 0, 7 and 14, the A, A + SL and A + SH groups were sensitized via intraperitoneal (i.p.) injection of 100 µg of OVA  complexed with alum. On days 0, and 7, the A, A + SL and A + SH groups were sensitized via intraperitoneal (i.p.) injection of 1 µg of LPS . On days 15, 17, 19, 22, 23, and 24, the A, A + SL and A + SH group were intranasally administered 50 µL of OVA and 1 µg of LPS. Between days 15 and 24, the A + SL and A + SH group was intragastrically (i.g.) administered SZYQD (15 g/ kg and 45 g/kg) [The lung tissue specimens were fixed in a formalin solution and subsequently underwent paraffin embedding. Slices were obtained from the embedded tissue and subjected to staining with HE solution. The resulting images were captured using a microscope . The evaluation of inflammation was conducted based on the degree of infiltration of inflammatory cells surrounding the airway. A scoring system was employed to quantify the severity of inflammation observed, with the following criteria: no inflammation (0 points), less (1); more (2 points) circles (2), inflammatory cell ring (3), and large infiltration of inflammatory cells (4).Molecular docking was performed using AutoDockTools 1.5.6. The core compound structure file (mol2) was downloaded from the TCMSP database and then converted to a 3D structure using ChemOffice software to minimize the structure energy. AutoDockTools 1.5.6 software was used to hydrogen bond the 3D structure and saved as a pdbqt file. Target proteins were obtained from the PDB and imported into PyMOL software for dehydration and ligand isolation. The prepared compounds and target files were opened in AutoDockTools 1.5.6 for the active site of each target protein using the Genetic Algorithm algorithm . PyMOL wTraditional Chinese herbs were purchased from Shanghai Hua Yu Machinery Co., Shanghai, China. The SZYQD water extract is mainly made by Perilla frutescens, Semen sinapis, Semen raphani. One set of SZYQD components is listed in Table Five set of mixed herbs with water were boiled. The filtrate was collected and centrifuged. The supernatant was harvested and concentrated. The concentrated sample was filtered through a 0.22 μm microporous membrane used for in vitro study. For water extraction, directly freeze dried to a concentrated decoction to obtain lyophilized powder 27.6 g. The extraction rate was 14.15%. The powder was dissolved in water for use as water extract of SZYQD (SZYQD-W) in vitro studies.Weigh 20 mg of the SZYQD water extract and add 500 µL of extract (methanol: water = 4:1) with an internal standard concentration of 10 µg/mL. Then, add 500 µL of water with the same internal standard concentration. Vortex the mixture for 4 min, followed by sonication in an ice water bath for 1 h and incubation at 40℃ for 1 h. Centrifuge the samples at 12,000 rpm for 15 min. Carefully remove the supernatant through a 0.22 μm microporous filter. The LC-MS/MS analysis was performed using a UHPLC system . The flow rate was set at 0.4 mL/min, and the sample injection volume was set at 5 µL. The mobile phase consisted of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B). An Orbitrap Exploris 120 mass spectrometer coupled with Xcalibur software was used to acquire the MS and MS/MS data based on the IDA acquisition mode.RPMI-1640 , DMEM , BCA protein detection kit and cell lysis reagent , antibodies to p-p65, p-AKT, p-EGFR , Actin , Luteolin .2.The NCI-H292 human lung airway epithelial cells was provide by The Cell Bank of Type Culture Collection of Chinese Academy of Sciences  and MH-S mouse macrophages was provided by Shanghai Zhong Qiao Xin Zhou Biotechnology Company . The H292 airway epithelial cells were cultured in RPMI-1640 medium and murine alveolar macrophages (MH-S) were cultured in DMEM at 37 ℃ containing 5% COTotal RNA was extracted by an EZB kit and reverse transcribed into cDNA. qPCR primers are listed in Table M-HS cells were treated with LPS for 24 h, and IL-6 in cell culture supernatants was determined using a mouse IL-6 ELISA kit (ABclone) according to the manufacturer’s instructions.Cells were lysed with RIPA buffer. The proteins were separated by sodium dodecyl sulfate‒polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride membranes (PVDF). The membrane was blocked with 5% milk at room temperature for 2 h. Membranes were cropped along with the molecular weight marker to separate the target regions, and the primary antibodies p-P65, p-AKT, and p-EGFR were added to incubate the membrane overnight at 4 ℃, respectively. The membrane was then washed with TBST three times followed by incubation with anti-rabbit IgG horseradish peroxidase secondary antibody  for 2 h at room temperature. Finally, immunoreactive bands were visualized with ECL reagent.SPSS 22.0 software and GraphPad Prism 8.0 were used to analyse the data. The results are expressed in the form of average standard deviation. T test, one-way analysis of variance, or two-way analysis of variance were used. A statistically significant difference was defined as p < 0.05.The flowchart of the study design is illustrated in Fig. A total of 7547 genes were obtained by retrieving the Gene Cards and OMIM databases, including 1913 genes with relevance scores greater than 0.804, which were integrated and deduplicated with drug targets, and 111 HUB target proteins were finally obtained Fig. A. The STTo explore the functional distribution of SZYQD in asthma, 111 key targets were input into the Metascape database for GO enrichment analysis and KEGG pathway analysis. After analysis of the KEGG database, 5107 biological processes, 408 cellular components, and 811 molecular functions were found to be associated with the anti-asthmatic effect of SZYQD, involving 273 pathways. KEGG enrichment analysis was performed on 111 key targets, and 463 results were obtained, among which the first 20 significant items were selected . In light of this finding, an OVA + LPS asthmatic model was established to further investigate the therapeutic potential of SZYQD Fig. A. In thiIn order to gain deeper insights into the underlying mechanisms of SZYQD in its anti-asthmatic effects, we selected IL-6, AKT, and RELA  for further validation. These specific targets were chosen based on the results obtained from network pharmacology analysis and their association with inflammation and mucus overproduction. We observed a significant increase in the relative levels of IL-6 mRNA in group A compared to group N, indicating an upregulation of IL-6 in asthma. However, following treatment with high doses of SZYQD, the expression of IL-6 was downregulated Fig. E. FurtheTo investigate whether SZYQD exerted its effects through the aforementioned signaling pathways, in vitro experiments were conducted. We used LPS to stimulate IL-6 production and NF-κB activation in M-HS cells. Our results showed that compared with the control group, the expression of IL-6 in the LPS stimulation group was significantly increased, and the level of IL-6 decreased in a dose-dependent manner after intervention with different concentrations of SZYQD water extract Fig. A-B. FurtOur in vivo results showed that the AKT pathway was related to the anti-asthmatic effect of SZYQD. It has been reported that the secretion of EGF increases in asthma and EGF can induce the activation of the EGFR-AKT signalling pathway. We then observed the regulatory effects of the SZYQD extract on activation of the EGFR-AKT signalling pathway induced by EGF. The results showed that compared with the blank group, protein expression of p-AKT and p-EGFR was upregulated; in contrast, protein expression of p-AKT and p-EGFR was significantly downregulated after treatment with SZYQD extract Fig. E-F. A prActive ingredient analysis found that luteolin was the core component of SZYQD Fig. E. The SZSZYQD is a common prescription for the treatment of asthma. However, there are few studies demonstrating the active components and mechanism of SZYQD in the treatment of asthma. In this study, the “SZYQD target-asthma” network was established through network pharmacology, and on the basis of pharmacological analysis, the related effective components and potential mechanism of SZYQD in the treatment of asthma were discussed. Our in vivo and in vitro experiments showed that SZYQD and its main active component luteolin play a therapeutic role in relieving asthma symptoms by reducing inflammation and mucus overproduction, which was associated with decreased IL-6 and MUC5AC expression.Using OB and DL as the screening conditions, 28 effective active compounds were obtained from the TCMSP database and literature reports, including 5 from Semen raphani, 19 from Perilla frutescens, and 4 from Semen sinapis. It can be preliminarily predicted from the GO enrichment results that the targets of SZYQD for the treatment of asthma mainly involve the biological functions of positive regulation of protein phosphorylation, response to lipopolysaccharide, inflammatory response, asymmetric synapse, cytoplasmic side of membrane, metalloendopeptidase activity, electron transfer activity, and chromatin DNA binding etc. KEGG analysis indicated that SZYQD was predicted to treat asthma by regulating multiple pathways, including Lipid and atherosclerosis signalling pathway, PI3K-Akt signalling pathway, Kaposi sarcoma-associated herpesvirus infection signalling pathway, antiviral infection (hepatitis B) signalling pathway, Human cytomegalovirus infection signalling pathway, AGE-RAGE signalling pathway, Cancer pathway. Core target analysis showed that SZYQD may directly or indirectly affect asthma through potential targets, such as AKT, IL-6, TNF-α, and EGFR , IL-6 level in patients with active asthma was higher than that in healthy subjects and patients with stable asthma . Some stLuteolin is a typical flavonoid that has high oral availability and drug-like properties and is the main source of the core target of SZYQD. Luteolin has anti-inflammatory, anti-allergic, and immune enhancement functions. Some studies have shown that luteolin decreases the expression of IL-4, IL-5 and IL-13 in the bronchoalveolar lavage fluid (BALF) of asthmatic models. It can reduce inflammation and autophagy in lung tissue . Other sOur results show that SZYQD and its key compound luteolin can relieve asthma symptoms through the mechanisms predicted by network pharmacology, such as reducing overexpression of IL-6 and MUC5AC, inhibiting activation of the EGFR-AKT pathway and NF-κB pathway to inhibit inflammation and mucus overproduction. These findings provide a new reference for the clinical application of SZYQD.Below is the link to the electronic supplementary material.Supplementary Material 1: A UHPLC-QE-MS analysis was used for SZYQD water extract to detect the presence of luteolinSupplementary Material 2: Raw data for WB dataSupplementary Material 3: Data for Table


Solanum nigrum L. However, its efficacy in the treatment of gliomas and the underlying mechanisms remain unclear. The aim of this study was to investigate the inhibitory effects of α-solanine on glioma and elucidate its mechanisms and targets using network pharmacology, molecular docking, and molecular biology experiments.An anti-tumour activity has been demonstrated for α-solanine, a bioactive compound extracted from the traditional Chinese herb Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to predict the potential targets of α-solanine. GeneCards was used to gather glioma-related targets, and the STRING online database was used to analyze protein–protein interaction (PPI) networks for the shared targets. Hub genes were identified from the resulting PPI network and further investigated using Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Additionally, prognostic and gene set enrichment analyses (GSEA) were carried out to identify potential therapeutic targets and their underlying mechanisms of action in relation to the prognosis of gliomas. In vitro experiments were conducted to verify the findings from the network pharmacology analysis.A total of 289 α-solanine targets and 1149 glioma-related targets were screened, of which 78 were common targets. 11 hub genes were obtained, including SRC, HRAS, HSP90AA1, IGF1, MAPK1, MAPK14, KDR, STAT1, JAK2, MAP2K1, and IGF1R. The GO and KEGG pathway analyses unveiled that α-solanine was strongly associated with several signaling pathways, including positive regulation of MAP kinase activity and PI3K-Akt. Moreover, α-solanine (10 µM and 15 µM) inhibited the proliferation and migration but promoted the apoptosis of glioma cells. Finally, STAT1 was identified as a potential mediator of the effect of α-solanine on glioma prognosis.α-Solanine can inhibit the proliferation and migration of gliomas by regulating multiple targets and signalling pathways. These findings lay the foundation for the creation of innovative clinical anti-glioma agents.The online version contains supplementary material available at 10.1186/s12906-023-04215-1. Glioma, a primary tumor most frequently in the central nervous system (CNS), has become a significant global public health concern owing to its high mortality rate . AlthougSolanum nigrum L. (Longkui), a kind of traditional Chinese medicine (TCM), as well as several edible plants such as potatoes, cherries, and tomatoes [α-Solanine is a glycoalkaloid that occurs naturally and is synthesized by different plants, including tomatoes . Numeroutomatoes , 5. It htomatoes . AlthougNetwork pharmacology is a rapidly evolving field of research that aims to unravel the intricacies of disease and drug mechanisms within complex biological networks . This aphttp://tcmspw.com/). To obtain genes related to glioma, we used the GeneCards database (https://www.genecards.org) and searched for the keyword "glioma".To identify genes targeted by α-solanine in glioma, we conducted a keyword search for "α-solanine" using the TCMSP  to obtain information on their protein–protein interaction (PPI) network [The intersection targets were integrated into the STRING database , betweenness centrality (BC), closeness centrality (CC), and average shortest path length (ASPL), which facilitate in-depth analysis of the characteristics of nodes in an interaction network . In thishttps://DAVID.ncifcrf.gov) [https://www.bioinformatics.com.cn).Gene Ontology (GO) enrichment analysis is a common method for identifying biological processes, molecular functions, and cellular components. Meanwhile, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis can reveal significant signalling pathways associated with biological processes. In this study, we conducted GO and KEGG enrichment analyses of the hub targets identified using the DAVID database (crf.gov) . The reshttp://cao.labshare.cn/cb-dock/), a recently developed blind docking technology that can autonomously identify the sites for binding to a specific protein and conduct molecular docking using AutoDock [http://www.rcsb.org). For the ligand, the 3D structure of α-solanine was retrieved from the PubChem Compound database (https://www.ncbi.nlm.nih.gov). The protein (receptor) and α-solanine (ligand) files were then submitted to the CB-Dock website for molecular docking analysis.The application of molecular docking has become essential in computational drug design . In the AutoDock . CB-DockAutoDock . The cryhttp://gepia.cancer-pku.cn) to screen for potential therapeutic targets relevant to the prognosis of glioma patients [To reveal the prognostic value of α-solanine in individuals with glioma, we conducted survival analysis on its hub targets. The hub targets were entered into the GEPIA database  below 0.25 were deemed to be of statistical significance [To investigate the mechanisms associated with the differential expression of therapeutic targets in glioma and gain insight into how α-solanine affects the glioma prognosis, we used GSEA software (version 3.0) to examine the biological functions related to the differences in the expression of therapeutic targets between normal and glioma tissues. The reference gene sets were based on the c2 sets of the Molecular Signatures Database , and the permutation number was set at 1,000. The gene sets enriched through GSEA with a nominal ificance .The human glioma-derived U87MG cell line, a typical grade IV glioma cell line, was purchased from Wuhan Pu-nuo-sai Life Technology Co. Ltd. in Wuhan, China. This particular cell line is renowned for its vigorous proliferation and tumorigenic properties . The celStock solutions of α-solanine (1 mmol/l) were prepared in dimethyl sulfoxide (DMSO) and diluted with double-distilled water containing 10% DMSO to obtain various concentrations. To investigate the effects of α-solanine on U87MG cells, three different concentrations of the compound  were applied to the cells for a period of 24 h. The resulting morphological changes in the cells were then analyzed using a light microscope .3 cells per well and subjected to treatment with α-solanine at varying concentrations of 5 µM, 10 µM and 15 µM for 24 h. The Cell Counting Kit-8 (CCK-8) assay was performed to measure cell proliferation, with absorbance measurements recorded at a wavelength of 450 nm. GraphPad Prism 7.0 software was then used for data analysis and plotting.To evaluate the impact of α-solanine on cell viability, U87MG cells were cultured in 96-well plates at a density of 4 × 105 cells per well, allowing them to form a monolayer. To create a wound, three lines were drawn vertically in each well using a sterile pipette aspirator. The cells were then treated with a drug-free medium (serum-free) or a drug-containing medium (serum-free with 10 µM or 15 µM α-solanine) for 24 h. Following treatment, the cells were imaged using a light microscope , and the distance between the markers on the cells was measured at both 0 and 24 h. The relative migration distance was calculated using the formula: Relative migration distance (mm) = distance within the scratch at 0 h—distance within the scratch at 24 h. Each experiment was performed in triplicate.U87MG cells were cultured in 6-well plates at a density of 3 × 10U87MG cells were subjected to treatment with α-solanine at concentrations of 10 and 15μΜ for 48 h after being cultured in 6-well plates at 37 °C. To determine the extent of apoptosis, the Annexin V-FITC early apoptosis kit  and a flow cytometer  were used. After washing the treated cells with cold phosphate-buffered saline, they were resuspended in 400 μL of 1 × binding buffer, and 5 μL annexin V-FITC and 5 μL PI staining solution were added. After incubation in the dark, flow cytometry analysis was performed within one hour.−ΔΔCt method. The primer sequences used for qPCR analysis are listed in Additional file The RNA Easy Fast Cell Kit  was used to extract total RNA from U87MG cells according to the manufacturer's instructions. The quality of the RNA was evaluated using a SpectraMax Quick Drop reader . Reverse transcription was performed using the iScript cDNA synthesis kit (Bio-Rad) on 1 μg of RNA. RT-qPCR was conducted using SYBR Green Real-Time PCR Master Mix  to measure the mRNA expression levels of four genes: STAT1, P53, BAX, and BCL-2. The β-actin gene served as the internal control, and the expression of each gene was calculated using the 2P < 0.05) or two asterisks (**: P < 0.01).Continuous data that followed a normal distribution were represented as the mean value ± the standard deviation (SD). GraphPad Prism 7.0 software was used for conducting statistical analysis, and the two-tailed unpaired Student's t-test was used to determine differences between the groups. Statistical significance was indicated by an asterisk  and disease-free survival (DFS) of glioma patients Fig. a-c.Fig. To better understand how α-solanine exerts its therapeutic effects through the hub target STAT1 and improves the prognosis of glioma patients, we conducted a GSEA analysis to identify potential biological signalling pathways affected by the overexpression of STAT1 in glioma. As depicted in Fig. In order to investigate the effects of α-solanine on glioma cell proliferation, U87MG cells were treated with various concentrations of α-solanine. The morphology of cells was examined using an optical microscope. It was observed that α-solanine had no significant effect on the viability of U87MG cells when administered at a concentration of 5 µM  is a widely used traditional Chinese medicinal herb with anticancer properties. Its main steroidal glycoalkaloid, α-solanine, is highly effective against various types of cancer in all three stages: carcinogenesis, growth, and metastasis [Traditional Chinese Medicine (TCM) has a long history of application in treating various diseases and is now considered a complementary or alternative approach to conventional medicine . In conttastasis , 30, 31.The present study employed a systematic approach to identify potential target genes for α-solanine treatment of glioma based on relevant databases and Venn diagrams. Subsequently, 78 candidate genes were identified, and their interactions were visualized using protein–protein interaction (PPI) analysis. Through further network analysis using Cytoscape,11 hub target genes, including SRC, HRAS, HSP90AA1,IGF1, MAPK1, MAPK14, KDR, STAT1, JAK2, MAP2K1, and IGF1R, were selected for subsequent investigation. Molecular docking analysis was performed to determine whether α-solanine binds with the hub targets. The results revealed that α-solanine exhibited high binding affinity with the 11 core target genes, suggesting its potential as a therapeutic agent for glioma.SRCs are critical members of the SRC family of protein tyrosine kinases and play a crucial role in various cellular processes, including morphology, motility, proliferation, and survival . InhibitThe GO analysis revealed that α-solanine participates in several critical biological processes in glioma, including the regulation of reactive oxygen species (ROS) response, mitogen-activated protein (MAP) kinase activity, and phosphatidylinositol 3-kinase (PI3K) signalling, among others. ROS plays a crucial role in inducing apoptosis of tumour cells, and various medicinal plants have been found to increase ROS levels to induce cancer cell apoptosis , 43. MorThe KEGG pathway analysis suggested that α-solanine inhibits the proliferation of glioma through several pathways, such as the Ras signalling pathway, PD-L1 expression and the PD-1 checkpoint pathway, the PI3K-Akt signalling pathway, MAPK signalling pathways, and VEGF signalling pathways. The Ras signalling pathway is an essential component of cellular signalling pathways and plays a crucial role in oncogenic signalling . The PD-STAT1, as a transcription factor, plays a significant role in cytokine-mediated signalling pathways that have a range of biological effects such as antiviral activities, suppression of tumour cell growth, and promotion of apoptosis . AlthougDespite the well-established knowledge of solanine's inhibitory effects on multiple signaling pathways such as NF-κB, ERK1/2, AKT and STAT1, its precise effect on gliomas through STAT1 remains uncertain . AccordiIn recent years, network pharmacology, which combines principles from systems and computational biology, has emerged as a valuable research tool for investigating the network regulatory effects of TCM or formulas in the context of various diseases . Moleculα-Solanine is a promising and safe TCM for the treatment of glioma. Our network pharmacological analysis revealed that α-solanine exerts an anti-glioma effect by modulating the expression or activity of multiple targets, pathways and biological processes crucial for cellular metabolism and apoptosis. Specifically, α-solanine improves the glioma prognosis by down-regulating the expression of STAT1. Further exploration of the potential benefits of α-solanine glioma treatment is warranted to validate our findings.Additional file 1: Table S1. PCR primers and their sequences used in this study.Additional file 2: Table S2. Targets of disease and drug action and their intersection.Additional file 3. The attribute values of 78 common targets.Additional file 4: Figure S1. The key amino acid residues of STAT1interact with α-solanine. Blue dashed lines represent hydrogen bonds, gray dashed lines represent hydrophobic interactions, and yellow dashed lines represent salt bridges.


Background: Osteoporosis is a prevalent bone metabolism disease characterized by a reduction in bone density, leading to several complications that significantly affect patients’ quality of life. The Achyranthes bidentata–Dipsacus asper (AB–DA) herb pair is commonly used in Traditional Chinese Medicine (TCM) to treat osteoporosis. This study aimed to investigate the therapeutic compounds and potential mechanisms of AB–DA using network pharmacology, molecular docking, molecular dynamics simulation, and experimental verification.Methods: Identified compounds of AB–DA were collected from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicine Information Database (TCM-ID), TCM@Taiwan Database, BATMAN-TCM, and relevant literature. The main bioactive ingredients were screened based on the criteria of “OB  ≥ 30, DL (drug-likeness) ≥ 0.18.” Potential targets were predicted using the PharmMapper and SwissTargetPrediction websites, while disease (osteoporosis)-related targets were obtained from the GeneCards, DisGeNET, and OMIM databases. The PPI network and KEGG/GO enrichment analysis were utilized for core targets and pathway screening in the STRING and Metascape databases, respectively. A drug–compound–target–pathway–disease network was constructed using Cytoscape software to display core regulatory mechanisms. Molecular docking and dynamics simulation techniques explored the binding reliability and stability between core compounds and targets. In vitro and in vivo validation experiments were utilized to explore the anti-osteoporosis efficiency and mechanism of sitogluside.Results: A total of 31 compounds with 83 potential targets for AB–DA against osteoporosis were obtained. The PPI analysis revealed several hub targets, including AKT1, CASP3, EGFR, IGF1, MAPK1, MAPK8, and MAPK14. GO/KEGG analysis indicated that the MAPK cascade (ERK/JNK/p38) is the main pathway involved in treating osteoporosis. The D–C–T–P–T network demonstrated therapeutic compounds that mainly consisted of iridoids, steroids, and flavonoids, such as sitogluside, loganic acid, and β-ecdysterone. Molecular docking and dynamics simulation analyses confirmed strong binding affinity and stability between core compounds and targets. Additionally, the validation experiments showed preliminary evidence of antiosteoporosis effects.Conclusion: This study identified iridoids, steroids, and flavonoids as the main therapeutic compounds of AB–DA in treating osteoporosis. The underlying mechanisms may involve targeting core MAPK cascade (ERK/JNK/p38) targets, such as MAPK1, MAPK8, and MAPK14. In vivo experiments preliminarily validated the anti-osteoporosis effect of sitogluside. Further in-depth experimental studies are required to validate the therapeutic value of AB–DA for treating osteoporosis in clinical practice. Osteoporosis is a prevalent bone metabolism disease that affects over 200 million people worldwide . It is cAnti-osteoporosis drugs such as estrogen, raloxifene, bisphosphonates, calcitonin, and parathyroid hormone (PTH) are commonly used in clinical practice . These mTraditional Chinese Medicine (TCM) has a rich history and has been widely used in Asia to treat various diseases, including osteoporosis . TCM is Achyranthes bidentata (AB), also known as Niu Xi, is included in the Chinese, Japanese, and Korean pharmacopoeia (Dipsacus asper (DA), also known in Chinese as Xu Duan —meaning “to rebuild fractures and unite bones”—is discussed in Shennong’s Classic of Material Medicine, which is the earliest source  Database (http://lsp.nwu.edu.cn/tcmsp.php) (http://bionet.ncpsb.org.cn/), Traditional Chinese Medicine Information Database (http://bidd.group), and relevant literature were utilized to acquire all identified AB–DA compounds. ADME  properties were applied to screen bioactive ingredients, and the screening criteria were set as “oral bioavailability (OB)≥ 30, drug-likeness (DL)≥ 0.18” (http://www.swissadme.ch).The TCM@Taiwan  , BATMAN-msp.php)  (a bioinDatabase  (TCM-ID )≥ 0.18”  to scree)≥ 0.18”  databasehttp://www.swisstargetprediction.ch/) and PharmMapper databases (http://www.lilab-ecust.cn/pharmmapper/). The UniProt ID of the target was converted into a standardized gene name using the UniProt database (https://www.uniprot.org). The keyword “osteoporosis” was searched in the GeneCards (https://www.genecards.org/), DisGeNET (https://www.disgenet.org), and Online Mendelian Inheritance in Man (https://omim.org) databases to obtain relevant targets. Then, the overlapping targets identified by Venn diagram were considered as targets of AB–DA for the treatment of osteoporosis after merging and removing duplicates.To predict potential targets based on their spatial configuration, the compounds generated in the previous step were imported into the SwissTargetPrediction   database, with a focus on the anti-osteoporosis efficacy of AB–DA in Homo sapiens and an interaction score threshold of 0.4. Topological analysis was performed, and the core targets of AB–DA for treating osteoporosis were accurately selected by using the Cytoscape plug-ins MCODE (molecular complex detection) and CytoHubba  network was established in the STRING  (http://ytoHubba .http://www.metascape.org/), the cut-off p-value, minimum overlap value, and concentration value were set to 0.01, 3, and 1.5, respectively (http://www.bioinformatics.com.cn/). Comprehensive information on the most significantly enriched pathway was then extracted and colored (https://cytoscape.org/) to present the complicated network of the AB–DA herb pair in the treatment of osteoporosis.Analysis of Gene Ontology (GO) functions, including cellular component (CC), molecular function (MF), and biological process (BP), and Kyoto Encyclopedia of Genome and Genome (KEGG) pathway enrichment analysis, was utilized to clarify the key anti-osteoporosis mechanism of the AB–DA herb pair. When entering the targets into the Metascape database  is an online molecular docking (MD) tool to determine the binding affinity from each binding site between small molecule ligands and receptor proteins. The X-ray diffraction of the protein crystal structure of key targets were downloaded from the Protein Data Bank (PDB) database (www.rcsb.org) (https://www.3ds.com) was used to visualize the binding details (The SwissDock platform  (http://csb.org) . The bin details .To investigate the stability of the complexes between small-molecule ligands and proteins, molecular dynamics simulations (MDS) were performed using the Standard Dynamics Cascade subunit of the Discovery Studio 2019 software. The ligand–protein complex with the lowest binding affinity score according to molecular docking analysis was selected . In thisSitogluside, identified as one of the most promising bioactive compounds in the AB–DA herb pair, was further investigated for its anti-osteoporotic effects and associated mechanisms. Sitogluside was procured from the Dalian Meilunbio company and solubilized in dimethyl sulfoxide (DMSO). Human fetal osteoblast (hFOB) cells were obtained from the American Type Culture Collection (ATCC) and cultured in six-well plates using Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum , 1% penicillin–streptomycin (P/S), and 0.3 mg/mL Geneticin (G418). The JNK-specific inhibitor (SP600125) and p38-specific inhibitor (SB203580) were acquired from Absin (Shanghai). The cells were maintained in a humidified sterile atmosphere at 34 °C. They were subsequently treated with sitogluside when they reached a confluence of 60%–80% per well.4 cells/well in 24-well plates and grown for 14 days in osteogenic media (DMEM +10% FBS +1% P/S +100 M ascorbic acid +2 mM 2-glycerophosphate +10 nM dexamethasone). The stained culture plates were photographed using a microscope  and quantified using ImageJ software . In addition, a 2% ARS reagent (Beyotime Institute of Biotechnology) was used to detect matrix mineralization, with the same protocol as ALP assay except the dye. In addition, we also investigated the effect of sitogluside on the osteoclast to fully illustrate the anti-OP effects. The RAW264.7 (osteoclast precursor) cells were treated with a different concentration of sitogluside and supplemented with 50 ng/mL receptor activator of NF-κB ligand (RANKL) as an osteoclast formation stimulator. Cells were then fixed in paraformaldehyde and stained with tartrate-resistant acid phosphatase (TRAP) after the intervention.For alkaline phosphatase (ALP) activity analysis, the BCIP/NBT Alkaline Phosphatase color development kit  was used according to the manufacturer’s procedure. Briefly, osteoblast precursor cells were seeded at 3 × 10This study received ethical approval from the Animal Care Committee of the Second Xiangya Hospital of Central South University. A total of 30 10-week-old female C57BL/6 mice were procured from SLAC Laboratory Animal Co. Ltd. . They were acclimatized in specific pathogen-free (SPF) cages for 1 week, during which measures were taken to minimize animal suffering through the use of anesthesia and sterile techniques during the surgical procedures. Bilateral ovariectomy (OVX) or sham surgery  was performed based on group assignment, as described in the following paragraph.n = 10), vehicle group , and sitogluside group .Following the surgical procedures, the mice were randomly assigned to one of three groups: sham group  for 48 h. High-resolution micro-computed tomography  was employed for bone analysis at the following parameters: scanning voltage = 80 kV, electric current = 80 μA, and resolution = 10 μm. The relevant trabecular bone volume fractions (BV/TV), trabecular number (Tb. N), trabecular thickness (Tb. Th), and trabecular separation (Tb. Sp) were subsequently calculated to assess the protective efficacy of sitogluside in OVX mice. In addition, to investigate the biosafety of sitogluside in the OVX model, the main organs were also obtained and detected using hematoxylin-eosin (H&E) staining. The heart, liver, spleen, lung, and kidney were hence fixed with formalin and embedded in paraffin cut to a 4 μm section. They were dewaxed in xylene, rehydrated with concentration gradient ethanol, and then stained with H&E for histological examinations and morphometric analysis. The serum of the mice was also collected to examine the biomarkers of alanine aminotransferase (ALT), creatine kinase (CK), and blood urea nitrogen (BUN).−ΔΔCT method was employed for further analysis of RNA expression. In addition, to determine the modulated effect of sitogluside with JNK and osteogenic genes, the knockdown and activation of JNK expression were applied. ShRNA (shGnai3) was thus used to downregulate the expression level of JNK, and ASM was used as an activator to increase the p-JNK level (Human osteoblast (hFOB) cells were treated with 40 μM sitogluside or combined with the specific inhibitor of JNK and p38, depending on the groups, with ascorbic acid added in the osteogenic media. The cells were then harvested using the RNeasy Mini kit  to extract total RNA following the manufacturer’s protocol. Subsequently, cDNA synthesis was performed using the reverse transcriptase kit . Real-time PCR analysis was performed using the SYBR Premix Ex Taq kit . The PCR parameters were set as follows: 40 cycles (denaturation at 95 °C for 10 s and amplification at 60 °C for 30 s). The resultant data were recorded as cycle threshold (Ct) values, and the 2NK level . The altThe hFOB cells were harvested by trypsin and then lysed in RIPA for 30 min on ice. Cell lysates were centrifuged at 12,000 g for 15 min at 4 C; the supernatant was collected, and protein content was quantified via the BSA protein assay kit following the manufacturer’s instruction. Proteins were separated by electrophoresis on 10%–12% SDS-PAGE at 100 V for 1.5 h and transferred onto a 0.45 μm polyvinylidene difluoride (PVDF) membrane at 250 mA for 1 h. The PVDF membrane was blocked with 5% non-fat milk in TBST buffer for 1 h at room temperature and incubated with primary antibody at 4 °C overnight. They were then incubated with secondary antibody for 1 h at room temperature and detected using the Chemiluminescence Kit.p-value of less than 0.05.Statistical analyses were conducted using GraphPad Prism 8.0.2 software . The data are presented as means ± standard deviation (SD). Data comparisons were performed using one-way analysis of variance (ANOVA), and statistical significance was determined by a According to TCM databases, 185 components of AB and 82 compounds of DA were obtained in this work . After fAfter merging and duplicating results, 413 potential targets associated with 31 bioactive compounds were obtained, and 827 relevant targets of osteoporosis were acquired. Some 83 overlapped genes on Venn between AB–DA ingredients and osteoporosis were regarded as potential therapeutic targets .A total of 83 targets of AB–DA against osteoporosis were imported to the STRING database; after deleting the disconnect targets, a PPI network with 78 nodes and 702 edges was constructed. Cytoscape software was utilized for further visualization, and plug-ins of MCODE and CytoHubba based on the topological parameters were applied to screen the hub genes, including AKT1, IGF1, CASP3, MMP9, EGFR, PPARG, ESR1, MAPK1, MAPK8, and MAPK14 .p < 0.01, adjusted q < 0.05) , 29 cellular components (CC), and 74 molecular functions (MF) items  activity and mineralization in osteoblasts, we conducted ALP activity and ARS experiments. As illustrated in in vivo. As depicted in The OVX model was employed to further investigate the anti-osteoporotic effects of sitogluside To gain further insights into the underlying mechanism of sitogluside’s anti-osteoporotic effects, we examined the expression of osteogenic-related genes using q-PCR and Western blot. As shown in in vivo and in vitro   regulates a series of biological processes, including cell proliferation, growth, metabolism, and angiogenesis . A targest cell) , exhibitst cell) . The resThe GO/KEGG pathway enrichment analysis of 83 potential therapeutic targets showed that AB–DA anti-osteoporosis mainly involved the MAPK signaling pathway, osteoclast differentiation, and the PI3K-Akt signaling pathway. As shown in in vitro and in vivo experimental validation were both employed to explore the anti-osteoporotic effects of sitogluside  and its underlying molecular mechanism. Some research has indicated the regulation of both the osteoblast and osteoclast formation of AB–DA . Furthermore,


To explore the mechanism of Zhenwu Decoction (ZWD) in the treatment of heart failure (HF) by network pharmacology analysis, so as to provide a basis for the innovation and application of drugs. The effective components and targets of 5 Chinese herbal medicines in ZWD were retrieved by TCM Pharmacology Database and Analysis Platform (TCMSP).Gene card, OMIM and TTD databases were used to obtain the disease targets of HF, and the intersection with the targets of ZWD was obtained. We used Cytoscape3.9.1 software to construct a drug-active component-disease-target interaction network for ZWD treatment of HF, and performed protein-protein interaction (PPI) network and topology analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed. Fifty-nine effective components and 229 targets of ZWD were screened. Among them, ZWD for HF has 27 active components and 38 common targets, and the core targets of PPI are IL-6, ATK1 and TNF. Pathway enrichment analysis included lipid and atherosclerotic and TNF signaling pathways. This study preliminarily clarified the main active components, targets and related pathways of ZWD in the treatment of HF, and laid a foundation for further study of the pharmacological effects of ZWD. HF is a disease characterized by high morbidity and mortality, poor social capacity and quality of life, and high costs of treatment and prevention. HF affects more than 64 million people worldwide. One of the major issues in global public health today includes efforts to reduce the social and economic burden of HF. According to the statistics of China Research Association in 2019, the mortality rate of cardiovascular diseases in rural and urban areas accounted for 46.74% and 44.26% of all deaths. It is estimated that there are about 330 million patients with different degrees of cardiovascular disease in China, of which about 8.9 million are HF. At the same time, China is facing the dual pressure of population aging and the steady rise in the prevalence of metabolic risk factors. In the face of the increasing burden caused by cardiovascular diseases, new challenges have emerged in the prevention and treatment of cardiovascular diseases and the allocation of medical resources in China. According to the latest epidemiological data, there are about 12.1 million HF patients among people aged 25 and above in China, and there are about 3 million new HF patients every year, which has brought considerable burden to China health system.Heart failure (HF) is a clinically prominent and common syndrome characterized by structural and/or functional abnormalities of the heart, resulting in increased intracardiac pressure and inadequate cardiac output. The common causes of HF are cardiac systolic dysfunction and relaxation. Zhang Dysfunction Heart failure can also be caused by pathological changes in the heart valves, pericardium, and abnormal heart rhythm.,6Currently, drugs such as angiotensin-converting enzyme inhibitors (ACEI), β blockers and aldosterone receptor antagonists are used to treat heart failure, which can effectively treat heart failure and delay the progression of heart failure, but caution in patients with severe renal dysfunction. Therefore, the new treatment regimen is to replace ACEI drugs with sakubarase, whose mechanism of action is to antagonize angiotensin II receptors and neuropilin and to effectively inhibit the activation of the neuroendocrine system, as recommended by many guidelines for clinical symptoms and long-term outcomes in patients with chronic heart failure. ZWD has the effects of promoting urination, dilating blood vessels and strengthening heart, but its specific mechanism has not been clarified by special studies.The study of HF in traditional Chinese medicine has a long history. Through medium and long-term clinical evidence, the disease position of HF is the deficiency of qi, blood and Yin and Yang, the loss of the function of viscera is the essence, blood stasis, phlegm, water drinking, qi stagnation, etc, and the blood obstruction is the standard. Its treatment is mainly to warm Yang and promote diuresis, so it is often treated with Zhenwu Decoction (ZWD). ZWD comes from Treatise on Febrile and Miscellaneous Diseases by Zhang Zhongjing, an outstanding physician in the Han Dynasty. The original text is “Taiyang disease, sweating, sweating, people still have fever, palpitation, dizziness, body movement, and desire to vibrate, Zhenwu Tang governs it.” Which consists of 5 medicines of tuckahoe, white paeony root, largehead Atractylodes rhizome, ginger and aconite. ZWD has the effects of warming and activating Yang qi and promoting urination, and is mainly used to treat edema caused by heart and kidney Yang deficiency. ZWD is especially suitable for the treatment of total heart failure, acute heart failure, heart failure with reduced ejection fraction, etc.Traditional Chinese medicine (TCM) compound is a good resource for new drug development, and its clinical efficacy has been confirmed in thousands of years of clinical practice of traditional Chinese medicine, which is expected to bring benefits to patients with heart failure, but its multi-component, multi-target and multi-effect mechanism of action is a difficult problem in traditional Chinese medicine research. Network pharmacology integrates the emerging concepts and methods of systems biology, multi-directional pharmacology, computational biology and network analysis to explore the relationship between drugs and diseases from multiple levels, which has a certain degree of systematicness and integrity. Therefore, we used the TCMSP database to screen the active ingredients of ZWD and predict their targets. Under the guidance of network pharmacology, the interaction between ZWD active components and targets was analyzed, and the ZWD active component-target network and ZWD active component-target-HF target network were established. Finally, bioinformatics analysis was used to clarify the multi-target and multi-pathway mechanism of ZWD in the prevention and treatment of HF.https://old.tcmsp-e.com/tcmsp.php), 5 kinds of traditional Chinese medicines, including aconite, tuckahoe, white Atractylodes rhizome, ginger and white peony root, were retrieved in turn. The screening conditions were set as  OB ≥ 30% and  ≥ 0.18 to obtain the corresponding active ingredients of the 5 Chinese herbal medicines, and the UniProt database (https://www.uniprot.org/) was used. UniProtKB search function, the database selection is limited to “Reviewed (Swiss-Prot),” the species is “Human,” and the target is queried to obtain the target corresponding to the active ingredient of ZWD.Through the application of TCMSP database (https://ngdc.cncb.ac.cn/databasecommons/database/id/723), OMIM database (https://www.omim.org/) and https://ngdc.cncb.ac.cn/databasecommons/database/id/4948). The higher the Relevance score in the Gene cards database, the closer the relationship between the target and the disease, so the target with Relevance score ≥ 10 was taken as the target of HF disease. The key words “heart failure” or “HF” were used to search for the HF gene targets that had been confirmed and had related studies, and the duplicate and false positive genes were eliminated, which were the related gene targets of HF.HF disease target are identified and identify through that Gene card database (https://cn.string-db.org/), and the Multiple proteins tool was used. Homo sapiens is defined as a species, the highest confidence is more than 0.4, protein interaction is obtained, the free protein is hidden, and the protein is obtained. Cytoscape software draws the protein-protein interaction network, analyzes the topology of the network, and visualizes the core target data to construct the PPI network diagram. Cytoscape3.9.1 software was used to construct the drug-active ingredient-disease-target interaction network of ZWD in the treatment of HF, and based on this network, the mechanism of action of the whole ZWD compound was explored.The target of ZWD and the gene target of HF were imported into the UniProt database for standardization, and then the intersection target was screened as the potential target of ZWD for HF. The potential targets of ZWD were imported into the STRING: functional protein association networks database (https://david.ncifcrf.gov/) was used for enrichment analysis of targets for ZWD treatment of HF by Gene Ontology (GO) biological processes and metabolic pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG). The molecular mechanism of ZWD acting on HF was elucidated from 2 aspects of gene function and pathway analysis.The DAVID database (http://www.rcsb.org/), The 3D structure of the ZWD core active compound was downloaded from the Pubchem database (https://pubchem.ncbi.nlm.nih.gov/), and AutoDockTools 1.5.7 software was used to remove water molecules and ligands from the above file, and at the same time, hydrogenation and electron addition were carried out. Carry out molecular docking on that core active ingredient and the core target.The core active ingredients screened from the “Drug-Active Ingredient-Disease-Target” network were selected for molecular docking with the core targets. The 3-dimensional structures of the potential targets and the screened targets to be verified are searched and obtained through the RCSB PDB database ” and species to “Human,” 229 protein targets were obtained after correcting the names of protein targets and removing duplications. 27 core components and their corresponding 93 protein targets.https://bioinfogp.cnb.csic.es/tools/venny/index.html). 1569 disease targets were obtained by sorting and removing duplicates, as shown in Figure The Potential targets of HF were predicted in GeneCards, OMIM, TTD and other databases, and the disease targets were mapped by Venny 2.1 website  to prevent heart failure,12; Both beta-sitosterol and Stigmasterol are phytosterols, which have pharmacological activities such as antioxidant, cholesterol-lowering and anti-inflammatory, and studies have shown that they can reduce the risk of cardiovascular disease–15; Experimental studies of paeoniflorin have shown that it can reduce ventricular remodeling and improve cardiac function in rats. Based on the active components and targets retrieved, the potential biological mechanism of ZWD in the treatment of HF was discussed. We obtained 1569 HF-related targets using GeneCards, OMIM and TTD databases, and 38 intersection targets were obtained by mapping with ZWD active component targets. Animal experimental studies have found that Zwd Kezhenwu Decoction can reduce cardiomyocyte apoptosis and myocardial pathological changes in HF rats, enhance myocardial contractility in HF rats, and then delay the process of heart failure in rats. The mechanism may be achieved by inhibiting the expression of AKT1.Network pharmacology is the study of interactions among drug components, targets, and diseases from the perspective of biomolecular networks. The interaction between the active ingredients of drugs and their targets and the targets of diseases is constructed as a network model, and then the topological parameters of the nodes in the network are evaluated by software to explore the importance of the nodes in the whole network model. Based on the TCMSP database, 59 ZWD active components were obtained with OB > 30% and DL > 0.18 as screening parameters, and 27 active components were obtained after Uniprot database correction and target prediction. The results showed that the activity of Radix Aconiti Lateralis Preparata in ZWD compound was the strongest, followed by Poria cocos, Radix Paeoniae Alba, Rhizoma Atractylodis Macrocephalae and Rhizoma Zingiberis Recens; literature verification was conducted on the screened core components, and it was found that aconitine, one of the main components of Radix Aconiti Lateralis Preparata, was an adrenergic receptor agonist, which could activate adrenergic receptors and thus play a cardiotonic role Studies have found that IL6 plays a protective role in the acute response of myocardial cells, but long-term high expression of IL6 can cause decreased myocardial contractility and myocardial hypertrophy. Transient activation of AKT is associated with increased capillary density in the myocardium, and activation of AKT signaling within endothelial cells is sufficient to promote angiogenesis within the myocardium, thereby improving cardiac perfusion. GO functional enrichment analysis of the screened core targets showed that, It involves many biological processes such as endoplasmic reticulum membrane, extracellular space, cell surface, membrane rafts, response to hydrogen peroxide, positive regulation of peptidyl-serine phosphorylation, response to lipopolysaccharide, positive regulation of smooth muscle cell proliferation, response to hypoxia, sequence-specific DNA binding, zinc ion binding, heme binding, enzyme binding and protein binding. Cell composition and molecular function. The main signaling pathways for ZWD treatment of HF include lipid and atherosclerosis, age − RAGE signaling pathway in diabetic complications, TNF signaling pathway, fluid shear stress and atherosclerosis, The interleukin-17 signaling pathway and the hypoxia-inducible factor-1 signaling pathway. Atherosclerosis is the main cause of cardiovascular diseases such as coronary heart disease, heart failure and stroke, and abnormal lipid metabolism, oxidative stress and inflammation are the main characteristics of atherosclerosis; Tumor necrosis factor (TNF) is a major mediator of apoptosis, inflammation and humoral immune system, which may be related to the pathogenesis of cardiovascular and cerebrovascular diseases. Many related experiments have shown that the expression level of RAGE in AGE-RAGE cells is usually low. However, when the patient body is in inflammation, trauma, diabetes and other pathological conditions, RAGE may suddenly appear abnormal high level of expression, which will activate NF-κB and other transcription factors, make their expression exceed the normal level, trigger inflammatory toxic reaction, and eventually cause immune tissue dysfunction and structural damage,23; The inflammatory response mediated by the il − 17 and HIF − 1 signaling pathways is an important mechanism for the occurrence of cardiovascular events, and its degree of activation is highly related to the HF process; shear stress represents the frictional force exerted by blood flow on the endothelial surface of the vascular wall, plays a central role in vascular biology, and contributes to the development of atherosclerosis. It can be seen that Zhenwu Decoction can achieve the purpose of treating HF by regulating the role of the above pathways.Through the construction of PPI network, it is found that there is a close and complex relationship between the target proteins. Through the topological analysis of the targets of PPI network, the target proteins of IL6, AKT1 and TNF may be the core targets of ZWD in the treatment of HF. Interleukin (IL-6) and tumor necrosis factor-α (TNF-α) are closely related to the pathogenesis of heart failure. IL-6 and TNF-α can inhibit the contractile function of cardiomyocytes, induce inflammatory activation of macrophages, and stimulate microvascular inflammation and dysfunction. At the same time, IL-6 can promote chronic myocardial fibrosis, which is the pathogenesis of heart failure with preserved ejection fraction.. Using molecular docking technology, the binding energy-5.0 kcal/ mol between ligand small molecule and receptor protein, each binding site is formed by stable hydrophobic and hydrogen bonds, where IL 6, AKT 1, TNF and kaempferol and β-sitosterol binding are all relatively stable. The molecular docking results further verified the accuracy of the screened ZWD treatment core network for HF.Molecular docking evaluates the intermolecular interactions by evaluating the binding energy of small molecules and protein ligands in the network, thus improving the accuracy of the networkThe underlying biological mechanisms of ZWD for HF are characterized by multi-omics, multi-targets, and multi-pathways.IL6, AKT1, and TNF may be the core disease targets of ZWD for HF. It may be related to lipid and atherosclerosis, age − RAGE signaling pathway in diabetic complications, TNF signaling pathway, fluid shear stress and atherosclerosis, interleukin-17 signaling pathway, and hypoxia-inducible factor-1 signaling pathway. In this study, network pharmacology was used to study the mechanism of drug action of ZWD holistically and systematically, which provided a basis for further promotion and application of ZWD. Of course, this study may have some limitations in exploring the active ingredients and targets of ZWD by using only network pharmacology. Therefore, the next step is to carry out experimental research to further confirm the results of this study.Conceptualization: Sai Yan.Data curation: Sai Yan, Qingchun Shi, Hongtao Ma.Formal analysis: Sai Yan.Funding acquisition: Sai Yan.Investigation: Sai Yan.Methodology: Sai Yan.Project administration: Sai Yan.Resources: Sai Yan.Software: Qian Xu.Supervision: Qian Xu.Validation: Sai Yan.Visualization: Sai Yan.Writing – original draft: Sai Yan.Writing – review & editing: Sai Yan.


Periodontal ligament stem cells (PDLSCs) have multidirectional differentiation potential and self-renewal abilities and are important seed cells for the regenerative repair of periodontal tissues. In recent years, many studies have identified multiple signalling pathways involved in regulating the osteogenic differentiation of PDLSCs in an inflammatory environment. In this article, we review the osteogenic differentiation of PDLSCs in an inflammatory environment in terms of signalling pathways and provide new ideas for the regenerative treatment of periodontal tissues. 2+, Wnt/PCP, NF-κB, MAPK, BMPs, and PI3K/AKT, are involved in regulating the osteogenic differentiation of PDLSCs. In addition, multiple signalling pathways that interact with microRNAs play crucial roles in the osteogenic differentiation of PDLSCs.PDLSCs possess multidirectional differentiation potential and self-renewal ability. In the inflammatory environment, signalling pathways, such as Wnt/β-catenin, Wnt/Ca The oral cavity is an open organ where many microorganisms accumulate, and the oral inflammatory environment can be divided into two categories: pathological and nonpathological. The nonpathological oral inflammatory environment is a harmless inflammatory microenvironment maintained by the normal flora in the oral cavity through competition and mutual restraint between the host and the normal flora, and most microorganisms are normal flora and conditionally pathogenic bacteria, maintaining the balance of flora in the human body. When the balance between the flora in the oral cavity is disrupted due to a decrease in immunity, trauma, infection, allergy, or systemic disease, inflammatory diseases of the oral cavity will occur, resulting in the formation of a pathological inflammatory environment. There is a wide range of clinical oral inflammatory diseases, including oral ulceration, allergic stomatitis, chemo/radiotherapy-induced oral mucositis, periodontitis, necrotising inflammatory disease of the jaws, Sjogren syndrome (SS), and many more others. Of these, periodontitis is one of the most common clinical inflammatory diseases of the oral cavity and is by far one of the most dangerous to human oral health. Periodontitis is a chronic inflammation of the supporting tissues of the periodontium caused mainly by local factors, and oral bacteria are the initiating factors in its pathogenesis, while genetic and acquired factors of the host are the determining factors in the development and aggravation of periodontitis. If gingivitis is not treated in time, inflammation can spread from the gingiva to the periodontium, alveolar bone and dental bone and develop into periodontitis, eventually leading to the loosening and loss of teeth, resulting in masticatory dysfunction . The goain vitro experiments. Although there have been animal studies on the use of PDLSCs in periodontal tissue regeneration therapy, many of these animal models are not true models of pathological inflammation, and the cells have not been successfully implanted into the jawbone, making this research somewhat limited [In recent years, with the rapid development of tissue engineering and stem cell technology, many studies have identified the use of mesenchymal stem cells (MSCs) as a promising therapeutic strategy for the treatment of oral inflammatory diseases . In part limited . HoweverIn this article, we review studies on the regulation of the osteogenic differentiation of PDLSCs by different signalling pathways in an inflammatory environment to provide inspiration to subsequent researchers.22+ and Wnt/PCP signalling pathways [The Wnt signalling pathway is a complex network of protein interactions that mainly consists of the classical Wnt/β-catenin signalling pathway and the nonclassical Wnt/Capathways .2.1Previous studies have demonstrated that the Wnt/β-catenin signalling pathway plays an important role in activating the osteogenic differentiation potential of stem cells ,7. In thIt has been shown that the classical Wnt/β-catenin signalling pathway is involved in the osteogenic differentiation of PDLSCs, but it is still unclear whether the classical Wnt signalling pathway plays a positive or negative role in the osteogenic differentiation of PDLSCs. Many scholars found that the classical Wnt signalling pathway positively regulated the osteogenic differentiation of PDLSCs. Interestingly, the inflammatory microenvironment can inhibit the osteogenic differentiation of PDLSCs by activating the Wnt/β-catenin signalling pathway. Wu and Xi  found th2.22+ concentrations and further activation of downstream CAMKII, CaN, and PKC [The binding of Wnt5a and Wnt11 to the FZD protein and LRP coreceptor on the cell membrane can activate PLC via G proteins, resulting in a transient increase in cytoplasmic Ca and PKC . Activat2+ signalling pathway is involved in the osteogenic differentiation of PDLSCs in a chronic inflammatory microenvironment. After osteogenesis induction, CAMKII and NLK levels were significantly increased in H-PDLSCs and P-PDLSCs, but the levels were always lower in P-PDLSCs than in H-PDLSCs, indicating that the osteogenic differentiation of PDLSCs via the nonclassical Wnt/Ca2+ signalling pathway was somewhat inhibited in an inflammatory environment.Liu et al.  showed t2.3In the atypical planar cell polarity pathway, Wnt is expressed upstream of PCP signalling and in a gradient, providing the polarity signal . Wnt11 aThe role of the Wnt/PCP signalling pathway in the development of cancer has been demonstrated previously . Li et a2.4Current research suggests that classical and nonclassical Wnt signalling pathways play important roles in bone development and regeneration . In a heThe Wnt signalling pathway has been relatively well studied, but the complex regulatory mechanisms through which inflammatory factors activate the Wnt signalling pathway in an inflammatory environment remain unclear. Furthermore, the underlying mechanisms of the interactions among Wnt signalling pathways remain obscure. Investigating the activation mechanisms of Wnt signalling pathways and the interaction mechanisms between classical and nonclassical Wnt signalling pathways to identify key targets to block the development of chronic periodontitis could be invaluable in the clinical management of periodontal disease.3Two NF-κB activation pathways exist in cells. The classical pathway is mainly activated by TNF, IL-1, and Toll-like receptor 4 (TLR4), is mainly dependent on IKKβ and NEMO, and leads to IκBα phosphorylation and p65-containing heterodimeric nuclear translocation. The nonclassical pathway is induced by specific members of the TNF cytokine family and relies primarily on IKKα-mediated phosphorylation of p100 associated with RelB, leading to partial processing of p100 and production of the p52-RelB complex . NumerouIn chronic periodontitis, there is a mutually reinforcing relationship between the NF-κB signalling pathway and the inflammatory environment. Inflammatory factors such as TNF-α and IL-1β in the inflammatory environment activate the NF-κB signalling pathway, while the NF-κB signalling pathway promotes the expression of these inflammation-related factors, creating a vicious cycle that exacerbates the development of chronic periodontitis . Li and TNFα, IL1β, and IL6 as well as the inhibition of proliferation and osteogenic differentiation of PDLSCs, and the EZH2-TLR4/MyD88/NF-κB axis may be a new target in periodontal tissue regeneration therapy.The main pathogenic factor in periodontitis is bacteria, and lipopolysaccharide (LPS) is a cell wall component of gram-negative bacteria. Many studies have shown the role of LPS in the pathogenesis of periodontitis. Dong and Shuang  showed tin vitro stage, and more research is needed to confirm the safety and feasibility of this strategy in the treatment of periodontitis. Most of the drugs currently used in the treatment of inflammatory diseases, such as NSAIDs, anti-rheumatic drugs, cyclosporine A, and corticosteroids, have inhibitory effects on NF-κB activity [It has long been known that the NF-κB signalling pathway plays a negative role in the osteogenic differentiation of PDLSCs and that activation of the NF-κB signalling pathway in an inflammatory environment is one of the key factors that reduces the regenerative capacity of periodontal tissues. Many studies have focused on targeting the NF-κB signalling pathway to improve periodontitis-induced alveolar bone loss and enhance the osteogenic differentiation of stem cells. For example, reducing the expression of some proteins upstream or downstream of the NF-κB signalling pathway and blocking activation of the NF-κB signalling pathway have provided many new targets for periodontal tissue regeneration therapy. However, many studies are still in the activity , providi4Mitogen-activated protein kinases (MAPKs) are a group of serine-threonine protein kinases that can be activated by different extracellular stimuli. All eukaryotic cells express MAPKs, which consist of a three-tier signalling pathway: MAPK, MAP kinase kinase, and MAP kinase kinase of MAPK kinase. These three levels of signalling are activated sequentially and are involved in the regulation of cell proliferation, differentiation, stress, inflammation, apoptosis, and carcinogenesis. The MAPK family consists of four main subfamilies: extracellular signal-regulated protein kinase 1/2 (ERK1/2), p38 MAPK, c-Jun amino-terminal kinase (JNK), and ERK5. Cascade activation of MAPK is the intersection of many signalling pathways; therefore, MAPK is inextricably linked to the development of many diseases. in vivo. Yong et al. [A number of studies have shown that the ERK1/2 and p38 MAPK subfamilies are involved in the expression of osteogenic genes and bone formation. Kim et al.  demonstrg et al.  showed tin vivo, there have been fewer studies of MAPK pathway involvement in regulating osteogenic differentiation in the inflammatory setting. The p38MAPK subfamily pathway has been shown to be involved in the osteogenic differentiation of stem cells derived from inflammatory tissues. Nie et al. [Although there have been many studies on the role of the MAPK family in osteogenic differentiation e et al.  demonstrin vitro stage, and there is a lack of animal studies to confirm its role in promoting the osteogenic differentiation of P-PDLSCs in vivo. Yan et al. [Given the important role of the MAPK signalling pathway in the osteogenic differentiation of stem cells, there have been many studies targeting the MAPK pathway to improve the osteogenic differentiation potential of PDLSCs in an inflammatory environment. Wang et al.  showed tn et al.  found thA search of major databases revealed that research on MAPK signalling pathway regulation of the osteogenic differentiation of PDLSCs in inflammatory states is still in its infancy. However, a recent study used the MAPK signalling pathway as a key target, especially the p38MAPK pathway, which is closely related to inflammation , and by 5Bone morphogenetic protein (BMP) signalling molecules belong to the transforming growth factor-β (TGF-β) protein superfamily, which plays an important role in the formation of bone and cartilage. Previous studies have identified BMP3 as a negative regulator of bone density and BMP13 as a strong inhibitor of bone formation. Moreover, BMP2, 4, 6, 7, and 9 have potent osteoinductive activity and play important roles in maintaining bone homeostasis in humans . A study showed that the BMP signalling pathway could activate the MAPK pathway to participate in the osteogenic differentiation of stem cells. Li et al.  showed tMany studies have shown that the BMP/Smad pathway plays an important role in the osteogenic differentiation of stem cells. After BMP binds to receptors on the corresponding cell membrane, it can phosphorylate Smad and activate the BMP signalling pathway, thereby regulating the expression of osteogenic-related markers and promoting the osteogenic differentiation of stem cells. Wang et al.  found thMany studies have demonstrated the role of the BMP signalling pathway in the development of periodontal disease. The search for targets related to the BMP signalling pathway may provide new ideas for the treatment of periodontal diseases. Liu et al.  showed t6PI3K is an intracellular phosphatidylinositol kinase that consists of the regulatory subunit p85 and the catalytic subunit p110. PI3K can be divided into three classes, and the most widely studied is class I PI3K. When PI3K binds to the corresponding receptor on the cell membrane, the receptor activates the regulatory subunit p85 and recruits the catalytic subunit p110, which in turn catalyses the production of PI3P from PIP2 on the inner surface of the membrane. PI3P acts as a second messenger that can further activate AKT, which is an important signalling molecule downstream of PI3K that has at least three forms: AKT1, AKT2, and AKT3. Activated AKT plays an important physiological role in regulating cell proliferation, differentiation, development, and apoptosis by phosphorylating various downstream signalling molecules.in vivo through the PI3K/AKT/mTOR/S6K1 signalling pathway [Mammalian target of rapamycin (mTOR) is an important signalling molecule downstream of the PI3K/AKT signalling pathway. The PI3K/AKT/mTOR signalling pathway is involved in regulating the osteogenic differentiation of PDLSCs . Zhao et pathway , but theIn addition to inducing the osteogenic differentiation of PDLSCs through the mTOR pathway, a study by Xiong  showed tAlthough many studies have confirmed the role of the PI3K/AKT signalling pathway in osteogenic differentiation, there have been few studies on the osteogenic differentiation of PDLSCs by the PI3K/AKT signalling pathway in an inflammatory environment. Further studies on the complex mechanisms by which the PI3K/AKT pathway regulates the osteogenic differentiation of P-PDLSCs could identify new targets for the treatment of periodontitis .7miRNAs are a class of noncoding single-stranded RNA molecules, approximately 19–24 nt in length that are encoded by endogenous genes. miRNAs bind to the 3′UTR or coding region of target mRNA sequences through complementary base pairing, thereby directing the silencing complex (RISC) to degrade the RNA or prevent the translation of mRNA into protein.Many studies have shown an inextricable relationship between miRNAs and signalling pathways, and the regulation of cellular signalling pathways via miRNAs is expected to provide new approaches for the treatment of some diseases. Zhong et al.  found thIn recent years, many scholars have found that miRNAs can regulate the osteogenic differentiation of PDLSCs through signalling pathways. Chen and Wu  found th8In this review, the effects of different signalling pathways on the osteogenic differentiation of PDLSCs in the context of periodontitis were summarised through a search of national and international databases. The current study showed that Wnt, NF-κB, MAPK, BMP, PI3K/AKT, and other signalling pathways play important roles in the osteogenic differentiation of P-PDLSCs. These signalling pathways have independent transduction mechanisms and undergo crosstalk, and together, these pathways govern the osteogenic differentiation of P-PDLSCs. The aim of this article was to elucidate the mechanisms through which these signalling pathways regulate the osteogenic differentiation of P-PDLSCs and to show that the Wnt and NF-κB signalling pathways have been studied more frequently and that these two signalling pathways play major roles in osteogenic differentiation, while the MAPK, BMP, and PI3K/AKT signalling pathways have been less studied and need to be further explored.Controlling the progression of inflammation is currently the main strategy in the treatment of periodontitis. Different anti-inflammatory drugs have different anti-inflammatory mechanisms, and many studies have shown that anti-inflammatory drugs exert their effects through signalling pathways, which raises many questions about drug use options. The antagonistic or synergistic effects of several anti-inflammatory drugs when used together can affect the efficacy of these drugs. The nature of the inflammatory response is defensive, and the misuse of anti-inflammatory drugs can be counterproductive. As a result, studying different signalling pathways in the pathological oral inflammatory environment may provide new insights into drug use.Furthermore, anti-inflammatory treatment can only stop the further development of inflammation but cannot compensate for the tissue damage already caused by inflammation. Therefore, repairing periodontal tissue, inducing the regeneration of bone and alveolar bone and re-establishing a normal occlusal relationship are important strategies to improve the prognosis of periodontitis and to improve the quality of life of patients with periodontitis. With the development of bioinformatics and tissue engineering technologies, the interaction network between different signalling pathways can be constructed through bioinformatics analysis, and key targets for osteogenic differentiation can be identified. Through the extraction and combination of natural compounds acting on the targets, it is expected that periodontal tissue regeneration inducers with good efficacy can be developed, providing new ideas to improve the prognosis of periodontitis.