Network pharmacological analysis and experimental verification of Zisheng Tongmai decoction in the treatment of Premature ovarian failure

Network pharmacological analysis and experimental verification of Zisheng Tongmai decoction in the treatment of Premature ovarian failure | 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 Research Article Network pharmacological analysis and experimental verification of Zisheng Tongmai decoction in the treatment of Premature ovarian failure Jiaru Wu, Mengjie Wen, Zecheng Wang, Kun Yu, Xinyue Jin, Chenxu Liu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4791876/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Oct, 2024 Read the published version in Naunyn-Schmiedeberg's Archives of Pharmacology → Version 1 posted 8 You are reading this latest preprint version Abstract Purpose Premature ovarian failure (POF) is a disease that seriously jeopardizes women's physical and mental health worldwide. Zisheng Tongmai decoction (ZSTMD), a famous Traditional Chinese Medicine (TCM) formula, has a marked effect on the clinical treatment of POF. This study investigated the potential mechanism of ZSTMD to improve POF through network pharmacology and experimental validation. Methods The active components, key targets and potential mechanisms of ZSTMD against POF were predicted by network pharmacology and molecular docking. The POF model was induced in rats by cyclophosphamide (CTX) and subsequently gavaged with different doses of ZSTMD. KGN cells were treated with different concentrations of quercetin and CTX. Histopathological were observed via hematoxylin and eosin (H&E) staining and immunofluorescence staining. Serum estrogen levels were detected via ELISA. Protein expression was detected via Western blotting. Results We identified quercetin as the main active ingredients targeting VEGFA. Molecular docking showed that VEGFA interacted well with the main active components of ZSTMD. In vivo experiments, ZSTMD significantly increased body weight and the ovarian index, significantly increased E2 and AMH, and decreased FSH and LH in POF rats. Histologic results showed that ZSTMD increased the number of follicles and vascular density in the ovary. It also increased VEGFA and CD31 protein expression. In vitro experiments, quercetin suppressed CTX-induced apoptosis in KGN cells and increased VEGFA protein expression. Discussion Our study demonstrated that ZSTMD improves POF by promoting angiogenesis through VEGFA target. Network pharmacology Zisheng Tongmai decoction Quercetin VEGFA Premature ovarian failure KGN cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Premature ovarian failure (POF) is characterized by amenorrhea resulting from follicular depletion or dysfunction in women under 40 years old. It is marked by increased serum concentrations of follicle-stimulating hormone (FSH) and luteinizing hormone (LH), along with decreased levels of estradiol (E2). Clinical manifestations include reproductive endocrine disorders such as prolonged menstrual cycles, amenorrhea, reduced fertility, or infertility. Additionally, some patients may experience menopausal symptoms including hot flashes, night sweats, vaginal dryness, and decreased libido (Wesevich et al., 2020 ). Epidemiological surveys indicate that the global prevalence of POF is 3.5%, posing a significant threat to women's reproductive health, particularly among younger women (Li et al., 2012 ). The pathogenesis of POF is highly complex. Although hormone replacement therapy (HRT) is a common modern treatment, long-term HRT increases the risks of stroke, heart disease, and pulmonary embolism (Lin et al., 2021 ). Therefore, there is an urgent need for the development of complementary and alternative therapies for POF. Traditional Chinese Medicine (TCM) treatment for POF is known for its efficacy and minimal side effects (Fu et al., 2022 ). According to TCM, the etiology of POF primarily involves kidney deficiency, but also spleen deficiency, liver depression, and qi and blood deficiency (Li et al., 2020 ; Ma et al., 2019 ). These deficiencies manifest as loss of appetite, irritability, and poor blood circulation (Wesevich et al., 2020 ). Consequently, TCM primarily focuses on tonifying the kidney and nourishing the essence, while also addressing blood tonification, liver drainage, spleen strengthening, and heart nourishment (Li et al., 2022 ). TCM herbs contain various bioactive components that can inhibit apoptosis, reduce oxidative stress, promote follicular development, and improve POF through multiple pathways and targets (Cai et al., 2021 ). For example, flavonoids such as quercetin and kaempferol, commonly found in herbs, are known to reduce mitochondrial oxidative stress and inhibit ovarian cell apoptosis (Liu et al., 2021 ; Zheng et al., 2022 ). ZSTMD is a traditional formulation derived from the ‘Records of Tradition Chinese and Western Medicine in Combination’. It consists of Baizhu ( Paeonia lactiflora Pall., Paeoniaceae ), Shanyao ( Dioscorea opposite Thunb., Dioscoreaceae ), Jineijin (G alli Gigerii Endothelium Coreneum, Animals ), Longyan ( Dimocarpus longan Lour., Sapindaceae ), Shanzhuyu ( Cornus officinalis Siebold & Zucc., Cornaceae ), Gouqi ( Lycium berlandieri Dunal., Solanaceae ), Xuanshen ( Scrophularia ningpoensis Hemsl., Scrophulariaceae ), Baishao ( Paeonia lactiflora Pall., Paeoniaceae ), Taoren ( Prunus persica L. Batsch, Rosaceae ), Honghua ( Carthamus tinctorius L., Asteraceae ) and Gancao ( Glycyrrhiza L., Fabaceae ). ZSTMD is recognized for its ability to nourish blood and promote menstruation, making it a common treatment for conditions such as menorrhagia, reduced appetite, and burning cough in women. Despite its significant therapeutic effects in clinical practice, there is a notable lack of in-depth international research on ZSTMD for POF. Only one study in the China National Knowledge Infrastructure (CNKI) has reported a clinical trial, indicating that ZSTMD effectively treats menstrual stagnation in women with a cure rate of up to 72.73% (Guo, 2014 ). This study aims to elucidate the main components of ZSTMD for the treatment of POF through network pharmacological analysis and experimental validation. We have identified VEGFA as a key target of ZSTMD in treating POF. VEGFA, also known as vascular permeability factor (VPF), plays a crucial role in promoting ovarian vascular growth in POF model rats. It was originally identified as an endothelial growth factor and a regulator of vascular permeability (Claesson-Welsh and Welsh, 2013 ; Zhou et al., 2021b ). Therefore, we investigated whether ZSTMD enhances angiogenesis in POF through VEGFA targets at both in vivo and cellular levels. Methods and Materials Information on the herbs, active ingredients and targets of ZSTMD The Chinese Pharmacopoeia 2020 edition (Commission, 2020 ) was consulted to obtain information on the classification and properties of Baizhu, Shanyao, Jineijin, Longyan, Gouqizi, Xuanshen, Baishao, Taoren, Honghua, and Gancao. Data on each herb in ZSTMD were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, http://tcmspw.com/tcmsp.php ) and the Traditional Chinese Medicine Integrative Database (TCMID, http://bidd.group/TCMID/ ). The chemical components retrieved were screened for oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18. Active compounds without potential target information were excluded. The UniProt database ( https://www.uniprot.org/ ) was then utilized to identify target genes corresponding to the target proteins, with filters set to ‘reviewed’ status and ‘human’ species. Prediction of potential targets for POF The GeneCards database ( https://www.genecards.org/ ) was searched for targets associated with POF using the keywords ‘Premature ovarian failure’ and ‘Premature ovarian insufficiency (POI)’. The resulting targets were filtered by taking those that appeared more than twice the median frequency, to identify those more strongly associated with POF. The names of the screened targets were normalized using the UniProt database. Intersecting targets of the ZSTMD and POF The targets of ZSTMD and those related to POF and POI were input into Venny2.1.0 ( https://bioinfogp.cnb.csic.es/tools/venny ) to generate Venn diagrams, identifying the intersecting targets. Construction of the protein-protein interaction (PPI) network The intersecting targets were entered into the STRING database ( https://string-db.org/ ) to construct a protein-protein interaction (PPI) network. Free nodes were removed, and the minimum interaction score was set to 0.4. The resulting data were exported and imported into Cytoscape software for network topology analysis. Subnetworks with the highest scores were initially screened using the MCODE plug-in. Subsequently, key targets for ZSTMD treatment of POF, characterized by high degree values, were identified using the CentiScaPe plug-in. OD, GO and KEGG enrichment analysis The intersecting target information was imported into the DAVID ( https://david.ncifcrf.gov/ ) database to perform Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The collected information was then used to create bubble diagrams on the Wbioinformatics web page ( https://www.bioinformatics.com.cn/ ). Network diagrams were also generated using Cytoscape 3.9.0. Prediction of the core components of the ZSTMD The components and corresponding targets identified in ZSTMD were imported into Cytoscape 3.9.0 software to construct an herbal-active component-target network. The intersecting targets were then added to construct an active component-intersecting target network. This network enables the identification of high-frequency components as key components. Molecular docking In this study, molecular docking was conducted using key target proteins and core components identified through the aforementioned method. The 3D structures of the target proteins were obtained from the RCSB PDB database ( https://www.rcsb.org ). Water molecules and native ligands were removed from the target proteins using PyMOL. The target proteins were then imported into AutoDock Tools 1.5.7 for hydrogen addition, charge calculation, and nonpolar hydrogen merging. The results were saved as PDBQT receptor files. Small molecule ligands were downloaded from the TCMSP database in MOL2 format. Hydrogen addition, charge calculation, and nonpolar hydrogen merging were performed in AutoDock Tools 1.5.7, and torsion bonds were set to incorporate nonpolar hydrogens. The results were saved as PDBQT ligand files. The PDBQT structures of the receptor and ligand were imported into AutoDock Tools 1.5.7 to construct docking pockets, ensuring the grid box size could completely encompass the protein. Finally, AutoDock Vina was executed via the CMD command to perform molecular docking, calculate binding energies, and select the model with the lowest binding energy. The results were exported in PDBQT format. These files were then imported into PyMOL for visualization of the hydrogen bonds in the docking model. Animals Eight-week-old female SD rats weighing approximately 220 g were purchased from Huafukang Biotechnology Co., Ltd. (Beijing, China). Rats were allowed ad libitum adaptive feeding at a constant temperature of 23°C for one week on a 12-hour day-night cycle. During this period, the estrous cycle of the rats was monitored daily, and those with a normal estrous cycle were selected for the experiment. Drugs and reagents ZSTMD was procured from the outpatient department of Hebei University of Chinese Medicine. The preparation method entails the removal of water from the decocted herbal liquid using thin-film concentration technology, reverse osmosis technology, and drying techniques such as spray drying, to obtain herbal granules. Each bag of granules weighs approximately 15g. The product complied with Good Manufacturing Practice and Good Laboratory Practice standards. The drugs used were Baizhu (9 g), Shanyao (30 g), Jineijin (6 g), Longyan (18 g), Shanzhuyu (12 g), Gouqi (12g), Xuanshen (9 g), Baishao (9 g), Taoren (6 g), Honghua (4.5 g) and Gancao (6 g). Cyclophosphamide (CTX, 0523188-32, Cayman, Michigan, USA) was used to induce the POF rat model. Estrogen (J20080036) was purchased from Bayer Healthcare Co., Ltd., and was used as a control for chemical drugs. Quercetin (HPLC > 99.0%, S2391, Houston, TX, USA) was used to treat KGN cells. Establishment of the POF rat model and grouping The POF model was initiated with 50 mg/kg cyclophosphamide on the first day, followed by 8 mg/kg per day for the next two weeks. The rats were observed beyond the initial period, and their weights were recorded weekly. Successful modeling was indicated when the rats’ estrous cycles were longer than six days. The remaining rats were used as the blank control (CON) group and were injected intraperitoneally with saline. During the experiment, the ZSTMD pellets were administered using distilled water. Drug concentrations for the rats were adjusted based on the conversion of rat to human body surface area. Subsequently, the rats were randomly divided into five groups: the model group (MOD), the ZSTMD low-concentration group (ZSTMD-L, 1.575 g/kg), the ZSTMD high-concentration group (ZSTMD-H, 3.150 g/kg), the estrogen group (E2, 0.0216 g/kg), and the blank control (CON) group. Gavage was performed at the same time each day for 28 days in the ZSTMD-L/H and E2 groups. Continuous estrous cycle testing was performed daily. The MOD and CON groups were gavaged with distilled water. At the end of the treatment, all rats were sacrificed. Blood was collected, and the serum obtained after centrifugation was frozen. The ovaries were removed and weighed. Part of the tissue was stored in a -80°C refrigerator, and the other part was fixed in 4% paraformaldehyde (20220927, Biosharp, Guangzhou, China). Hematoxylin & eosin (H&E) staining and immunofluorescence staining Ovarian tissue samples from each mouse were fixed in 4% formalin saline solution, embedded in paraffin, and cut into 5 µm sections. After dewaxing and rehydration, the tissue sections were stained with hematoxylin solution (C211107, Baso, Beijing, China) for 5 minutes, followed by soaking in different concentrations of ethanol five times, and rinsing with distilled water. The sections were then stained with eosin (C220501, Baso, Beijing, China) for 3 minutes. Xylene was used to dehydrate the sections in a graded series of alcohol. Immunofluorescence staining for the vascular marker CD31 was performed. Goat serum (G1208, Servicebio, Wuhan, China) diluted 20-fold in PBS was added to the sections, which were incubated for 5 minutes at room temperature. The sections were then incubated overnight at 4°C with a CD31 antibody (GB21303, Servicebio, Wuhan, China). The next day, the sections were incubated with a secondary antibody and stained with DAPI (G1012, Servicebio, Wuhan, China). Images were acquired by fluorescence microscopy (DMi8, Leica, Solms, Germany). ELISA After the treatment, blood samples were collected from the rats. Serum was separated by centrifugation at 1500 rpm for 15 minutes at 4°C. Serum concentrations of AMH, E2, and FSH were quantified using enzyme-linked immunosorbent assay (ELISA) kits (Shanghai Enzyme Biotechnology Co., Ltd., Shanghai, China). The assays were performed in strict accordance with the manufacturer’s protocols. The optical density (OD) was measured at 450 nm using an enzyme-linked immunosorbent assay reader (RT-6100, Rayto, Shenzhen, China). Hormone concentrations were then calculated based on the corresponding standard curves. Cell culture and establishment of the POF model The KGN human granulosa cell line was purchased from Starfish Biotechnology Co., Ltd. (TCH-C230, HyCyte, Suzhou, China). A total of 2 × 10 6 cells were inoculated in 100 mm Petri dishes (TCH-G230, HyCyte, Suzhou, China) and cultured in an incubator at 37°C with humidified air containing 5% CO2. The culture medium was changed every other day. KGN cells were treated with various concentrations (20, 50, 100, 150, and 200 µg/mL) of CTX to determine the optimal concentration. Cells were pretreated with different concentrations (30, 60, and 100 µM) of quercetin followed by treatment with 100 µg/mL of CTX. Western blot A protein assay kit was used to determine the protein concentration of each sample. Ovarian tissue proteins were extracted according to the instructions of the Total Protein Extraction Kit, transferred to PVDF membranes, blocked in 5% skim milk powder for 1 hour, and then incubated overnight at 4°C with primary antibodies including anti-VEGFA (1:1000, bs1313R, Bioss Antibodies, Beijing, China), anti-CD31 (1:1000, bsm10825M, Bioss Antibodies, Beijing, China), anti-caspase3 (1:1000, p42574, Bioworld Technology, Inc., MN, USA), and β-actin (1:1000, bs55208R, Bioss Antibodies, Beijing, China). The next day, the membranes were incubated with the corresponding secondary antibodies for 1 hour at room temperature. Bands were detected using the ECL detection kit (Applygen Technologies Inc., Beijing, China). Statistical analysis Data were analyzed using SPSS 20.0 statistical software (SPSS Inc., Chicago, IL, USA). All data are expressed as the mean ± SD. P-values were analyzed using Student’s t-test, with a significant difference defined as P < 0.05. Results Information on the herbs, active ingredients and targets of ZSTMD Most of the herbs in ZSTMD have a sweet taste, accounting for 42.86% (Fig. 1 A), and the majority of the nature are calm, accounting for 45.45% (Fig. 1 B). Herbs attributed to the liver and spleen meridians were the most abundant in ZSTMD (Fig. 1 C). Specific information on the Chinese medicines used is shown in Table 1 . A search of TCMSP, TCMID, and the literature revealed Baizhu with 4 constituents, Shanyao with 14 constituents, Longyan with 3 constituents, Shanzhuyu with 4 constituents, Gouqi with 40 constituents, Xuanshen with 9 constituents, Baishao with 4 constituents, Taoren with 21 constituents, Honghua with 20 constituents, and Gancao with 40 constituents. Among them, 9 common components were identified. After combining and deduplicating the data, 203 active ingredients acting on a total of 571 targets were identified. Table 1 Channel Tropism, Properties and Flavour of TCM in ZSTMD Herbs Channel Tropism Property and flavor Baizhu Spleen,Stomach Warm, Bitter, Sweet, Shanyao Spleen, Lung, Kidney Calm, Sweet Jineijing Spleen, Stomach, Small Intestine, Bladder Calm, Sweet Longyan Heart, Spleen Warm, Sweet Shanzhuyu Liver,Kidney Warm,Sour, Astringent Gouqi Liver,Kidney Calm, Sweet Xuanshen Lung,Large Intestine,Liver Cold, Bitter, Salty Baishao Liver,Spleen Cold,Bitter,Sour Taoren Heart, Liver, Lung, Large Intestine Calm, Bitter Honghua Heart Liver Warm, Bitter Gancao Spleen,Lung,Stomach,Heart Calm, Sweet Identification of intersection targets From the GeneCards database, 5082 targets associated with POF and 5943 targets associated with POI were initially screened. Secondary screening based on the median relevance score yielded 1657 and 1556 targets, respectively. A Venn diagram was plotted to show the 568 targets acting on the active ingredient of ZSTMD and the above targets, revealing 209 intersection targets (Fig. 2 A). PPI network construction The PPI network with 206 nodes and 1374 edges was constructed by importing 209 intersection targets into the STRING database (Fig. 2 B). The minimum required interaction score was set to 0.4. The data obtained from STRING were imported into Cytoscape 3.9.0 software for topology analysis. First, we used the MCODE plug-in to filter the subnetwork with the highest score of 59 as the core cluster, obtaining a network of 36 nodes and 628 edges. Then, we used the CentiScaPe plug-in to filter the nine targets with the highest degree values (degree > 71), resulting in a network of 9 nodes and 36 edges (Fig. 2 C). A total of nine key targets were identified, including VEGFA, STAT3, CASP3, TP53, GAPDH, JUN, HIF1A, ALB, and AKT1. The literature was reviewed to understand the functions of these targets and identify key targets for the treatment of POF. These targets may be critical for the treatment of POF with ZSTMD. GO, DO and KEGG pathway enrichment analysis of the targets GO, DO, and KEGG enrichment analyses were performed on the intersecting targets using the DAVID platform. GO analyses included biological process (BP), cellular component (CC), and molecular function (MF) analyses. A total of 3963 statistically significant GO terms were obtained in this study, including 1053 BP items such as positive regulation of gene expression, negative regulation of apoptotic process, drug response, hypoxia response, aging, and estradiol response. Additionally, 116 CC terms were identified, such as extracellular space, macromolecular complex, extracellular region, cytoplasm, cytosol, and nucleoplasm. For MF, 200 terms were identified, including enzyme binding, identical protein binding, protein kinase activity, protein binding, protein tyrosine kinase activity, and protein kinase binding. The top 10 genes were selected for visualization (Fig. 3 A). DO terms identified 519 diseases, such as reperfusion injury, depressive disorder, breast carcinoma, hypertensive disease, and mammary neoplasms. The top 20 were selected for visualization (Fig. 3 B). 174 KEGG items were identified, and the top 50 pathways were selected for functional categorization. Pathways related to oxidative stress, apoptosis, and inflammation were screened, including the PI3K-Akt, DIAGRAMK, FoxO, TNF, and HIF-1 signaling pathways, as well as pathways related to cancer, the AGE-RAGE signaling pathway in diabetic complications, lipids, hepatitis B, and microRNAs in cancer. The top 20 pathways were selected for visualization (Fig. 3 C). Thirteen pathways associated with these functions were imported into Cytoscape 3.9.0 software with the names of their constituent genes, and network diagrams were generated (Fig. 3 D). These results suggest that POF is a multitarget and multipathway disease control agent. Construction of the active ingredient-intersection target network Cytoscape software was used to visualize the network of active ingredients and intersection targets related to the action of ZSTMD. First, the Chinese herbal medicine-ingredient-target sequence was imported into Cytoscape software to construct a Chinese herbal medicine-ingredient-target visualization network (Fig. 4 A). Then, the intersecting genes were imported into the software and screened for active ingredients connected to these genes, resulting in 199 connections. This was used to construct the component-intersection target visualization network (Fig. 4 B). The top 5 core ingredients were identified based on degree values, including quercetin, kaempferol, beta-sitosterol, luteolin, and hancinol. Information on the top 5 ingredients and their degree values is shown in Table 2 . The top three components, quercetin (MOL000098), kaempferol (MOL000422), and beta-sitosterol (MOL000358), are common to multiple herbs and were selected as candidate ligands for molecular docking validation. Table 2 Information on the core ingredients of the top 5 degree values of ZSTMD MOL ID MOL Name OB DL Source Degree value MOL000098 Quercetin 46.43 0.28 Honghua, Gouqizi, Gancao 208 MOL000422 Kaempferol 41.88 0.24 Honghua, Gouqizi, Baishao 106 MOL000358 Beta-sitosterol 36.91 0.75 Xuanshen, Taoren, Honghua, Gouqizi, Shanzhuyu, Baishao 100 MOL000006 Luteolin 36.16 0.25 Honghua 44 MOL005429 Hancinol 64.01 0.37 Shanyao 36 Molecular docking results The key target VEGFA (ID: 4QAF), identified through the PPI network, was molecularly docked with three candidate components: quercetin, kaempferol, and beta-sitosterol. The VEGFA suppressor Emvododstat was used as a positive control. The results showed that VEGFA had good affinity for quercetin, kaempferol, and beta-sitosterol, with binding energies of -7.14, -5.13, and − 7.47 kcal/mol, respectively, all below − 5.00 kcal/mol (Table 3 ). The active sites of the ligands and receptor in these binding models were stabilized by multiple hydrogen bonds (Fig. 4 C-E). Quercetin interacts with the amino acid residues TYR-25, ILE-37, ASN-62, and TRP-144 of VEGFA; kaempferol binds to the amino acid residues GLY-112, GLN-89, HIS-86, and LYS-58; and beta-sitosterol binds to the PRO-28 residue of VEGFA (Fig. 4 C-E). These modeling results suggest that these compounds are key pharmacological components of ZSTMD for the treatment of POF. Table 3 Specific information on the free energy of ligand-receptor binding Target protein Compound name Affinity (kcal/mol) VEGF(PDB ID: 4QAF) Emvododstat (Control) -7.81 Quercetin -7.14 Kaempferol -5.13 Beta-sitosterol -7.47 POF rat model test H&E staining of vaginal exfoliated cells showed nucleated, rounded epithelial cells in proestrus; large, cherry-like keratinized epithelial exfoliative cells during estrus; and equal numbers of nucleated cells, keratinized cells, and leukocytes in metestrus. During diestrus, most leukocytes were stained blue and few cells were stained pink (Fig. 5 B). Normally, rats have a 4-day estrous cycle. Modeling is considered successful when the estrous cycle is prolonged to 6 days or disrupted. In this experiment, most of the rats in the MOD group were in diestrus compared to the CON group, and most of their vaginal exfoliated cells were blue-stained leukocytes. These results indicate that the POF model was successfully established. ZSTMD contributed to the improvement of POF status After the start of modeling, we found that the weight gain of the rats slowed down and even became negative. However, after treatment, the weight of the rats in the ZSTMD-L/H and E2 groups began to increase slowly, with growth accelerating after two weeks. The weight of the model group decreased significantly one week after modeling, and then began to rise again two weeks post-modeling (Fig. 5 C). At the end of the experiment, the weight of the rat ovaries was measured, and the ovarian index was calculated. Analysis showed that the ovarian index was significantly higher in the CON and ZSTMD-L/H groups compared to the MOD group ( P <0.001 and P <0.05, respectively) (Fig. 5 D). ZSTMD improves ovarian function in a POF rat model Microscopic observation of H&E-stained ovaries from different groups revealed that the ovaries in the blank group had multiple developed dominant follicles, whereas those in the model group had only small atretic or undeveloped follicles. After treatment with traditional Chinese medicine or Western medicine, well-developed dominant follicles appeared in the ovaries (Fig. 6 A). Measurement of serum hormones in each group revealed a significant increase in E2 ( P <0.001) and AMH ( P <0.05), and a significant decrease in both FSH ( P <0.01) and LH ( P <0.001) in the ZSTMD-H group (Fig.s 6B-E). The effects of ZSTMD-L and E2 treatments were not as pronounced as those of the ZSTMD-H group. The E2 group also showed significant effects on E2 ( P <0.05), FSH ( P <0.001), LH ( P <0.05), and AMH ( P <0.001) (Fig. 6 B-E). The ZSTMD-L group showed significant elevations only in FSH ( P <0.01) and LH ( P <0.01) (Fig. 6 C-D). ZSTMD can promote ovarian blood vessel growth through VEGFA targets To further investigate the specific mechanism by which ZSTMD improves POF, we examined the expression of VEGFA and CD31 in ovarian tissues using Western blotting. The results revealed that the expression of VEGFA and CD31, a vascular endothelial marker, increased following treatment with ZSTMD (Fig. 7 A). In addition, immunofluorescence staining of ovarian tissues showed significantly reduced vascular density in the MOD group compared to the CON group, with an increase in vascular density following treatment with ZSTMD and E2 (Fig. 7 B). These results suggest that ZSTMD could act directly on VEGFA targets to promote ovarian angiogenesis, thereby improving POF. Quercetin suppresses apoptosis and promotes VEGFA protein expression in CTX-treated KGN cells We obtained granulosa cells for POF studies by treating KGN cells with CTX. The increase in apoptotic protein caspase3 was not significant at concentrations of 20 and 50 µg/ml, but it increased significantly when the concentration reached 100 µg/ml and above (Fig. 8 A). To investigate the cytotoxicity of quercetin, we treated KGN cells with different concentrations of quercetin for 24 hours and found no increase in apoptosis (Fig. 8 B). Subsequently, KGN cells were pretreated with 30, 60, and 100 µM quercetin for 1 hour, followed by CTX treatment for 24 hours. The results showed a significant increase in caspase3 protein expression and a significant decrease in VEGFA protein expression in the CTX group compared to the CON group (Fig. 8 C). Quercetin treatment significantly decreased caspase3 protein expression and increased VEGFA protein expression in a concentration-dependent manner (Fig. 8 C). Cellular experiments demonstrated that quercetin could suppress KGN cell apoptosis by targeting VEGFA. Discussion The main findings of this study include (a) ZSTMD improved ovarian function and related symptoms in POF model rats. (b) ZSTMD promoted the protein expression of VEGFA and CD31, (c) Quercetin suppressed CTX-induced apoptosis in KGN cells and promoted VEGFA protein expression, and (d) ZSTMD and its main constituent quercetin were found to act on VEGFA targets to improve aging ovaries by promoting blood vessel growth through network pharmacology, molecular docking, and experimental validation. ZSTMD is a well-known herbal tonic clinically proven to have therapeutic effects and is widely used to treat amenorrhea. However, no pharmacological analysis of this formula for the treatment of POF has been conducted. In this study,we analize the taste, nature and meridian tropism of the herbs in ZSTMD revealed that the majority of these herbs exhibits a sweet taste and calm nature, targeting the liver and spleen meridians. This aligns with traditional Chinese medicine principles for treating POF, which focus on nourishing the liver and spleen, promoting blood flow, and stabilizing the body's internal environment (Li et al., 2022 ). A total of 199 active ingredients and 209 intersecting genes of ZSTMD and POF were obtained by screening herbs from the TCMSP database. The active ingredient-target network analysis of the herbal medicines showed that quercetin, kaempferol, beta-sitosterol, luteolin, and hancinol were connected to multiple targets in the network diagram. The first three of these are common to various herbal medicines, and they all belong to the group of natural flavonoid compounds with mechanisms of action including anti-SARS-CoV-2, antioxidant, anticancer, anti-aging, antiviral, and anti-inflammatory activities (Sharma et al., 2021 ; Wang et al., 2022 ; Wang et al., 2019 ). Several studies have shown that quercetin acts as an inhibitor of oxidative stress in the treatment of POF. Quercetin significantly increased the expression of AMH, E2, superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) through the PI3K/Akt/FOXO3 signaling pathway (Zheng et al., 2022 ). After in-depth analysis of GO, DO, and KEGG, we found that the effects of ZSTMD on POF were mainly related to oxidative stress, apoptosis, inflammation, and hypoxia, and the involved pathways included PI3K-Akt, DIAGRAMK, FoxO, TNF, and HIF-1 signaling pathways. The PI3K-Akt pathway was the most involved. Several studies have demonstrated that the PI3K-Akt pathway induces oxidative stress, granulosa cell apoptosis, and autophagy in the ovary (Dai et al., 2023 ; Han et al., 2022 ; Zheng et al., 2022 ). To explore the core targets of POF in ZSTMD, a protein-protein interaction (PPI) network was constructed, revealing that VEGFA, STAT3, CASP3, TP53, GAPDH, JUN, HIF1A, ALB, and AKT1, especially VEGFA, which is highly enriched, may be the core targets involved in the treatment of POF by ZSTMD. These proteins are involved in the processes of oxidative stress, apoptosis, inflammation, and senescence. VEGFA is one of the major proangiogenic factors involved in regulating ovarian angiogenesis (Ferrara et al., 2003 ), and its role in regulating follicular development has been extensively studied (Guzmán et al., 2023 ; McFee et al., 2012 ). The vascular system has a strong influence on the formation of ovarian structures. The early developmental processes of ovarian cord formation, primordial follicle assembly, and follicular activation all begin in ovarian regions closely associated with a highly vascular medulla (McFee and Cupp, 2013 ). Additionally, abnormal angiogenesis is involved in the induction and development of pathological ovaries, such as in polycystic ovary syndrome and ovarian cancer (Xie et al., 2017 ). Chemotherapeutic agents such as cyclophosphamide have been shown to induce ovarian failure in young patients with breast cancer, possibly through vascular injury (Ben-Aharon et al., 2012 ). Therefore, VEGFA is necessary to improve oocyte competence, increase vascularity, and maintain functional ovarian activity. In the present experiments, ZSTMD promoted vascular growth, body weight, and ovarian index after CTX induction by targeting VEGFA, as evidenced by increased expression of VEGFA and CD31 proteins, as well as increased vessel density. In addition, E2 and AMH levels increased significantly while FSH and LH levels decreased significantly after treatment. Mingmin Zhang’s team reversed CTX-induced atrophy of the ovarian vasculature in a POF model and upregulated VEGFA expression using Si-Wu-Tang and umbilical cord-derived MSCs, respectively (Liu et al., 2023 ; Zhou et al., 2021a ). These findings are consistent with the results of our experiments. Molecular docking results showed that the three main active components of ZSTMD had strong binding affinities with VEGFA. Among the active components, quercetin has more hydrogen bond donors and acceptors, facilitating the formation of hydrogen bonds with targets and resulting in lower binding energy and more stable binding. Therefore, we pretreated KGN cells with quercetin for 1 hour and subsequently treated them with CTX for 24 hours. The results showed that quercetin suppressed CTX-induced apoptosis and promoted VEGFA protein expression. We demonstrated in vivo and in vitro that ZSTMD and its main component, quercetin, can target VEGFA to promote ovarian angiogenesis and improve POF. There remains considerable ambiguity regarding the role of quercetin in promoting angiogenesis. Several studies have demonstrated that flavonoids, such as quercetin, have a protective effect on tissue endothelial cells by promoting angiogenesis and blood reperfusion (Li et al., 2021 ; Sumi et al., 2013 ). However, other studies have found that quercetin suppresses VEGFA and angiogenesis in contexts such as allergic diseases and tumors (Oh et al., 2010 ; Okumo et al., 2021 ). These discrepancies may be related to the concentration of quercetin used and the specific mechanisms of action, necessitating further studies. Conclusions In conclusion, our study is the first to analyze the pharmacological components of ZSTMD and demonstrate that it can promote the recovery of ovarian function in POF. Specifically, ZSTMD reversed CTX-induced ovarian vascular atrophy in POF by targeting VEGFA, thereby improving ovarian function. Quercetin, a major component of ZSTMD, suppressed CTX-induced apoptosis in KGN cells and promoted VEGFA protein expression. Thus, we demonstrated that ZSTMD and quercetin could be potential treatments for POF by promoting ovarian blood vessel growth. These findings provide new insights into the treatment of POF with traditional Chinese medicine. Declarations Funding: This work was supported financially by the Hebei province Department of Human Resources (c20210358) and Social Security and Hebei Traditional Chinese Medicine Administration (2017010). Competing interests: The authors declare no competing interests. Authors Contributions: Jiaru Wu designed the study, supervised the data collection; Mengjie Wen, Zecheng Wang, Xinyue Jin and Chenxu Liu performed the experiments. Kun Yu, Qiuhang Song, Guohong Zhang and Beibei Wu analyzed the data, interpreted the data; Yunfeng Li prepare the manuscript for publication and reviewed the draft of the manuscript. All authors have read and approved the manuscript. The authors declare that all data were generated in-house and that no paper mill was used. Ethics approval: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Hebei University of Chinese Medicine (Date:2024.06.1 / No: DWLL202406001). Data availability: All data supporting the article is provided in this article. Ethical approval: Not applicable. References Ben-Aharon I, Meizner I, Granot T, Uri S, Hasky N, Rizel S, Yerushalmi R, Sulkes A and Stemmer SM (2012) Chemotherapy-induced ovarian failure as a prototype for acute vascular toxicity. Oncologist 17:1386-1393 doi: 10.1634/theoncologist.2012-0172. Cai L, Zong DK, Tong GQ and Li L (2021) Apoptotic mechanism of premature ovarian failure and rescue effect of Traditional Chinese Medicine: a review. J Tradit Chin Med 41:492-498 doi: 10.19852/j.cnki.jtcm.2021.03.017. Claesson-Welsh L and Welsh M (2013) VEGFA and tumour angiogenesis. J Intern Med 273:114-127 doi: 10.1111/joim.12019. Commission CP (2020) the Chinese Pharmacopoeia 2020 edition . Dai W, Yang H, Xu B, He T, Liu L, Ma X, Ma J, Yang G, Si R, Pei X, Du X and Fu X (2023) Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) alleviate excessive autophagy of ovarian granular cells through VEGFA/PI3K/AKT/mTOR pathway in premature ovarian failure rat model. J Ovarian Res 16:198 doi: 10.1186/s13048-023-01278-z. Ferrara N, Gerber HP and LeCouter J (2003) The biology of VEGF and its receptors. Nat Med 9:669-676 doi: 10.1038/nm0603-669. Fu Y, Ding DN, Shen Y, Jia LY, Yan MY, Wei W, Song CH and Han FJ (2022) Complementary and Alternative Medicine for Premature Ovarian Insufficiency: A Review of Utilization and Mechanisms. Evid Based Complement Alternat Med 2022:9053930 doi: 10.1155/2022/9053930. Guo Y (2014) Zisheng Tongmai Decoction in treating stagnation of too litte menstrual blood-stasis syndrome: a clinical observation [in Chinese], in Heilongjiang University of Chinese Medicine , Heilongjiang, China. Guzmán A, Hernández-Coronado CG, Gutiérrez CG and Rosales-Torres AM (2023) The vascular endothelial growth factor (VEGF) system as a key regulator of ovarian follicle angiogenesis and growth. Mol Reprod Dev 90:201-217 doi: 10.1002/mrd.23683. Han Y, Yao R, Yang Z, Li S, Meng W, Zhang Y, Zhang Y and Luo H (2022) Interleukin-4 activates the PI3K/AKT signaling to promote apoptosis and inhibit the proliferation of granulosa cells. Exp Cell Res 412:113002 doi: 10.1016/j.yexcr.2021.113002. Li HF, Shen QH, Chen WJ, Chen WM, Feng ZF and Yu LY (2020) Efficacy of Traditional Chinese Medicine Tonifying Kidney (Bushen) and Activating Blood (Huoxue) Prescription for Premature Ovarian Insufficiency: A Systematic Review and Meta-Analysis. Evid Based Complement Alternat Med 2020:1789304 doi: 10.1155/2020/1789304. Li M, Xiao YB, Wei L, Liu Q, Liu PY and Yao JF (2022) Beneficial Effects of Traditional Chinese Medicine in the Treatment of Premature Ovarian Failure. Evid Based Complement Alternat Med 2022:5413504 doi: 10.1155/2022/5413504. Li MT, Ke J, Guo SF, Wu Y, Bian YF, Shan LL, Liu QY, Huo YJ, Guo C, Liu MY, Liu YJ and Han Y (2021) The Protective Effect of Quercetin on Endothelial Cells Injured by Hypoxia and Reoxygenation. Front Pharmacol 12:732874 doi: 10.3389/fphar.2021.732874. Li X, Xu X, Wang J, Yu H, Wang X, Yang H, Xu H, Tang S, Li Y, Yang L, Huang L, Wang Y and Yang S (2012) A system-level investigation into the mechanisms of Chinese Traditional Medicine: Compound Danshen Formula for cardiovascular disease treatment. PLoS One 7:e43918 doi: 10.1371/journal.pone.0043918. Lin J, Wu D, Jia L, Liang M, Liu S, Qin Z, Zhang J, Han Y, Liu S and Zhang Y (2021) The Treatment of Complementary and Alternative Medicine on Premature Ovarian Failure. Evid Based Complement Alternat Med 2021:6677767 doi: 10.1155/2021/6677767. Liu H, Yang H, Qin Z, Chen Y, Yu H, Li W, Zhu X, Cai J, Chen J and Zhang M (2021) Exploration of the Danggui Buxue Decoction Mechanism Regulating the Balance of ESR and AR in the TP53-AKT Signaling Pathway in the Prevention and Treatment of POF. Evid Based Complement Alternat Med 2021:4862164 doi: 10.1155/2021/4862164. Liu X, Song Y, Zhou F, Zhang C, Li F, Hu R, Ma W, Song K, Tang Z and Zhang M (2023) Network and experimental pharmacology on mechanism of Si-Wu-tang improving ovarian function in a mouse model of premature ovarian failure induced by cyclophosphamide. J Ethnopharmacol 301:115842 doi: 10.1016/j.jep.2022.115842. Ma K, Wang KL and Chen YX (2019) [Infertility caused by salpingitis treated based on theory of kidney deficiency and blood stasis]. Zhongguo Zhong Yao Za Zhi 44:1099-1103 doi: 10.19540/j.cnki.cjcmm.20181225.004. McFee RM and Cupp AS (2013) Vascular contributions to early ovarian development: potential roles of VEGFA isoforms. Reprod Fertil Dev 25:333-342 doi: 10.1071/rd12134. McFee RM, Rozell TG and Cupp AS (2012) The balance of proangiogenic and antiangiogenic VEGFA isoforms regulate follicle development. Cell Tissue Res 349:635-647 doi: 10.1007/s00441-012-1330-y. Oh SJ, Kim O, Lee JS, Kim JA, Kim MR, Choi HS, Shim JH, Kang KW and Kim YC (2010) Inhibition of angiogenesis by quercetin in tamoxifen-resistant breast cancer cells. Food Chem Toxicol 48:3227-3234 doi: 10.1016/j.fct.2010.08.028. Okumo T, Furuta A, Kimura T, Yusa K, Asano K and Sunagawa M (2021) Inhibition of Angiogenic Factor Productions by Quercetin In Vitro and In Vivo. Medicines (Basel) 8 doi: 10.3390/medicines8050022. Sharma N, Biswas S, Al-Dayan N, Alhegaili AS and Sarwat M (2021) Antioxidant Role of Kaempferol in Prevention of Hepatocellular Carcinoma. Antioxidants (Basel) 10 doi: 10.3390/antiox10091419. Sumi M, Tateishi N, Shibata H, Ohki T and Sata M (2013) Quercetin glucosides promote ischemia-induced angiogenesis, but do not promote tumor growth. Life Sci 93:814-819 doi: 10.1016/j.lfs.2013.09.005. Wang G, Wang Y, Yao L, Gu W, Zhao S, Shen Z, Lin Z, Liu W and Yan T (2022) Pharmacological Activity of Quercetin: An Updated Review. Evid Based Complement Alternat Med 2022:3997190 doi: 10.1155/2022/3997190. Wang H, Chen L, Zhang X, Xu L, Xie B, Shi H, Duan Z, Zhang H and Ren F (2019) Kaempferol protects mice from d-GalN/LPS-induced acute liver failure by regulating the ER stress-Grp78-CHOP signaling pathway. Biomed Pharmacother 111:468-475 doi: 10.1016/j.biopha.2018.12.105. Wesevich V, Kellen AN and Pal L (2020) Recent advances in understanding primary ovarian insufficiency. F1000Res 9 doi: 10.12688/f1000research.26423.1. Xie Q, Cheng Z, Chen X, Lobe CG and Liu J (2017) The role of Notch signalling in ovarian angiogenesis. J Ovarian Res 10:13 doi: 10.1186/s13048-017-0308-5. Zheng S, Ma M, Chen Y and Li M (2022) Effects of quercetin on ovarian function and regulation of the ovarian PI3K/Akt/FoxO3a signalling pathway and oxidative stress in a rat model of cyclophosphamide-induced premature ovarian failure. Basic Clin Pharmacol Toxicol 130:240-253 doi: 10.1111/bcpt.13696. Zhou F, Song Y, Liu X, Zhang C, Li F, Hu R, Huang Y, Ma W, Song K and Zhang M (2021a) Si-Wu-Tang facilitates ovarian function through improving ovarian microenvironment and angiogenesis in a mouse model of premature ovarian failure. J Ethnopharmacol 280:114431 doi: 10.1016/j.jep.2021.114431. Zhou Y, Zhou J, Xu X, Du F, Nie M, Hu L, Ma Y, Liu M, Yu S, Zhang J and Chen Y (2021b) Matrigel/Umbilical Cord-Derived Mesenchymal Stem Cells Promote Granulosa Cell Proliferation and Ovarian Vascularization in a Mouse Model of Premature Ovarian Failure. Stem Cells Dev 30:782-796 doi: 10.1089/scd.2021.0005. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Oct, 2024 Read the published version in Naunyn-Schmiedeberg's Archives of Pharmacology → Version 1 posted Editorial decision: Revision requested 09 Aug, 2024 Reviews received at journal 09 Aug, 2024 Reviewers agreed at journal 06 Aug, 2024 Reviewers agreed at journal 24 Jul, 2024 Reviewers invited by journal 24 Jul, 2024 Editor assigned by journal 24 Jul, 2024 Submission checks completed at journal 24 Jul, 2024 First submitted to journal 23 Jul, 2024 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. 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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-4791876","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338240550,"identity":"53265aa9-9c4e-4ec7-8ccb-8582473ffd11","order_by":0,"name":"Jiaru Wu","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiaru","middleName":"","lastName":"Wu","suffix":""},{"id":338240551,"identity":"0b26f7fc-c157-47b1-bd20-2ed3cec65132","order_by":1,"name":"Mengjie Wen","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Mengjie","middleName":"","lastName":"Wen","suffix":""},{"id":338240552,"identity":"012b04a8-70a7-4894-901d-e5e729dcef1e","order_by":2,"name":"Zecheng Wang","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zecheng","middleName":"","lastName":"Wang","suffix":""},{"id":338240553,"identity":"d6d79972-66a0-46ed-8846-a7761ce5f300","order_by":3,"name":"Kun Yu","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kun","middleName":"","lastName":"Yu","suffix":""},{"id":338240554,"identity":"7b8e677f-526d-43f9-8437-73082ed6a757","order_by":4,"name":"Xinyue Jin","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xinyue","middleName":"","lastName":"Jin","suffix":""},{"id":338240555,"identity":"9f9d0a0d-507e-4378-9c28-05d6a98ceddf","order_by":5,"name":"Chenxu Liu","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chenxu","middleName":"","lastName":"Liu","suffix":""},{"id":338240556,"identity":"c9214fc7-e2a6-4962-b1b8-ab4e8d49e1d5","order_by":6,"name":"Qiuhang Song","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qiuhang","middleName":"","lastName":"Song","suffix":""},{"id":338240557,"identity":"d865359c-4b57-4e5f-a54c-dc0b49222016","order_by":7,"name":"Guohong Zhang","email":"","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Guohong","middleName":"","lastName":"Zhang","suffix":""},{"id":338240558,"identity":"008f68a4-06af-4fd8-ad67-06c315c66978","order_by":8,"name":"Beibei Wu","email":"","orcid":"","institution":"Hebei Province Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Beibei","middleName":"","lastName":"Wu","suffix":""},{"id":338240559,"identity":"90c246e3-ee44-4005-890d-9278e8917a40","order_by":9,"name":"Yunfeng Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBAC9gYog42Z/+MDhgIJwlp4DkAZfOwMxgYMBqRokeNnMJNgMCDCYTzsvYdf/qi4Y9fGzJBW8cPAInHD7QbGDx9z8GjhOZdmIXHmWTJQy7GbPQYSiRvuHGCWnLkNtxZ7iRwzA8O2w8lszIxtN3hAWm4ksDHz4tHCI//GzCARrIWZrfAPUVokeIwfHGw7bMfGzMbGTJwtPDlmjA1nDgOV8TBLyxhIGM+8kdiM1y887GeMP/6oOGwv33+G8eObijrZvhvJBz98xKMFCNhA0ZfYAOU5NjAwNuBWDAHMH4CEPYxnj0flKBgFo2AUjFAAAG6CTcVm3Vg7AAAAAElFTkSuQmCC","orcid":"","institution":"Hebei University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Yunfeng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-07-24 02:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4791876/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4791876/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00210-024-03476-y","type":"published","date":"2024-10-01T15:58:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62889279,"identity":"22711275-efd4-494b-ad3a-0996b14c490e","added_by":"auto","created_at":"2024-08-20 16:53:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":353468,"visible":true,"origin":"","legend":"\u003cp\u003eTCM information of the ZSTMD. (A) Percentage of medicinal properties. (B) Percentage of medicinal flavour. (C) Meridian attribution of herbs.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/6eb305a0a1e06cfccd8a5c9f.jpg"},{"id":62889788,"identity":"eb8a36aa-a5fb-4aea-ac4d-fa03227aca82","added_by":"auto","created_at":"2024-08-20 17:01:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":795362,"visible":true,"origin":"","legend":"\u003cp\u003ePPI network construction. (A) Venn diagram of the intersection of herb targets and disease targets. (B) PPI network diagram of the intersection targets in the STRING database. (C) Topological analysis diagram of the intersection targets. Inside the blue box is the PPI network graph of the intersection targets, inside the red box is the core cluster screened with the MCOED plug-in, and the black aspect is the key target network graph screened with the CentiScaPe plug-in. (Degree value \u0026gt;71)\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/2da3970cba51f309a8161adc.jpg"},{"id":62890009,"identity":"d7a790b2-f058-4158-8b5c-e3722f8d0a6d","added_by":"auto","created_at":"2024-08-20 17:09:06","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":832636,"visible":true,"origin":"","legend":"\u003cp\u003eGO function and KEGG pathway enrichment analysis of the targets. (A) GO enrichment analysis of intersecting target functions. (B) DO enrichment analysis of intersecting targets. (C) KEGG enrichment analysis of the intersectional target pathways. (D) Network diagram of the KEGG pathway and the targets it contains.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/1e71c20de97a5690abe4cce7.jpg"},{"id":62889272,"identity":"6354696c-56c4-489e-a53c-763866ccffcb","added_by":"auto","created_at":"2024-08-20 16:53:06","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1012933,"visible":true,"origin":"","legend":"\u003cp\u003eThe identification of ZSTMD components related to intersecting targets and the molecular docking of key components to key targets were performed. (A) Herb-component-target network diagram. (B) Component-intersection target network diagram. (C) Visualization of VEGFA-Quercetin binding graphs. (D) Visualization of VEGFA-Kacmpferol binding graphs. (E)Visualization of VEGFA-Beta-sitosterol binding graphs.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/c266c2d0e1aab9439afd6208.jpg"},{"id":62889276,"identity":"8efe6609-73d3-4214-a2cc-8477900fabe2","added_by":"auto","created_at":"2024-08-20 16:53:06","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":294568,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in body weight and the ovarian index in different groups of rats during the experiment. (A)Experimental flow chart. (B) Representative light microscopic HE-stained images of rat vaginal detached cells. (C) Changes in body weight. (D) Changes in the ovarian index. * P＜0.05, *** P＜0.001 versus the CON group. # P＜0.05, ##P＜0.01, ### P＜0.001 versus the MOD group. N=4.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/2ad82e64848381cb31359b4b.jpg"},{"id":62889274,"identity":"b74899d9-0a5c-4115-adab-5e70eeea9c7f","added_by":"auto","created_at":"2024-08-20 16:53:06","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":347107,"visible":true,"origin":"","legend":"\u003cp\u003eZSTMD can promote ovarian blood vessel growth and restore ovarian function through VEGFA targets. (A) Representative light microscopic H\u0026amp;E-stained images of ovarian tissue in different groups. (B) The concentration of E2 was detected by ELISA. (C) Concentration of FSH detected by ELISA. (D) Concentration of LH detected by ELISA. (E) Concentration of AMH detected by ELISA. * \u003cem\u003eP\u003c/em\u003e＜0.05, ** \u003cem\u003eP\u003c/em\u003e＜0.01, *** \u003cem\u003eP\u003c/em\u003e＜0.001 versus the CON group. # \u003cem\u003eP\u003c/em\u003e＜0.05, ##\u003cem\u003eP\u003c/em\u003e＜0.01, ### \u003cem\u003eP\u003c/em\u003e＜0.001 versus the MOD group. N=4.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/59238428703a13b4ec333448.jpg"},{"id":62889278,"identity":"20e26109-c686-4260-954b-eb00a945320c","added_by":"auto","created_at":"2024-08-20 16:53:06","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":7676924,"visible":true,"origin":"","legend":"\u003cp\u003eZSTMD promotes ovarian angiogenesis through VEGFA targeting. (A) The expression of VEGFA and CD31 in the different groups was determined by western blotting. (B) Representative confocal immunofluorescence images of CD31 in the different groups. Nuclei are stained blue, and CD31 is stained red. ** \u003cem\u003eP\u003c/em\u003e＜0.01 versus the CON group. # \u003cem\u003eP\u003c/em\u003e＜0.05, ##\u003cem\u003eP\u003c/em\u003e＜0.01, ### \u003cem\u003eP\u003c/em\u003e＜0.001 versus the MOD group. N=4.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/e5b0bd5cc8cd06842f09c585.jpg"},{"id":62889277,"identity":"4bc93694-7c74-482c-aaa9-628c562c3337","added_by":"auto","created_at":"2024-08-20 16:53:06","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":146124,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of Caspase3 and VEGFA in different groups of KGN cells was determined by western blotting. (A) The expression of caspase3 in KGN cells was determined by western blot after treatment with different concentrations of CTX. (B) The expression of caspase3 in KGN cells after treatment with different concentrations of quercetin was determined by western blotting. (C) The expression of caspase3 and VEGFA in KGN cells was determined by western blot after treatment with different concentrations of quercetin and CTX.\u003c/p\u003e","description":"","filename":"Figure8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/35c12bd69b97d2510b2a5428.jpg"},{"id":66096956,"identity":"87d2d52c-2837-4afc-805a-06fee713085c","added_by":"auto","created_at":"2024-10-07 16:12:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12258392,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4791876/v1/eb6958e9-91fb-4c25-8c29-839949a34df7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Network pharmacological analysis and experimental verification of Zisheng Tongmai decoction in the treatment of Premature ovarian failure","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePremature ovarian failure (POF) is characterized by amenorrhea resulting from follicular depletion or dysfunction in women under 40 years old. It is marked by increased serum concentrations of follicle-stimulating hormone (FSH) and luteinizing hormone (LH), along with decreased levels of estradiol (E2). Clinical manifestations include reproductive endocrine disorders such as prolonged menstrual cycles, amenorrhea, reduced fertility, or infertility. Additionally, some patients may experience menopausal symptoms including hot flashes, night sweats, vaginal dryness, and decreased libido (Wesevich et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Epidemiological surveys indicate that the global prevalence of POF is 3.5%, posing a significant threat to women's reproductive health, particularly among younger women (Li et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The pathogenesis of POF is highly complex. Although hormone replacement therapy (HRT) is a common modern treatment, long-term HRT increases the risks of stroke, heart disease, and pulmonary embolism (Lin et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, there is an urgent need for the development of complementary and alternative therapies for POF.\u003c/p\u003e \u003cp\u003eTraditional Chinese Medicine (TCM) treatment for POF is known for its efficacy and minimal side effects (Fu et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). According to TCM, the etiology of POF primarily involves kidney deficiency, but also spleen deficiency, liver depression, and qi and blood deficiency (Li et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ma et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These deficiencies manifest as loss of appetite, irritability, and poor blood circulation (Wesevich et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Consequently, TCM primarily focuses on tonifying the kidney and nourishing the essence, while also addressing blood tonification, liver drainage, spleen strengthening, and heart nourishment (Li et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). TCM herbs contain various bioactive components that can inhibit apoptosis, reduce oxidative stress, promote follicular development, and improve POF through multiple pathways and targets (Cai et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For example, flavonoids such as quercetin and kaempferol, commonly found in herbs, are known to reduce mitochondrial oxidative stress and inhibit ovarian cell apoptosis (Liu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zheng et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eZSTMD is a traditional formulation derived from the \u0026lsquo;Records of Tradition Chinese and Western Medicine in Combination\u0026rsquo;. It consists of Baizhu (\u003cem\u003ePaeonia lactiflora Pall., Paeoniaceae\u003c/em\u003e), Shanyao (\u003cem\u003eDioscorea opposite Thunb., Dioscoreaceae\u003c/em\u003e), Jineijin (G\u003cem\u003ealli Gigerii Endothelium Coreneum, Animals\u003c/em\u003e), Longyan (\u003cem\u003eDimocarpus longan Lour., Sapindaceae\u003c/em\u003e), Shanzhuyu (\u003cem\u003eCornus officinalis Siebold \u0026amp; Zucc., Cornaceae\u003c/em\u003e), Gouqi (\u003cem\u003eLycium berlandieri Dunal., Solanaceae\u003c/em\u003e), Xuanshen (\u003cem\u003eScrophularia ningpoensis Hemsl., Scrophulariaceae\u003c/em\u003e), Baishao (\u003cem\u003ePaeonia lactiflora Pall., Paeoniaceae\u003c/em\u003e), Taoren (\u003cem\u003ePrunus persica L. Batsch, Rosaceae\u003c/em\u003e), Honghua (\u003cem\u003eCarthamus tinctorius L., Asteraceae\u003c/em\u003e) and Gancao (\u003cem\u003eGlycyrrhiza L., Fabaceae\u003c/em\u003e). ZSTMD is recognized for its ability to nourish blood and promote menstruation, making it a common treatment for conditions such as menorrhagia, reduced appetite, and burning cough in women. Despite its significant therapeutic effects in clinical practice, there is a notable lack of in-depth international research on ZSTMD for POF. Only one study in the China National Knowledge Infrastructure (CNKI) has reported a clinical trial, indicating that ZSTMD effectively treats menstrual stagnation in women with a cure rate of up to 72.73% (Guo, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to elucidate the main components of ZSTMD for the treatment of POF through network pharmacological analysis and experimental validation. We have identified VEGFA as a key target of ZSTMD in treating POF. VEGFA, also known as vascular permeability factor (VPF), plays a crucial role in promoting ovarian vascular growth in POF model rats. It was originally identified as an endothelial growth factor and a regulator of vascular permeability (Claesson-Welsh and Welsh, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e). Therefore, we investigated whether ZSTMD enhances angiogenesis in POF through VEGFA targets at both in vivo and cellular levels.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInformation on the herbs, active ingredients and targets of ZSTMD\u003c/h2\u003e \u003cp\u003eThe Chinese Pharmacopoeia 2020 edition (Commission, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) was consulted to obtain information on the classification and properties of Baizhu, Shanyao, Jineijin, Longyan, Gouqizi, Xuanshen, Baishao, Taoren, Honghua, and Gancao. Data on each herb in ZSTMD were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://tcmspw.com/tcmsp.php\u003c/span\u003e\u003cspan address=\"http://tcmspw.com/tcmsp.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the Traditional Chinese Medicine Integrative Database (TCMID, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bidd.group/TCMID/\u003c/span\u003e\u003cspan address=\"http://bidd.group/TCMID/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The chemical components retrieved were screened for oral bioavailability (OB)\u0026thinsp;\u0026ge;\u0026thinsp;30% and drug-likeness (DL)\u0026thinsp;\u0026ge;\u0026thinsp;0.18. Active compounds without potential target information were excluded. The UniProt database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.uniprot.org/\u003c/span\u003e\u003cspan address=\"https://www.uniprot.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was then utilized to identify target genes corresponding to the target proteins, with filters set to \u0026lsquo;reviewed\u0026rsquo; status and \u0026lsquo;human\u0026rsquo; species.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003ePrediction of potential targets for POF\u003c/h2\u003e \u003cp\u003eThe GeneCards database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was searched for targets associated with POF using the keywords \u0026lsquo;Premature ovarian failure\u0026rsquo; and \u0026lsquo;Premature ovarian insufficiency (POI)\u0026rsquo;. The resulting targets were filtered by taking those that appeared more than twice the median frequency, to identify those more strongly associated with POF. The names of the screened targets were normalized using the UniProt database.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eIntersecting targets of the ZSTMD and POF\u003c/h2\u003e \u003cp\u003eThe targets of ZSTMD and those related to POF and POI were input into Venny2.1.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to generate Venn diagrams, identifying the intersecting targets.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of the protein-protein interaction (PPI) network\u003c/h2\u003e \u003cp\u003eThe intersecting targets were entered into the STRING database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to construct a protein-protein interaction (PPI) network. Free nodes were removed, and the minimum interaction score was set to 0.4. The resulting data were exported and imported into Cytoscape software for network topology analysis. Subnetworks with the highest scores were initially screened using the MCODE plug-in. Subsequently, key targets for ZSTMD treatment of POF, characterized by high degree values, were identified using the CentiScaPe plug-in.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOD, GO and KEGG enrichment analysis\u003c/h2\u003e \u003cp\u003eThe intersecting target information was imported into the DAVID (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database to perform Disease Ontology (DO), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The collected information was then used to create bubble diagrams on the Wbioinformatics web page (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.com.cn/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Network diagrams were also generated using Cytoscape 3.9.0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePrediction of the core components of the ZSTMD\u003c/h2\u003e \u003cp\u003eThe components and corresponding targets identified in ZSTMD were imported into Cytoscape 3.9.0 software to construct an herbal-active component-target network. The intersecting targets were then added to construct an active component-intersecting target network. This network enables the identification of high-frequency components as key components.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMolecular docking\u003c/h2\u003e \u003cp\u003eIn this study, molecular docking was conducted using key target proteins and core components identified through the aforementioned method. The 3D structures of the target proteins were obtained from the RCSB PDB database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Water molecules and native ligands were removed from the target proteins using PyMOL. The target proteins were then imported into AutoDock Tools 1.5.7 for hydrogen addition, charge calculation, and nonpolar hydrogen merging. The results were saved as PDBQT receptor files. Small molecule ligands were downloaded from the TCMSP database in MOL2 format. Hydrogen addition, charge calculation, and nonpolar hydrogen merging were performed in AutoDock Tools 1.5.7, and torsion bonds were set to incorporate nonpolar hydrogens. The results were saved as PDBQT ligand files. The PDBQT structures of the receptor and ligand were imported into AutoDock Tools 1.5.7 to construct docking pockets, ensuring the grid box size could completely encompass the protein. Finally, AutoDock Vina was executed via the CMD command to perform molecular docking, calculate binding energies, and select the model with the lowest binding energy. The results were exported in PDBQT format. These files were then imported into PyMOL for visualization of the hydrogen bonds in the docking model.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003eEight-week-old female SD rats weighing approximately 220 g were purchased from Huafukang Biotechnology Co., Ltd. (Beijing, China). Rats were allowed ad libitum adaptive feeding at a constant temperature of 23\u0026deg;C for one week on a 12-hour day-night cycle. During this period, the estrous cycle of the rats was monitored daily, and those with a normal estrous cycle were selected for the experiment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDrugs and reagents\u003c/h2\u003e \u003cp\u003eZSTMD was procured from the outpatient department of Hebei University of Chinese Medicine. The preparation method entails the removal of water from the decocted herbal liquid using thin-film concentration technology, reverse osmosis technology, and drying techniques such as spray drying, to obtain herbal granules. Each bag of granules weighs approximately 15g. The product complied with Good Manufacturing Practice and Good Laboratory Practice standards. The drugs used were Baizhu (9 g), Shanyao (30 g), Jineijin (6 g), Longyan (18 g), Shanzhuyu (12 g), Gouqi (12g), Xuanshen (9 g), Baishao (9 g), Taoren (6 g), Honghua (4.5 g) and Gancao (6 g). Cyclophosphamide (CTX, 0523188-32, Cayman, Michigan, USA) was used to induce the POF rat model. Estrogen (J20080036) was purchased from Bayer Healthcare Co., Ltd., and was used as a control for chemical drugs. Quercetin (HPLC\u0026thinsp;\u0026gt;\u0026thinsp;99.0%, S2391, Houston, TX, USA) was used to treat KGN cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment of the POF rat model and grouping\u003c/h2\u003e \u003cp\u003eThe POF model was initiated with 50 mg/kg cyclophosphamide on the first day, followed by 8 mg/kg per day for the next two weeks. The rats were observed beyond the initial period, and their weights were recorded weekly. Successful modeling was indicated when the rats\u0026rsquo; estrous cycles were longer than six days. The remaining rats were used as the blank control (CON) group and were injected intraperitoneally with saline. During the experiment, the ZSTMD pellets were administered using distilled water. Drug concentrations for the rats were adjusted based on the conversion of rat to human body surface area. Subsequently, the rats were randomly divided into five groups: the model group (MOD), the ZSTMD low-concentration group (ZSTMD-L, 1.575 g/kg), the ZSTMD high-concentration group (ZSTMD-H, 3.150 g/kg), the estrogen group (E2, 0.0216 g/kg), and the blank control (CON) group. Gavage was performed at the same time each day for 28 days in the ZSTMD-L/H and E2 groups. Continuous estrous cycle testing was performed daily. The MOD and CON groups were gavaged with distilled water. At the end of the treatment, all rats were sacrificed. Blood was collected, and the serum obtained after centrifugation was frozen. The ovaries were removed and weighed. Part of the tissue was stored in a -80\u0026deg;C refrigerator, and the other part was fixed in 4% paraformaldehyde (20220927, Biosharp, Guangzhou, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eHematoxylin \u0026amp; eosin (H\u0026amp;E) staining and immunofluorescence staining\u003c/h2\u003e \u003cp\u003eOvarian tissue samples from each mouse were fixed in 4% formalin saline solution, embedded in paraffin, and cut into 5 \u0026micro;m sections. After dewaxing and rehydration, the tissue sections were stained with hematoxylin solution (C211107, Baso, Beijing, China) for 5 minutes, followed by soaking in different concentrations of ethanol five times, and rinsing with distilled water. The sections were then stained with eosin (C220501, Baso, Beijing, China) for 3 minutes. Xylene was used to dehydrate the sections in a graded series of alcohol. Immunofluorescence staining for the vascular marker CD31 was performed. Goat serum (G1208, Servicebio, Wuhan, China) diluted 20-fold in PBS was added to the sections, which were incubated for 5 minutes at room temperature. The sections were then incubated overnight at 4\u0026deg;C with a CD31 antibody (GB21303, Servicebio, Wuhan, China). The next day, the sections were incubated with a secondary antibody and stained with DAPI (G1012, Servicebio, Wuhan, China). Images were acquired by fluorescence microscopy (DMi8, Leica, Solms, Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eELISA\u003c/h2\u003e \u003cp\u003eAfter the treatment, blood samples were collected from the rats. Serum was separated by centrifugation at 1500 rpm for 15 minutes at 4\u0026deg;C. Serum concentrations of AMH, E2, and FSH were quantified using enzyme-linked immunosorbent assay (ELISA) kits (Shanghai Enzyme Biotechnology Co., Ltd., Shanghai, China). The assays were performed in strict accordance with the manufacturer\u0026rsquo;s protocols. The optical density (OD) was measured at 450 nm using an enzyme-linked immunosorbent assay reader (RT-6100, Rayto, Shenzhen, China). Hormone concentrations were then calculated based on the corresponding standard curves.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and establishment of the POF model\u003c/h2\u003e \u003cp\u003eThe KGN human granulosa cell line was purchased from Starfish Biotechnology Co., Ltd. (TCH-C230, HyCyte, Suzhou, China). A total of 2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells were inoculated in 100 mm Petri dishes (TCH-G230, HyCyte, Suzhou, China) and cultured in an incubator at 37\u0026deg;C with humidified air containing 5% CO2. The culture medium was changed every other day. KGN cells were treated with various concentrations (20, 50, 100, 150, and 200 \u0026micro;g/mL) of CTX to determine the optimal concentration. Cells were pretreated with different concentrations (30, 60, and 100 \u0026micro;M) of quercetin followed by treatment with 100 \u0026micro;g/mL of CTX.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eA protein assay kit was used to determine the protein concentration of each sample. Ovarian tissue proteins were extracted according to the instructions of the Total Protein Extraction Kit, transferred to PVDF membranes, blocked in 5% skim milk powder for 1 hour, and then incubated overnight at 4\u0026deg;C with primary antibodies including anti-VEGFA (1:1000, bs1313R, Bioss Antibodies, Beijing, China), anti-CD31 (1:1000, bsm10825M, Bioss Antibodies, Beijing, China), anti-caspase3 (1:1000, p42574, Bioworld Technology, Inc., MN, USA), and β-actin (1:1000, bs55208R, Bioss Antibodies, Beijing, China). The next day, the membranes were incubated with the corresponding secondary antibodies for 1 hour at room temperature. Bands were detected using the ECL detection kit (Applygen Technologies Inc., Beijing, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS 20.0 statistical software (SPSS Inc., Chicago, IL, USA). All data are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. P-values were analyzed using Student\u0026rsquo;s t-test, with a significant difference defined as P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eInformation on the herbs, active ingredients and targets of ZSTMD\u003c/h2\u003e \u003cp\u003eMost of the herbs in ZSTMD have a sweet taste, accounting for 42.86% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), and the majority of the nature are calm, accounting for 45.45% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Herbs attributed to the liver and spleen meridians were the most abundant in ZSTMD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Specific information on the Chinese medicines used is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A search of TCMSP, TCMID, and the literature revealed Baizhu with 4 constituents, Shanyao with 14 constituents, Longyan with 3 constituents, Shanzhuyu with 4 constituents, Gouqi with 40 constituents, Xuanshen with 9 constituents, Baishao with 4 constituents, Taoren with 21 constituents, Honghua with 20 constituents, and Gancao with 40 constituents. Among them, 9 common components were identified. After combining and deduplicating the data, 203 active ingredients acting on a total of 571 targets were identified.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChannel Tropism, Properties and Flavour of TCM in ZSTMD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHerbs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChannel Tropism\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProperty and flavor\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaizhu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpleen,Stomach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWarm, Bitter, Sweet,\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShanyao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpleen, Lung, Kidney\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm, Sweet\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJineijing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpleen, Stomach, Small Intestine, Bladder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm, Sweet\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongyan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeart, Spleen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWarm, Sweet\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShanzhuyu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver,Kidney\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWarm,Sour, Astringent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGouqi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver,Kidney\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm, Sweet\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eXuanshen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLung,Large Intestine,Liver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCold, Bitter, Salty\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaishao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiver,Spleen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCold,Bitter,Sour\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaoren\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeart, Liver, Lung, Large Intestine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm, Bitter\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHonghua\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeart Liver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWarm, Bitter\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGancao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpleen,Lung,Stomach,Heart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCalm, Sweet\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of intersection targets\u003c/h2\u003e \u003cp\u003eFrom the GeneCards database, 5082 targets associated with POF and 5943 targets associated with POI were initially screened. Secondary screening based on the median relevance score yielded 1657 and 1556 targets, respectively. A Venn diagram was plotted to show the 568 targets acting on the active ingredient of ZSTMD and the above targets, revealing 209 intersection targets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePPI network construction\u003c/h2\u003e \u003cp\u003eThe PPI network with 206 nodes and 1374 edges was constructed by importing 209 intersection targets into the STRING database (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The minimum required interaction score was set to 0.4. The data obtained from STRING were imported into Cytoscape 3.9.0 software for topology analysis. First, we used the MCODE plug-in to filter the subnetwork with the highest score of 59 as the core cluster, obtaining a network of 36 nodes and 628 edges. Then, we used the CentiScaPe plug-in to filter the nine targets with the highest degree values (degree\u0026thinsp;\u0026gt;\u0026thinsp;71), resulting in a network of 9 nodes and 36 edges (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). A total of nine key targets were identified, including VEGFA, STAT3, CASP3, TP53, GAPDH, JUN, HIF1A, ALB, and AKT1. The literature was reviewed to understand the functions of these targets and identify key targets for the treatment of POF. These targets may be critical for the treatment of POF with ZSTMD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eGO, DO and KEGG pathway enrichment analysis of the targets\u003c/h2\u003e \u003cp\u003eGO, DO, and KEGG enrichment analyses were performed on the intersecting targets using the DAVID platform. GO analyses included biological process (BP), cellular component (CC), and molecular function (MF) analyses. A total of 3963 statistically significant GO terms were obtained in this study, including 1053 BP items such as positive regulation of gene expression, negative regulation of apoptotic process, drug response, hypoxia response, aging, and estradiol response. Additionally, 116 CC terms were identified, such as extracellular space, macromolecular complex, extracellular region, cytoplasm, cytosol, and nucleoplasm. For MF, 200 terms were identified, including enzyme binding, identical protein binding, protein kinase activity, protein binding, protein tyrosine kinase activity, and protein kinase binding. The top 10 genes were selected for visualization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). DO terms identified 519 diseases, such as reperfusion injury, depressive disorder, breast carcinoma, hypertensive disease, and mammary neoplasms. The top 20 were selected for visualization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). 174 KEGG items were identified, and the top 50 pathways were selected for functional categorization. Pathways related to oxidative stress, apoptosis, and inflammation were screened, including the PI3K-Akt, DIAGRAMK, FoxO, TNF, and HIF-1 signaling pathways, as well as pathways related to cancer, the AGE-RAGE signaling pathway in diabetic complications, lipids, hepatitis B, and microRNAs in cancer. The top 20 pathways were selected for visualization (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Thirteen pathways associated with these functions were imported into Cytoscape 3.9.0 software with the names of their constituent genes, and network diagrams were generated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). These results suggest that POF is a multitarget and multipathway disease control agent.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eConstruction of the active ingredient-intersection target network\u003c/h2\u003e \u003cp\u003eCytoscape software was used to visualize the network of active ingredients and intersection targets related to the action of ZSTMD. First, the Chinese herbal medicine-ingredient-target sequence was imported into Cytoscape software to construct a Chinese herbal medicine-ingredient-target visualization network (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Then, the intersecting genes were imported into the software and screened for active ingredients connected to these genes, resulting in 199 connections. This was used to construct the component-intersection target visualization network (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). The top 5 core ingredients were identified based on degree values, including quercetin, kaempferol, beta-sitosterol, luteolin, and hancinol. Information on the top 5 ingredients and their degree values is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The top three components, quercetin (MOL000098), kaempferol (MOL000422), and beta-sitosterol (MOL000358), are common to multiple herbs and were selected as candidate ligands for molecular docking validation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInformation on the core ingredients of the top 5 degree values of ZSTMD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMOL Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDegree value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHonghua, Gouqizi, Gancao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHonghua, Gouqizi, Baishao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta-sitosterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eXuanshen, Taoren, Honghua, Gouqizi, Shanzhuyu, Baishao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL000006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLuteolin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHonghua\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOL005429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHancinol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eShanyao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eMolecular docking results\u003c/h2\u003e \u003cp\u003eThe key target VEGFA (ID: 4QAF), identified through the PPI network, was molecularly docked with three candidate components: quercetin, kaempferol, and beta-sitosterol. The VEGFA suppressor Emvododstat was used as a positive control. The results showed that VEGFA had good affinity for quercetin, kaempferol, and beta-sitosterol, with binding energies of -7.14, -5.13, and \u0026minus;\u0026thinsp;7.47 kcal/mol, respectively, all below \u0026minus;\u0026thinsp;5.00 kcal/mol (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The active sites of the ligands and receptor in these binding models were stabilized by multiple hydrogen bonds (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-E). Quercetin interacts with the amino acid residues TYR-25, ILE-37, ASN-62, and TRP-144 of VEGFA; kaempferol binds to the amino acid residues GLY-112, GLN-89, HIS-86, and LYS-58; and beta-sitosterol binds to the PRO-28 residue of VEGFA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-E). These modeling results suggest that these compounds are key pharmacological components of ZSTMD for the treatment of POF.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpecific information on the free energy of ligand-receptor binding\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarget protein\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompound name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffinity (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eVEGF(PDB ID: 4QAF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmvododstat (Control)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeta-sitosterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003ePOF rat model test\u003c/h2\u003e \u003cp\u003eH\u0026amp;E staining of vaginal exfoliated cells showed nucleated, rounded epithelial cells in proestrus; large, cherry-like keratinized epithelial exfoliative cells during estrus; and equal numbers of nucleated cells, keratinized cells, and leukocytes in metestrus. During diestrus, most leukocytes were stained blue and few cells were stained pink (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Normally, rats have a 4-day estrous cycle. Modeling is considered successful when the estrous cycle is prolonged to 6 days or disrupted. In this experiment, most of the rats in the MOD group were in diestrus compared to the CON group, and most of their vaginal exfoliated cells were blue-stained leukocytes. These results indicate that the POF model was successfully established.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eZSTMD contributed to the improvement of POF status\u003c/h2\u003e \u003cp\u003eAfter the start of modeling, we found that the weight gain of the rats slowed down and even became negative. However, after treatment, the weight of the rats in the ZSTMD-L/H and E2 groups began to increase slowly, with growth accelerating after two weeks. The weight of the model group decreased significantly one week after modeling, and then began to rise again two weeks post-modeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). At the end of the experiment, the weight of the rat ovaries was measured, and the ovarian index was calculated. Analysis showed that the ovarian index was significantly higher in the CON and ZSTMD-L/H groups compared to the MOD group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001 and \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eZSTMD improves ovarian function in a POF rat model\u003c/h2\u003e \u003cp\u003eMicroscopic observation of H\u0026amp;E-stained ovaries from different groups revealed that the ovaries in the blank group had multiple developed dominant follicles, whereas those in the model group had only small atretic or undeveloped follicles. After treatment with traditional Chinese medicine or Western medicine, well-developed dominant follicles appeared in the ovaries (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Measurement of serum hormones in each group revealed a significant increase in E2 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and AMH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), and a significant decrease in both FSH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01) and LH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) in the ZSTMD-H group (Fig.s 6B-E). The effects of ZSTMD-L and E2 treatments were not as pronounced as those of the ZSTMD-H group. The E2 group also showed significant effects on E2 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), FSH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), LH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), and AMH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-E). The ZSTMD-L group showed significant elevations only in FSH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01) and LH (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC-D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eZSTMD can promote ovarian blood vessel growth through VEGFA targets\u003c/h2\u003e \u003cp\u003eTo further investigate the specific mechanism by which ZSTMD improves POF, we examined the expression of VEGFA and CD31 in ovarian tissues using Western blotting. The results revealed that the expression of VEGFA and CD31, a vascular endothelial marker, increased following treatment with ZSTMD (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). In addition, immunofluorescence staining of ovarian tissues showed significantly reduced vascular density in the MOD group compared to the CON group, with an increase in vascular density following treatment with ZSTMD and E2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). These results suggest that ZSTMD could act directly on VEGFA targets to promote ovarian angiogenesis, thereby improving POF.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eQuercetin suppresses apoptosis and promotes VEGFA protein expression in CTX-treated KGN cells\u003c/h2\u003e \u003cp\u003eWe obtained granulosa cells for POF studies by treating KGN cells with CTX. The increase in apoptotic protein caspase3 was not significant at concentrations of 20 and 50 \u0026micro;g/ml, but it increased significantly when the concentration reached 100 \u0026micro;g/ml and above (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). To investigate the cytotoxicity of quercetin, we treated KGN cells with different concentrations of quercetin for 24 hours and found no increase in apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Subsequently, KGN cells were pretreated with 30, 60, and 100 \u0026micro;M quercetin for 1 hour, followed by CTX treatment for 24 hours. The results showed a significant increase in caspase3 protein expression and a significant decrease in VEGFA protein expression in the CTX group compared to the CON group (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). Quercetin treatment significantly decreased caspase3 protein expression and increased VEGFA protein expression in a concentration-dependent manner (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). Cellular experiments demonstrated that quercetin could suppress KGN cell apoptosis by targeting VEGFA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe main findings of this study include (a) ZSTMD improved ovarian function and related symptoms in POF model rats. (b) ZSTMD promoted the protein expression of VEGFA and CD31, (c) Quercetin suppressed CTX-induced apoptosis in KGN cells and promoted VEGFA protein expression, and (d) ZSTMD and its main constituent quercetin were found to act on VEGFA targets to improve aging ovaries by promoting blood vessel growth through network pharmacology, molecular docking, and experimental validation.\u003c/p\u003e \u003cp\u003eZSTMD is a well-known herbal tonic clinically proven to have therapeutic effects and is widely used to treat amenorrhea. However, no pharmacological analysis of this formula for the treatment of POF has been conducted. In this study,we analize the taste, nature and meridian tropism of the herbs in ZSTMD revealed that the majority of these herbs exhibits a sweet taste and calm nature, targeting the liver and spleen meridians. This aligns with traditional Chinese medicine principles for treating POF, which focus on nourishing the liver and spleen, promoting blood flow, and stabilizing the body's internal environment (Li et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A total of 199 active ingredients and 209 intersecting genes of ZSTMD and POF were obtained by screening herbs from the TCMSP database. The active ingredient-target network analysis of the herbal medicines showed that quercetin, kaempferol, beta-sitosterol, luteolin, and hancinol were connected to multiple targets in the network diagram. The first three of these are common to various herbal medicines, and they all belong to the group of natural flavonoid compounds with mechanisms of action including anti-SARS-CoV-2, antioxidant, anticancer, anti-aging, antiviral, and anti-inflammatory activities (Sharma et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Several studies have shown that quercetin acts as an inhibitor of oxidative stress in the treatment of POF. Quercetin significantly increased the expression of AMH, E2, superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) through the PI3K/Akt/FOXO3 signaling pathway (Zheng et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAfter in-depth analysis of GO, DO, and KEGG, we found that the effects of ZSTMD on POF were mainly related to oxidative stress, apoptosis, inflammation, and hypoxia, and the involved pathways included PI3K-Akt, DIAGRAMK, FoxO, TNF, and HIF-1 signaling pathways. The PI3K-Akt pathway was the most involved. Several studies have demonstrated that the PI3K-Akt pathway induces oxidative stress, granulosa cell apoptosis, and autophagy in the ovary (Dai et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Han et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zheng et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo explore the core targets of POF in ZSTMD, a protein-protein interaction (PPI) network was constructed, revealing that VEGFA, STAT3, CASP3, TP53, GAPDH, JUN, HIF1A, ALB, and AKT1, especially VEGFA, which is highly enriched, may be the core targets involved in the treatment of POF by ZSTMD. These proteins are involved in the processes of oxidative stress, apoptosis, inflammation, and senescence. VEGFA is one of the major proangiogenic factors involved in regulating ovarian angiogenesis (Ferrara et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), and its role in regulating follicular development has been extensively studied (Guzm\u0026aacute;n et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; McFee et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The vascular system has a strong influence on the formation of ovarian structures. The early developmental processes of ovarian cord formation, primordial follicle assembly, and follicular activation all begin in ovarian regions closely associated with a highly vascular medulla (McFee and Cupp, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Additionally, abnormal angiogenesis is involved in the induction and development of pathological ovaries, such as in polycystic ovary syndrome and ovarian cancer (Xie et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Chemotherapeutic agents such as cyclophosphamide have been shown to induce ovarian failure in young patients with breast cancer, possibly through vascular injury (Ben-Aharon et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Therefore, VEGFA is necessary to improve oocyte competence, increase vascularity, and maintain functional ovarian activity.\u003c/p\u003e \u003cp\u003eIn the present experiments, ZSTMD promoted vascular growth, body weight, and ovarian index after CTX induction by targeting VEGFA, as evidenced by increased expression of VEGFA and CD31 proteins, as well as increased vessel density. In addition, E2 and AMH levels increased significantly while FSH and LH levels decreased significantly after treatment. Mingmin Zhang\u0026rsquo;s team reversed CTX-induced atrophy of the ovarian vasculature in a POF model and upregulated VEGFA expression using Si-Wu-Tang and umbilical cord-derived MSCs, respectively (Liu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021a\u003c/span\u003e). These findings are consistent with the results of our experiments.\u003c/p\u003e \u003cp\u003eMolecular docking results showed that the three main active components of ZSTMD had strong binding affinities with VEGFA. Among the active components, quercetin has more hydrogen bond donors and acceptors, facilitating the formation of hydrogen bonds with targets and resulting in lower binding energy and more stable binding. Therefore, we pretreated KGN cells with quercetin for 1 hour and subsequently treated them with CTX for 24 hours. The results showed that quercetin suppressed CTX-induced apoptosis and promoted VEGFA protein expression. We demonstrated in vivo and in vitro that ZSTMD and its main component, quercetin, can target VEGFA to promote ovarian angiogenesis and improve POF.\u003c/p\u003e \u003cp\u003eThere remains considerable ambiguity regarding the role of quercetin in promoting angiogenesis. Several studies have demonstrated that flavonoids, such as quercetin, have a protective effect on tissue endothelial cells by promoting angiogenesis and blood reperfusion (Li et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sumi et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, other studies have found that quercetin suppresses VEGFA and angiogenesis in contexts such as allergic diseases and tumors (Oh et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Okumo et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These discrepancies may be related to the concentration of quercetin used and the specific mechanisms of action, necessitating further studies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our study is the first to analyze the pharmacological components of ZSTMD and demonstrate that it can promote the recovery of ovarian function in POF. Specifically, ZSTMD reversed CTX-induced ovarian vascular atrophy in POF by targeting VEGFA, thereby improving ovarian function. Quercetin, a major component of ZSTMD, suppressed CTX-induced apoptosis in KGN cells and promoted VEGFA protein expression. Thus, we demonstrated that ZSTMD and quercetin could be potential treatments for POF by promoting ovarian blood vessel growth. These findings provide new insights into the treatment of POF with traditional Chinese medicine.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported financially by the Hebei province Department of Human Resources (c20210358) and Social Security and Hebei Traditional Chinese Medicine Administration (2017010).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions:\u0026nbsp;\u003c/strong\u003eJiaru Wu designed the study, supervised the data collection; Mengjie Wen, Zecheng Wang, Xinyue Jin and Chenxu Liu performed the experiments. Kun Yu, Qiuhang Song, Guohong Zhang and Beibei Wu analyzed the data, interpreted the data; Yunfeng Li prepare the manuscript for publication and reviewed the draft of the manuscript. All authors have read and approved the manuscript. The authors declare that all data were generated in-house and that no paper mill was used.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003e This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Hebei University of Chinese Medicine (Date:2024.06.1 / No: DWLL202406001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eAll data supporting the article is provided in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval:\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBen-Aharon I, Meizner I, Granot T, Uri S, Hasky N, Rizel S, Yerushalmi R, Sulkes A and Stemmer SM (2012) Chemotherapy-induced ovarian failure as a prototype for acute vascular toxicity. \u003cem\u003eOncologist\u003c/em\u003e 17:1386-1393 doi: 10.1634/theoncologist.2012-0172.\u003c/li\u003e\n\u003cli\u003eCai L, Zong DK, Tong GQ and Li L (2021) Apoptotic mechanism of premature ovarian failure and rescue effect of Traditional Chinese Medicine: a review. \u003cem\u003eJ Tradit Chin Med\u003c/em\u003e 41:492-498 doi: 10.19852/j.cnki.jtcm.2021.03.017.\u003c/li\u003e\n\u003cli\u003eClaesson-Welsh L and Welsh M (2013) VEGFA and tumour angiogenesis. \u003cem\u003eJ Intern Med\u003c/em\u003e 273:114-127 doi: 10.1111/joim.12019.\u003c/li\u003e\n\u003cli\u003eCommission CP (2020) \u003cem\u003ethe Chinese Pharmacopoeia 2020 edition\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eDai W, Yang H, Xu B, He T, Liu L, Ma X, Ma J, Yang G, Si R, Pei X, Du X and Fu X (2023) Human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) alleviate excessive autophagy of ovarian granular cells through VEGFA/PI3K/AKT/mTOR pathway in premature ovarian failure rat model. \u003cem\u003eJ Ovarian Res\u003c/em\u003e 16:198 doi: 10.1186/s13048-023-01278-z.\u003c/li\u003e\n\u003cli\u003eFerrara N, Gerber HP and LeCouter J (2003) The biology of VEGF and its receptors. \u003cem\u003eNat Med\u003c/em\u003e 9:669-676 doi: 10.1038/nm0603-669.\u003c/li\u003e\n\u003cli\u003eFu Y, Ding DN, Shen Y, Jia LY, Yan MY, Wei W, Song CH and Han FJ (2022) Complementary and Alternative Medicine for Premature Ovarian Insufficiency: A Review of Utilization and Mechanisms. \u003cem\u003eEvid Based Complement Alternat Med\u003c/em\u003e 2022:9053930 doi: 10.1155/2022/9053930.\u003c/li\u003e\n\u003cli\u003eGuo Y (2014) Zisheng Tongmai Decoction in treating stagnation of too litte menstrual blood-stasis syndrome: a clinical observation [in Chinese], in \u003cem\u003eHeilongjiang University of Chinese Medicine\u003c/em\u003e, Heilongjiang, China.\u003c/li\u003e\n\u003cli\u003eGuzm\u0026aacute;n A, Hern\u0026aacute;ndez-Coronado CG, Guti\u0026eacute;rrez CG and Rosales-Torres AM (2023) The vascular endothelial growth factor (VEGF) system as a key regulator of ovarian follicle angiogenesis and growth. \u003cem\u003eMol Reprod Dev\u003c/em\u003e 90:201-217 doi: 10.1002/mrd.23683.\u003c/li\u003e\n\u003cli\u003eHan Y, Yao R, Yang Z, Li S, Meng W, Zhang Y, Zhang Y and Luo H (2022) Interleukin-4 activates the PI3K/AKT signaling to promote apoptosis and inhibit the proliferation of granulosa cells. \u003cem\u003eExp Cell Res\u003c/em\u003e 412:113002 doi: 10.1016/j.yexcr.2021.113002.\u003c/li\u003e\n\u003cli\u003eLi HF, Shen QH, Chen WJ, Chen WM, Feng ZF and Yu LY (2020) Efficacy of Traditional Chinese Medicine Tonifying Kidney (Bushen) and Activating Blood (Huoxue) Prescription for Premature Ovarian Insufficiency: A Systematic Review and Meta-Analysis. \u003cem\u003eEvid Based Complement Alternat Med\u003c/em\u003e 2020:1789304 doi: 10.1155/2020/1789304.\u003c/li\u003e\n\u003cli\u003eLi M, Xiao YB, Wei L, Liu Q, Liu PY and Yao JF (2022) Beneficial Effects of Traditional Chinese Medicine in the Treatment of Premature Ovarian Failure. \u003cem\u003eEvid Based Complement Alternat Med\u003c/em\u003e 2022:5413504 doi: 10.1155/2022/5413504.\u003c/li\u003e\n\u003cli\u003eLi MT, Ke J, Guo SF, Wu Y, Bian YF, Shan LL, Liu QY, Huo YJ, Guo C, Liu MY, Liu YJ and Han Y (2021) The Protective Effect of Quercetin on Endothelial Cells Injured by Hypoxia and Reoxygenation. \u003cem\u003eFront Pharmacol\u003c/em\u003e 12:732874 doi: 10.3389/fphar.2021.732874.\u003c/li\u003e\n\u003cli\u003eLi X, Xu X, Wang J, Yu H, Wang X, Yang H, Xu H, Tang S, Li Y, Yang L, Huang L, Wang Y and Yang S (2012) A system-level investigation into the mechanisms of Chinese Traditional Medicine: Compound Danshen Formula for cardiovascular disease treatment. \u003cem\u003ePLoS One\u003c/em\u003e 7:e43918 doi: 10.1371/journal.pone.0043918.\u003c/li\u003e\n\u003cli\u003eLin J, Wu D, Jia L, Liang M, Liu S, Qin Z, Zhang J, Han Y, Liu S and Zhang Y (2021) The Treatment of Complementary and Alternative Medicine on Premature Ovarian Failure. \u003cem\u003eEvid Based Complement Alternat Med\u003c/em\u003e 2021:6677767 doi: 10.1155/2021/6677767.\u003c/li\u003e\n\u003cli\u003eLiu H, Yang H, Qin Z, Chen Y, Yu H, Li W, Zhu X, Cai J, Chen J and Zhang M (2021) Exploration of the Danggui Buxue Decoction Mechanism Regulating the Balance of ESR and AR in the TP53-AKT Signaling Pathway in the Prevention and Treatment of POF. \u003cem\u003eEvid Based Complement Alternat Med\u003c/em\u003e 2021:4862164 doi: 10.1155/2021/4862164.\u003c/li\u003e\n\u003cli\u003eLiu X, Song Y, Zhou F, Zhang C, Li F, Hu R, Ma W, Song K, Tang Z and Zhang M (2023) Network and experimental pharmacology on mechanism of Si-Wu-tang improving ovarian function in a mouse model of premature ovarian failure induced by cyclophosphamide. \u003cem\u003eJ Ethnopharmacol\u003c/em\u003e 301:115842 doi: 10.1016/j.jep.2022.115842.\u003c/li\u003e\n\u003cli\u003eMa K, Wang KL and Chen YX (2019) [Infertility caused by salpingitis treated based on theory of kidney deficiency and blood stasis]. \u003cem\u003eZhongguo Zhong Yao Za Zhi\u003c/em\u003e 44:1099-1103 doi: 10.19540/j.cnki.cjcmm.20181225.004.\u003c/li\u003e\n\u003cli\u003eMcFee RM and Cupp AS (2013) Vascular contributions to early ovarian development: potential roles of VEGFA isoforms. \u003cem\u003eReprod Fertil Dev\u003c/em\u003e 25:333-342 doi: 10.1071/rd12134.\u003c/li\u003e\n\u003cli\u003eMcFee RM, Rozell TG and Cupp AS (2012) The balance of proangiogenic and antiangiogenic VEGFA isoforms regulate follicle development. \u003cem\u003eCell Tissue Res\u003c/em\u003e 349:635-647 doi: 10.1007/s00441-012-1330-y.\u003c/li\u003e\n\u003cli\u003eOh SJ, Kim O, Lee JS, Kim JA, Kim MR, Choi HS, Shim JH, Kang KW and Kim YC (2010) Inhibition of angiogenesis by quercetin in tamoxifen-resistant breast cancer cells. \u003cem\u003eFood Chem Toxicol\u003c/em\u003e 48:3227-3234 doi: 10.1016/j.fct.2010.08.028.\u003c/li\u003e\n\u003cli\u003eOkumo T, Furuta A, Kimura T, Yusa K, Asano K and Sunagawa M (2021) Inhibition of Angiogenic Factor Productions by Quercetin In Vitro and In Vivo. \u003cem\u003eMedicines (Basel)\u003c/em\u003e 8 doi: 10.3390/medicines8050022.\u003c/li\u003e\n\u003cli\u003eSharma N, Biswas S, Al-Dayan N, Alhegaili AS and Sarwat M (2021) Antioxidant Role of Kaempferol in Prevention of Hepatocellular Carcinoma. \u003cem\u003eAntioxidants (Basel)\u003c/em\u003e 10 doi: 10.3390/antiox10091419.\u003c/li\u003e\n\u003cli\u003eSumi M, Tateishi N, Shibata H, Ohki T and Sata M (2013) Quercetin glucosides promote ischemia-induced angiogenesis, but do not promote tumor growth. \u003cem\u003eLife Sci\u003c/em\u003e 93:814-819 doi: 10.1016/j.lfs.2013.09.005.\u003c/li\u003e\n\u003cli\u003eWang G, Wang Y, Yao L, Gu W, Zhao S, Shen Z, Lin Z, Liu W and Yan T (2022) Pharmacological Activity of Quercetin: An Updated Review. \u003cem\u003eEvid Based Complement Alternat Med\u003c/em\u003e 2022:3997190 doi: 10.1155/2022/3997190.\u003c/li\u003e\n\u003cli\u003eWang H, Chen L, Zhang X, Xu L, Xie B, Shi H, Duan Z, Zhang H and Ren F (2019) Kaempferol protects mice from d-GalN/LPS-induced acute liver failure by regulating the ER stress-Grp78-CHOP signaling pathway. \u003cem\u003eBiomed Pharmacother\u003c/em\u003e 111:468-475 doi: 10.1016/j.biopha.2018.12.105.\u003c/li\u003e\n\u003cli\u003eWesevich V, Kellen AN and Pal L (2020) Recent advances in understanding primary ovarian insufficiency. \u003cem\u003eF1000Res\u003c/em\u003e 9 doi: 10.12688/f1000research.26423.1.\u003c/li\u003e\n\u003cli\u003eXie Q, Cheng Z, Chen X, Lobe CG and Liu J (2017) The role of Notch signalling in ovarian angiogenesis. \u003cem\u003eJ Ovarian Res\u003c/em\u003e 10:13 doi: 10.1186/s13048-017-0308-5.\u003c/li\u003e\n\u003cli\u003eZheng S, Ma M, Chen Y and Li M (2022) Effects of quercetin on ovarian function and regulation of the ovarian PI3K/Akt/FoxO3a signalling pathway and oxidative stress in a rat model of cyclophosphamide-induced premature ovarian failure. \u003cem\u003eBasic Clin Pharmacol Toxicol\u003c/em\u003e 130:240-253 doi: 10.1111/bcpt.13696.\u003c/li\u003e\n\u003cli\u003eZhou F, Song Y, Liu X, Zhang C, Li F, Hu R, Huang Y, Ma W, Song K and Zhang M (2021a) Si-Wu-Tang facilitates ovarian function through improving ovarian microenvironment and angiogenesis in a mouse model of premature ovarian failure. \u003cem\u003eJ Ethnopharmacol\u003c/em\u003e 280:114431 doi: 10.1016/j.jep.2021.114431.\u003c/li\u003e\n\u003cli\u003eZhou Y, Zhou J, Xu X, Du F, Nie M, Hu L, Ma Y, Liu M, Yu S, Zhang J and Chen Y (2021b) Matrigel/Umbilical Cord-Derived Mesenchymal Stem Cells Promote Granulosa Cell Proliferation and Ovarian Vascularization in a Mouse Model of Premature Ovarian Failure. \u003cem\u003eStem Cells Dev\u003c/em\u003e 30:782-796 doi: 10.1089/scd.2021.0005.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"naunyn-schmiedebergs-archives-of-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nsap","sideBox":"Learn more about [Naunyn-Schmiedeberg's Archives of Pharmacology](https://www.springer.com/journal/210)","snPcode":"210","submissionUrl":"https://submission.nature.com/new-submission/210/3","title":"Naunyn-Schmiedeberg's Archives of Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Network pharmacology, Zisheng Tongmai decoction, Quercetin, VEGFA, Premature ovarian failure, KGN cells","lastPublishedDoi":"10.21203/rs.3.rs-4791876/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4791876/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003ePremature ovarian failure (POF) is a disease that seriously jeopardizes women's physical and mental health worldwide. Zisheng Tongmai decoction (ZSTMD), a famous Traditional Chinese Medicine (TCM) formula, has a marked effect on the clinical treatment of POF. This study investigated the potential mechanism of ZSTMD to improve POF through network pharmacology and experimental validation.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe active components, key targets and potential mechanisms of ZSTMD against POF were predicted by network pharmacology and molecular docking. The POF model was induced in rats by cyclophosphamide (CTX) and subsequently gavaged with different doses of ZSTMD. KGN cells were treated with different concentrations of quercetin and CTX. Histopathological were observed via hematoxylin and eosin (H\u0026amp;E) staining and immunofluorescence staining. Serum estrogen levels were detected via ELISA. Protein expression was detected via Western blotting.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe identified quercetin as the main active ingredients targeting VEGFA. Molecular docking showed that VEGFA interacted well with the main active components of ZSTMD. In vivo experiments, ZSTMD significantly increased body weight and the ovarian index, significantly increased E2 and AMH, and decreased FSH and LH in POF rats. Histologic results showed that ZSTMD increased the number of follicles and vascular density in the ovary. It also increased VEGFA and CD31 protein expression. In vitro experiments, quercetin suppressed CTX-induced apoptosis in KGN cells and increased VEGFA protein expression.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eOur study demonstrated that ZSTMD improves POF by promoting angiogenesis through VEGFA target.\u003c/p\u003e","manuscriptTitle":"Network pharmacological analysis and experimental verification of Zisheng Tongmai decoction in the treatment of Premature ovarian failure","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-20 16:53:01","doi":"10.21203/rs.3.rs-4791876/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-09T15:23:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-09T12:41:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"108968302575687219411316428219298287238","date":"2024-08-06T07:35:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76129114022966220696840422430101606970","date":"2024-07-24T19:32:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-24T18:39:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-24T05:51:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-24T05:51:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Naunyn-Schmiedeberg's Archives of Pharmacology","date":"2024-07-24T02:44:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"naunyn-schmiedebergs-archives-of-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nsap","sideBox":"Learn more about [Naunyn-Schmiedeberg's Archives of Pharmacology](https://www.springer.com/journal/210)","snPcode":"210","submissionUrl":"https://submission.nature.com/new-submission/210/3","title":"Naunyn-Schmiedeberg's Archives of Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"50fc90a5-d9cc-4212-a504-86bf1e817147","owner":[],"postedDate":"August 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T16:04:14+00:00","versionOfRecord":{"articleIdentity":"rs-4791876","link":"https://doi.org/10.1007/s00210-024-03476-y","journal":{"identity":"naunyn-schmiedebergs-archives-of-pharmacology","isVorOnly":false,"title":"Naunyn-Schmiedeberg's Archives of Pharmacology"},"publishedOn":"2024-10-01 15:58:02","publishedOnDateReadable":"October 1st, 2024"},"versionCreatedAt":"2024-08-20 16:53:01","video":"","vorDoi":"10.1007/s00210-024-03476-y","vorDoiUrl":"https://doi.org/10.1007/s00210-024-03476-y","workflowStages":[]},"version":"v1","identity":"rs-4791876","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4791876","identity":"rs-4791876","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}