Investigation of Anti-osteoporosis Mechanisms of Rehmanniae Radix Preparata Based on Network Pharmacology and Experimental Verification

Investigation of Anti-osteoporosis Mechanisms of Rehmanniae Radix Preparata Based on Network Pharmacology and Experimental Verification | 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 Investigation of Anti-osteoporosis Mechanisms of Rehmanniae Radix Preparata Based on Network Pharmacology and Experimental Verification Li Ou, Wenqian Kang, Ziyi Liang, Feng Gao, Taiwei Dong, Peifeng Wei, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-773165/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: Rehmanniae Radix Preparata (RRP) can effectively improve the symptoms of osteoporosis, but its molecular mechanism for treating osteoporosis is still unclear. The objective of this study is to investigate anti-osteoporosis mechanisms of RRP through network pharmacology. Methods: The overlapping targets of RRP and osteoporosis were screened out using online platforms. A visual network diagram of PPI was constructed and analyzed by Cytoscape 3.7.2 software. Molecular docking was used to evaluate the binding activity of ligands and receptors, and some key genes were randomly verified through pharmacological experiments. Results: According to topological analysis results, AKT1, MAPK1, ESR1, SRC, and MMP9 are key genes for RRP to treat osteoporosis, and they have high binding activity with stigmasterol and sitosterol. The main signal pathways of RRP in the treatment of osteoporosis, including Estrogen signaling pathway, HIF-1 signal pathway, MAPK signal pathway, PI3K-Akt signal pathway, etc. Results of animal experiments showed that RRP could significantly increase the expression levels of Akt1, ESR1 and SRC-1 mRNA in bone tissue to promote bone formation. Conclusion: This study explained the coordination between multiple components and multiple targets of RRP in the treatment of osteoporosis, and provided new ideas and basis for its clinical application and experimental research. Orthopedic Surgery Rehmanniae Radix Preparata network pharmacology mechanism osteoporosis bone Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Osteoporosis is a common bone metabolic disease in middle-aged and elderly, which often leads to sprout, bone deformity and even fracture, and seriously affects the health and quality of life of middle-aged and elderly people [ 1 , 2 ]. With the aging of the global population, its incidence is increasing year by year, so there is an urgent need to explore effective treatment methods [ 3 , 4 ]. At present, the clinical treatment of osteoporosis is mainly through the application of three types of drugs: bone formation promoters, bone resorption inhibitors and bone mineral agents to improve the clinical symptoms of patients, but these treatment methods have certain limitations [ 5 , 6 ]. Chinese herbal medicine has a long history of preventing and treating osteoporosis, with good curative effects and fewer side effects [ 7 , 8 ]. Rehmanniae Radix Preparata (RRP) is a commonly used Chinese herbal medicine for the treatment of osteoporosis. Its main chemical components include sterol, styrene glycosides, amino acids, carbohydrates, etc., which can reduce bone loss and slow down aging [ 9 , 10 ]. However, the material basis and molecular mechanism of RRP in the treatment of osteoporosis are still unclear. Based on systems biology and bioinformatics, network pharmacology explores the interaction between biomolecules and targets in the body, so as to effectively predict the efficacy and mechanism of drugs [ 11 ]. This study integrated information such as active ingredients, drug targets and disease targets through network pharmacological methods to explore the material basis and mechanism of RRP in the treatment of osteoporosis. This study explained the coordination between multiple components and multiple targets of RRP in the treatment of osteoporosis, and provided new ideas and basis for its clinical application and experimental research. First, overlapping targets of RRP and osteoporosis were screened out using online platforms. Next, a visual network diagram of PPI was constructed and analyzed by Cytoscape 3.7.2 software. Finally, molecular docking was used to evaluate the binding activity of ligands and receptors, and some key genes were randomly verified through pharmacological experiments. Network pharmacology research flow chart for RRP in the treatment of osteoporosis is shown in Fig. 1 . Methods Screening of anti-osteoporosis targets of RRP Osteoporosis-related targets were collected from online-accessible databases of DisGeNET (https://www.disgenet.org/), TTD (http://db.idrblab.net/ttd/) and Drukbank (https://www.drugbank.ca/) [12-14]. In addition, we used three online platforms: SEA (http://sea.bkslab.org), PharmMapper (http://www.lilab-ecust.cn/pharmmapper/) and SwissTargetPrediction (http://www.swisstargetprediction.ch/) to search for the target of RRP, and used UniProt database (https://www.Uniprot.org/) to standardize the gene ID [15-17]. Furthermore, all overlapping targets of RRP and osteoporosis were assayed by Venn diagrams to identify the targets for RRP-treated osteoporosis. Construction and analysis of protein interaction network The overlapping targets of RRP and osteoporosis were imported into STRING (https://string-db.org/) to obtain the protein-protein interaction (PPI) [18]. Then we used Cytoscape 3.7.2 software to construct a visual network diagram of PPI and further identified the targets for RRP-treated osteoporosis using cluster analysis [19]. GO and pathway enrichment analysis for key targets The key genes were imported into several online biological information databases such as DAVID (version: 6.8) and STRING (version: 11.0), and GO and KEGG pathway enrichment analysis were performed [20,21]. Molecular docking of RRP and key targets The 3D structure of the target protein was downloaded from PDB (https://www.rcsb.org/), and the water molecules and small molecule ligands of the target protein were removed using Pymol software [22]. Then we used AutoDock Tools software to prepare the hydrogenated protein and calculate the docking score. Establishment of the experimental model of osteoporosis Female SD rats weighing 200±20g were randomly divided into three groups: sham operation group, model group and RRP group, with 10 rats in each group. The experimental animals were purchased from Sichuan Chengdu Dashuo Experimental Animal Co., Ltd. (Chengdu, China), and the license number is SCXK 2019-028. Rats were kept in a well-ventilated environment with a room temperature of 22-25°C and relative humidity of 50%-60%. Animal experiments were carried out in accordance with the principles of the Care and Use of Laboratory Animal and the protocol was approved by the Animal Ethics Committee of Shaanxi University of Traditional Chinese Medicine (ethics approval number: AEC-19-002). The rats in the model group and the RRP group underwent ovariectomy, while the ovaries in the sham operation group were not removed. After the operation, the vaginal secretions of the rats were collected, and the keratinized epithelial cells were not observed as a key indicator of successful ovariectomy. Both the sham operation group and the model group were intragastrically administered with distilled water, and the RRP group was intragastrically administered with a dose of 5.4 g/kg of RRP daily. The rats were dissected and their femurs were taken after 16 weeks. Bone density examination The rats were anesthetized by intraperitoneal injection of 3% sodium pentobarbital (1 ml/kg), and the right femur and the third lumbar vertebra were peeled off. A dual-energy X-ray bone densitometer (Lunar, United States) was used to detect the bone mineral density of the femur and lumbar spine of rats. Validation of key targets through qRT-PCR Three key targets were randomly verified by Real-Time quantitative reverse transcription (RT-PCR). Primers were designed and synthesized by the solid-phase phosphoramidite triester method, and he sequence of primer was as follows: AKT1 forward primer: 5'- GGCCCAGATGATCACCATCAC-3'; AKT1 reverse primer: 5'-CTATCGTC CAGCGCAGTCCA-3'; ESR1 forward primer: 5'- CCAACCAGTGCACCATTGAT-3'; ESR1 reverse primer: 5'-TTTGATCATGAGCGGGCTTG-3-3'; SRC-1 forward primer: 5'-CAACCAGCAAAGGCTGAGTCCA-3'; SRC-1 reverse primer: 5'- AGTACCTCCTGAGGGGTTAGAG-3'. RNA of rats left femur were extracted with EasyPureTM RNA Kit (TransGen, China). TransScript first-strand cDNA synthesis SuperMix kit (TransGen, China) was used for reverse transcription reaction. The program used consisted of a pre-denaturation step of 95°C for 3 min, 40 cycling of denaturation 94°C for 15 s, annealing temperature 50°C for 30 s, extension 72°C for 1 min, and a final extension step of 72°C for 5 min. The gene expression data was analyzed by using the 2 -ΔΔCT method. Statistical Analysis All statistical analyses were performed using SPSS19.0 software. All data were expressed as mean ± standard deviation ( ±s). One-way analysis of variance was used to analyze the data from multiple groups. P-Values of 0.05 or less were regarded as statistically significant. Results Active ingredients and targets of RRP in the treatment of osteoporosis A total of 76 active ingredients of RRP were searched, and 2 active ingredients were screened based on oral bioavailability (OB)>30% and drug-likeness (DL)>0.18, including β-sitosterol (MOL000359) and stigmasterol (MOL000449). It was reported in the literature that 5-HMF could promote osteoblast production and might be one of the components of RRP in the treatment of osteoporosis. Therefore, although the DL value of 5-HMF (MOL000748) did not meet the standard, it was also included as an active ingredient (Table 1). We searched three online Platforms with the keyword “Osteoporosis” and identified 1179 osteoporosis-related targets. And we also obtained 428 RRP targets after removing duplicates. Finally, we found that there were a total of 118 overlapping targets for RRP and osteoporosis. Table 1 Active ingredients of RRP Molecule ID Molecule Name Structure OB (%) DL MOL000449 stigmasterol 43.83 0.76 MOL000359 sitosterol 36.91 0.75 MOL000748 5-HMF 45.07 0.02 Note: RRP: Rehmanniae Radix Preparata ; OB: oral bioavailability; DL: drug-likeness. Network construction and analysis After the overlapping targets were uploaded to STRING (at 70% confidence), the PPI network with 98 nodes and 378 edges was constructed using Cytoscape 3.7.2 software (Fig. 2). In the generated network, nodes represented targets, and edges represented the interaction between targets. We used the Cytohub plug-in to analyze the network topology properties. The degree value of node reflected the importance of the node in the network. In the PPI network, the node color changed from yellow to green reflected the degree value changed from low to high. The top 10 genes were MAPK1, MAPK3, AKT1, MAPK8, ESR1, PTG stigmasterol, EGFR, FGF2, SRC, MMP9. Their degree values were more than two fold of the median degree of all nodes in the network [23]. The MCODE plug-in was used to decompose the PPI network, and seven closely connected sub-modules in the network were identified, including two 16-cores (the connectivity of each node in the module is at least 16), one 7-cores, one 6-cores, two 4-cores and one 3-cores (Fig. 3). This sub-module reflected the closely related proteins interaction that completed specific molecular functions. The genes in these sub-modules were closely related to the following molecular functions: enzyme binding, phosphotransferase activity, signaling receptor binding, protein kinase binding, protein tyrosine kinase activity, ion binding, steroid hormone receptor activity, phosphatidylinositol-4,5-bisphosphate 3-kinase activity, heme binding, G protein-coupled receptor activity. And these genes were involved in many important biological processes related to osteoporosis, such as regulation of cell population proliferation, positive regulation of nitrogen compound metabolic process, activation of protein kinase activity, positive regulation of reactive oxygen species metabolic process, regulation of phosphorylation, steroid metabolic process, vitamin D metabolic process, bone development, regulation of protein binding and G protein-coupled receptor signaling pathway. Enrichment analysis of key targets In the results of the enrichment of KEGG pathways, the pathways of basic biological processes were screened with false discovery rate (FDR) less than 0.01, and an enriched cluster containing 162 pathways was obtained (enrichment score = 2.12). According to the FDR value of these pathways, 10 pathways related to osteoporosis were screened out, including Estrogen signaling pathway, HIF-1 signaling pathway, VEGF signaling pathway, TNF signaling pathway, Ras signaling pathway, FoxO signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, Osteoclast differentiation and Inflammatory mediator regulation of TRP channels (Table 2). Then we classified and visualized the pathways based on the number of key genes in these pathways (Fig. 4). The classification of these pathways belongs to endocrine system, signal transduction, development and regeneration and sensory system, which were the key target pathways of RRP to interfere with the biological process of osteoporosis. Table 2 KEGG signaling pathways regulated by important targets Category Pathway Number of genes Mapped targets FDR Endocrine system Estrogen signaling pathway 99 12 8.91×10 -7 Signal transduction HIF-1 signaling pathway 96 10 4.82×10 -5 Signal transduction VEGF signaling pathway signaling pathway 61 8 1.33×10 -4 Signal transduction TNF signaling pathway 107 9 4.21×10 -4 Signal transduction Ras signaling pathway 226 12 5.69×10 -4 Signal transduction FoxO signaling pathway 134 9 0.001 Signal transduction MAPK signaling pathway 253 12 0.001 Signal transduction PI3K-Akt signaling pathway 345 14 0.001 Development and regeneration Osteoclast differentiation 131 8 0.004 Sensory system Inflammatory mediator regulation of TRP channels 98 7 0.004 Note: KEGG: Kyoto Encyclopedia of Genes and Genomes; FDR: False discovery rate. Verification of molecular docking Molecular docking could effectively predict whether the ligand and the receptor could interact with each other through the complementarity of the spatial structure and the principle of energy minimization in the region of the receptor active site [24,25]. The lower the docking score between the ligand and the receptor, the greater the docking activity of the two and the more stable the structure. The molecular docking results showed that the molecular docking score between the active ingredients of RRP and the key targets was all less than -4.2 kcal/mol, suggesting that these active ingredients have a certain affinity and binding activity with the key targets (Table 3). Docking score of the ligand and the receptor was less than -7.0 kcal/mol, which indicated that they had strong binding activity. A total of 14 binding conformations have docking scores less than -7.0. The top 9 binding relationships with the highest docking activity are AKT1-stigmasterol, AKT1-sitosterol, MAPK1-stigmasterol, MAPK1-sitosterol, ESR1-stigmasterol, SRC-stigmasterol, MMP9-stigmasterol, ESR1-sitosterol, MMP9-sitosterol (Fig. 5). Table 3 Docking score of the active ingredients of RRP and key targets Molecule name PDB ID Docking score(kcal/mol) stigmasterol sitosterol 5-HMF MAPK1 4s33 -9.7 -9.5 -4.3 MAPK3 6ges -5.3 -5.0 -4.2 AKT1 6hhf -10.3 -10 -4.7 MAPK8 3pze -8.2 -8.3 -4.4 ESR1 2iok -9.6 -8.7 -4.3 PTGS2 4cox -7.9 -8.1 -5.0 EGFR 5y9t -6.3 -5.9 -3.8 FGF2 4fgf -5.0 -4.6 -3.2 SRC 4u5j -9.1 -8.0 -4.3 MMP9 6esm -8.9 -8.6 -5.6 Bone densitometry results Compared with the sham operation group, the femur and vertebral bone mineral density of the model group were significantly decreased (P <0.01). Compared with the model control group, the RRP group could significantly increase the bone mineral density of the femur of ovariectomized rats (P <0.01), and could significantly increase the bone density of the vertebral body (P <0.05), as shown in Fig. 6-7 . Effect on AKT1, ESR1and SRC-1 mRNA expression The relative quantitative expression levels of AKT1, ESR1and SRC mRNA were calculated by the 2-ΔΔ CT method. The results showed that compared with the sham operation group, the expression levels of AKT1, ESR1and SRC mRNA in the bone tissue of the model group decreased significantly (P<0.05). Compared with the model group, the expression of AKT1, ESR1and SRC mRNA in the bone tissue of the RRP group increased significantly (P<0.05). The results showed that RRP could increase the expression levels of AKT1, ESR1and SRC mRNA in the bone tissue of osteoporotic rats (Fig. 8). Discussion The high morbidity and mortality of osteoporosis and osteoporotic fractures not only seriously affect the quality of life of the elderly, but also cause a huge economic and social health burden [ 26 ]. RRP can effectively prevent and treat osteoporosis [ 27 ], but the material basis and molecular mechanism of its treatment of osteoporosis are still unclear. A total of 76 active ingredients of RRP were searched, and 3 active ingredients were screened: β-sitosterol, stigmasterol and 5-HMF. After removing the duplication, we obtained 428 RRP targets and 1,179 targets related to osteoporosis, of which 118 overlapping targets were the common targets of RRP and osteoporosis. We used the Cytohub plug-in to analyze the PPI network topology properties. According to the node degree value, the top 10 genes are MAPK1, MAPK3, AKT1, MAPK8, ESR1, PTGS2, EGFR, FGF2, SRC, MMP9. Results of molecular docking showed that AKT1, MAPK1, ESR1, SRC, MMP9 and Stigmasterol had strong binding activity. AKT1, MAPK1, ESR1, MMP9 and Sitosterol also had high binding activity. The main signal pathways of RRP in the treatment of osteoporosis, including Estrogen signaling pathway, HIF-1 signal pathway, MAPK signal pathway, PI3K-Akt signal pathway, VEGF signal pathway, osteoclast differentiation of TRP channel and regulation of inflammatory mediators, etc. The classification of these pathways belongs to endocrine system, signal transduction, development and regeneration and sensory system, which were the key target pathways of RRP to interfere with the biological process of osteoporosis. MAPK is the main carrier for signal transmission from the cell surface to the nucleus, mainly involved in the growth, differentiation and apoptosis caused by extracellular stimulation, and is a positive regulator of osteoblast differentiation and bone formation [ 28 ]. MAPK1, MAPK3 and MAPK8 are important members of the mitogen-activated protein kinase family. MAPK protein binds to the receptor complex, leading to inactivation of the cytosolic complex and degradation of β-catenin. Theβ-congenial protein can accumulate in the cytoplasm, and then transferred to the nucleus to promote the expression of specific genes in the bone, ultimately resulting in osteogenic differentiation to reduce and promote osteoblasts [ 29 , 30 ]. Activation of the MAPK pathway increases the proliferation and migration of osteoblasts, which can promote bone healing. Inhibition of MAPK signaling reduces the expression of specific genes in mature osteoblasts [ 31 , 32 ]. Estrogen is an important factor in increasing bone density and preventing bone loss after menopause. ESR1 is a nuclear biological macromolecule that mediates the biological effects of estrogen. Under the stimulation of EGF or IGF, the activated MAPK phosphorylates the serine of ESR1, allowing the receptor to bind to the specific coactivator of ESR1 to activate target genes [ 33 ]. When estrogen is insufficient, TNF-α promotes the proliferation and differentiation of osteoclast precursor cells and inhibits the formation of osteoblasts. Estrogen can also biphasically activate nitric oxide synthase in endothelial cells through MAPK and PI3K/Akt pathways [ 34 ]. In osteoblasts and osteoclasts, estradiol rapidly activates MAPK, which may be involved in cell proliferation and anti-apoptotic effects to prevent osteoporosis [ 35 ]. VEGF is an important downstream gene of the HIF-1 signaling pathway, which can promote the formation of osteoclasts and increase the activity of osteoclasts [ 36 , 37 ]. The VEGF produced by mature osteoblasts is essential for the angiogenesis-osteogenesis coupling. VEGF can promote the production of osteochondral progenitor cells during bone repair and endochondral bone formation [ 38 , 39 ]. PI3K/Akt signaling pathway is also involved in regulating the proliferation, differentiation and apoptosis of osteoclasts and osteoblasts [ 40 , 41 ]. Studies have found that the lack of Akt1 in osteoclasts can lead to cellular dysfunction and impaired bone resorption [ 42 , 43 ]. SRC-1 is an important nuclear receptor co-activator, which can enhance the effect of estrogen in many tissues and positively regulate the bone formation related to estrogen [ 44 ]. Experimental results showed that RRP could significantly increase the expression levels of Akt1, ESR1 and SRC-1 mRNA in bone tissue. Conclusions This study applied network pharmacology and molecular docking methods to study the material basis and potential mechanism of RRP in the treatment of osteoporosis. RRP interferes with the biological process of osteoporosis through the endocrine system, signal transduction, development and regeneration, and sensory system. The experimental animal study showed that RRP could significantly increase the expression levels of Akt1, ESR1 and SRC-1 mRNA in bone tissue to promote bone formation. This study explained the coordination between multiple components and multiple targets of RRP in the treatment of osteoporosis, and provided new ideas and basis for its clinical application and experimental research. Abbreviations RRP: Rehmanniae Radix Preparata ; PPI: Protein-protein interaction; GO: Gene ontology; KEGG: Kyoto encyclopedia of genes and genomes; OB: Oral bioavailability; DL: Drug-likeness; RT-PCR: Real-Time quantitative reverse transcription; FDR: False discovery rate Declarations Acknowledgments All authors would like to thank to the Laboratory of Clinical Chinese Pharmacy. Authors’ contributions O.L, L.ZY, K.WQ designed the study, analyzed the experiments, and wrote the paper. G.F, D.TW, W.PF, and L.M carried out the data collection and data analysis and revised the paper. The authors read and approved the final manuscript. Funding This study was supported by National Natural Science Foundation of China (No. 81903877); Shaanxi Provincial Department of Science and Technology Project (No. 2020JM-589); Shaanxi University of Traditional Chinese Medicine Innovation Team Project (No. 2019-QN02). Availability of data and materials All the data will be available upon motivated request to the corresponding author of the present paper. Ethical approval and consent to participate This study was conducted in agreement with the Declaration of Helsinki and its later amendments or comparable ethical standards and had been approved by the ethics board of Shaanxi University of Traditional Chinese Medicine (No: AEC-19-002). Consent for publication Not applicable. 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Advance in researches on role of MAPK and PI3K/AKT pathways in ROS-induced activation of nuclear factor erythroid 2-related factor 2. Chin J Public Health. 2016;32(6):870–3. https://doi.org/10.11847/zgggws2016-32-06-41 . Liu M, Xie WW, Zheng W, Yin DY, Luo R, Guo FJ. Targeted binding of estradiol with ESR1 promotes proliferation of human chondrocytes in vitro by inhibiting activation of ERK signaling pathway. J South Med Univ. 2019;39(2):134–43. https://doi.org/10.12122/j.issn.1673-4254.2019.09.02 . Miyauchi Y, Sato Y, Kobayashi T, Yoshida S, Mori T, Kanagawa H, et al. HIF1α is required for osteoclast activation by estrogen deficiency in postmenopausal osteoporosis. Proc Natl Acad Sci U S A. 2013;110(41):16568–73. https://doi.org/10.1073/pnas.1308755110 . Hu K, Olsen BR. Osteoblast-derived VEGF regulates osteoblast differentiation and bone formation during bone repair. J Clin Invest. 2016;126(2):509–26. https://doi.org/10.1172/jci82585 . Jafri MA, Kalamegam G, Abbas M, Al-Kaff M, Ahmed F, Bakhashab S, et al. Deciphering the Association of Cytokines, Chemokines, and Growth Factors in Chondrogenic Differentiation of Human Bone Marrow Mesenchymal Stem Cells Using an ex vivo Osteochondral Culture System. Front Cell Dev Biol. 2019;7380. https://doi.org/10.3389/fcell.2019.00380 . Duan X, Bradbury SR, Olsen BR, Berendsen AD. VEGF stimulates intramembranous bone formation during craniofacial skeletal development. Matrix Biol. 2016;52-54127-40. https://doi.org/10.1016/j.matbio.2016.02.005 . Moon JB, Kim JH, Kim K, Youn BU, Ko A, Lee SY, et al. Akt induces osteoclast differentiation through regulating the GSK3β/NFATc1 signaling cascade. J Immunol. 2012;188(1):163–9. https://doi.org/10.4049/jimmunol.1101254 . Zou W, Yang S, Zhang T, Sun H, Wang Y, Xue H, et al. Hypoxia enhances glucocorticoid-induced apoptosis and cell cycle arrest via the PI3K/Akt signaling pathway in osteoblastic cells. J Bone Miner Metab. 2015;33(6):615–24. https://doi.org/10.1007/s00774-014-0627-1 . Jiang P, Song KG. Research progress on osteoclast and its differentiation regulation mechanism. Chin J Bone Joint. 2017;6(3):223–7. https://doi.org/10.3969/j.issn.2095-252X.2017.03.013 . Choi YH, Choi HJ, Lee KY, Oh JW. Akt1 regulates phosphorylation and osteogenic activity of Dlx3. Biochem Biophys Res Commun. 2012;425(4):800–5. https://doi.org/10.1016/j.bbrc.2012.07.155 . Watters RJ, Hartmaier RJ, Osmanbeyoglu HU, Gillihan RM, Rae JM, Liao L, et al. Steroid receptor coactivator-1 can regulate osteoblastogenesis independently of estrogen. Mol Cell Endocrinol. 2017;44821-7. https://doi.org/10.1016/j.mce.2017.03.005 . Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 29 Aug, 2021 Review # 1 received at journal 25 Aug, 2021 Reviews received at journal 20 Aug, 2021 Reviewer # 1 agreed at journal 19 Aug, 2021 Reviewers invited by journal 05 Aug, 2021 Editor assigned by journal 03 Aug, 2021 Submission checks completed at journal 03 Aug, 2021 Editor invited by journal 03 Aug, 2021 First submitted to journal 01 Aug, 2021 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-773165","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":44135915,"identity":"02077ba6-af7e-41e8-ba8d-fd333a663c90","order_by":0,"name":"Li Ou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwklEQVRIiWNgGAWjYBACfv7Gxsd/eGrk+InWIjnjcLMBj8wxY8kGYrUYHEhvk+CxYU7ccIBoaw4cbJCQyGEzNj6evIHhR8U2wjoYmxsbDAzOyMiZnXlWwNhz5jZhLcwMBxsSEnvYjM1u5BgwM7YRoYWNIbHhwMF/zImbZxCrhYchsbGxgQfofQlitUhIHGxmZuA5ZiwB9MtBovxif779+W8GUFS2J2988KOCCC1IIMHgAEnqwVpI1TEKRsEoGAUjBAAAziw+uhGgIhIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-8767-1322","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Ou","suffix":""},{"id":44135916,"identity":"55ecd923-a05a-4ee8-9d1a-9a7a24a3c58e","order_by":1,"name":"Wenqian Kang","email":"","orcid":"","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wenqian","middleName":"","lastName":"Kang","suffix":""},{"id":44135917,"identity":"d0bd9bf4-8520-4806-95de-737125df84d6","order_by":2,"name":"Ziyi Liang","email":"","orcid":"","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ziyi","middleName":"","lastName":"Liang","suffix":""},{"id":44135918,"identity":"445b7a90-9c2b-4097-9141-ab2d9a8ecb67","order_by":3,"name":"Feng Gao","email":"","orcid":"","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Gao","suffix":""},{"id":44135919,"identity":"96ee3648-bb10-4d5f-8b59-120659a109cc","order_by":4,"name":"Taiwei Dong","email":"","orcid":"","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Taiwei","middleName":"","lastName":"Dong","suffix":""},{"id":44135920,"identity":"7ddc05eb-450a-4450-afe2-5dce610fabd9","order_by":5,"name":"Peifeng Wei","email":"","orcid":"","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Peifeng","middleName":"","lastName":"Wei","suffix":""},{"id":44135921,"identity":"e108a84e-fcc5-4d44-bffb-242f2a6f3a23","order_by":6,"name":"Min Li","email":"","orcid":"","institution":"Shaanxi University of Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2021-08-01 17:06:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-773165/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-773165/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":12258339,"identity":"2c199693-c6d5-4059-b789-295c2fe5d105","added_by":"auto","created_at":"2021-08-09 18:02:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":745553,"visible":true,"origin":"","legend":"Network pharmacology research flow chart","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/0757a1f9ed1bf9b4589203c8.png"},{"id":12258468,"identity":"76603ce1-7bd2-4483-8a59-e80f93c25c71","added_by":"auto","created_at":"2021-08-09 18:05:27","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124130,"visible":true,"origin":"","legend":"PPI network. PPI: Protein-protein interaction","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/3b17260d0d11d729f28982a7.jpeg"},{"id":12258335,"identity":"c1004da8-a718-4f75-86c0-6dec4e0da9f3","added_by":"auto","created_at":"2021-08-09 18:02:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":195820,"visible":true,"origin":"","legend":"Densely linked modules included in target network of RRP","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/03111035c98ac3c67e8d02e3.png"},{"id":12258333,"identity":"4f2560b5-b607-4c10-a7ca-a80515527c25","added_by":"auto","created_at":"2021-08-09 18:02:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":99228,"visible":true,"origin":"","legend":"Bubble diagram of top 10 KEGG enrichment pathways","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/5e9da9ac383f0682781a7174.png"},{"id":12258337,"identity":"d47eb92d-6907-4d2f-90f3-7105578384db","added_by":"auto","created_at":"2021-08-09 18:02:27","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":414369,"visible":true,"origin":"","legend":"Molecular docking model diagram","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/30c35ff0882be74f83fe7061.jpeg"},{"id":12258469,"identity":"96c02d65-67e2-4548-acb4-ada8c19bbcb0","added_by":"auto","created_at":"2021-08-09 18:05:27","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":198798,"visible":true,"origin":"","legend":"X-ray image of rat. A) Sham operation group. B) Model group. C) RRP group","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/70593c162dd1f2453062ee00.png"},{"id":12258470,"identity":"2a6c4f70-da64-4273-97ae-23975c03b867","added_by":"auto","created_at":"2021-08-09 18:05:27","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":57439,"visible":true,"origin":"","legend":"Effect on bone mineral density. Compared with the sham operation group, ##P\u003c0.01; Compared with the model group, **P\u003c0.01, *P\u003c0.05","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/7f8eef02735d6204da063083.png"},{"id":12258336,"identity":"53585f8a-b1f4-4e28-ad39-36c1bb595782","added_by":"auto","created_at":"2021-08-09 18:02:27","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":51335,"visible":true,"origin":"","legend":"Effect on AKT1, ESR1and SRC mRNA expression. Compared with the sham operation group, #P\u003c0.05; Compared with the model group, *P\u003c0.05","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/9cec59d8d7982ec9d003c2ec.png"},{"id":13708420,"identity":"5a466ddd-7e0c-4d1f-83f5-23a291904b87","added_by":"auto","created_at":"2021-09-17 14:07:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1999580,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-773165/v1/df2cce0e-b020-4fe1-aaa7-6c18484fbeba.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eInvestigation of Anti-osteoporosis Mechanisms of Rehmanniae Radix Preparata Based on Network Pharmacology and Experimental Verification\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoporosis is a common bone metabolic disease in middle-aged and elderly, which often leads to sprout, bone deformity and even fracture, and seriously affects the health and quality of life of middle-aged and elderly people [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. With the aging of the global population, its incidence is increasing year by year, so there is an urgent need to explore effective treatment methods [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. At present, the clinical treatment of osteoporosis is mainly through the application of three types of drugs: bone formation promoters, bone resorption inhibitors and bone mineral agents to improve the clinical symptoms of patients, but these treatment methods have certain limitations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Chinese herbal medicine has a long history of preventing and treating osteoporosis, with good curative effects and fewer side effects [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. \u003cem\u003eRehmanniae Radix Preparata\u003c/em\u003e (RRP) is a commonly used Chinese herbal medicine for the treatment of osteoporosis. Its main chemical components include sterol, styrene glycosides, amino acids, carbohydrates, etc., which can reduce bone loss and slow down aging [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, the material basis and molecular mechanism of RRP in the treatment of osteoporosis are still unclear.\u003c/p\u003e \u003cp\u003eBased on systems biology and bioinformatics, network pharmacology explores the interaction between biomolecules and targets in the body, so as to effectively predict the efficacy and mechanism of drugs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This study integrated information such as active ingredients, drug targets and disease targets through network pharmacological methods to explore the material basis and mechanism of RRP in the treatment of osteoporosis.\u003c/p\u003e \u003cp\u003eThis study explained the coordination between multiple components and multiple targets of RRP in the treatment of osteoporosis, and provided new ideas and basis for its clinical application and experimental research. First, overlapping targets of RRP and osteoporosis were screened out using online platforms. Next, a visual network diagram of PPI was constructed and analyzed by Cytoscape 3.7.2 software. Finally, molecular docking was used to evaluate the binding activity of ligands and receptors, and some key genes were randomly verified through pharmacological experiments. Network pharmacology research flow chart for RRP in the treatment of osteoporosis is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eScreening of anti-osteoporosis targets of RRP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOsteoporosis-related targets were collected from online-accessible databases of DisGeNET (https://www.disgenet.org/), TTD (http://db.idrblab.net/ttd/) and Drukbank (https://www.drugbank.ca/)\u0026nbsp;[12-14]. In addition, we used three online platforms: SEA (http://sea.bkslab.org), PharmMapper (http://www.lilab-ecust.cn/pharmmapper/) and SwissTargetPrediction (http://www.swisstargetprediction.ch/) to search for the target of RRP, and used UniProt database (https://www.Uniprot.org/) to standardize the gene ID\u0026nbsp;[15-17]. Furthermore, all overlapping targets of RRP and osteoporosis were assayed by Venn diagrams to identify the targets for RRP-treated osteoporosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction and analysis of protein interaction network\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overlapping targets of RRP and osteoporosis were imported into STRING (https://string-db.org/) to obtain the protein-protein interaction (PPI)\u0026nbsp;[18].\u0026nbsp;Then we used Cytoscape 3.7.2 software to construct a visual network diagram of PPI and further identified the targets for RRP-treated osteoporosis using cluster analysis [19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO and pathway enrichment analysis for key targets\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe key genes were imported into several online biological information databases such as DAVID (version: 6.8) and STRING (version: 11.0), and GO and KEGG pathway enrichment analysis were performed [20,21].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular docking of RRP and key targets\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 3D structure of the target protein was downloaded from PDB (https://www.rcsb.org/), and the water molecules and small molecule ligands of the target protein were removed using Pymol software [22]. Then we used AutoDock Tools software to prepare the hydrogenated protein and calculate the docking score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of the experimental model of osteoporosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFemale SD rats weighing 200\u0026plusmn;20g were randomly divided into three groups: sham operation group, model group and RRP group, with 10 rats in each group. The experimental animals were purchased from Sichuan Chengdu Dashuo Experimental Animal Co., Ltd. (Chengdu, China), and the license number is SCXK 2019-028. Rats were kept in a well-ventilated environment with a room temperature of 22-25\u0026deg;C and relative humidity of 50%-60%. Animal experiments were carried out in accordance with the principles of the Care and Use of Laboratory Animal and the protocol was approved by the Animal Ethics Committee of Shaanxi University of Traditional Chinese Medicine (ethics approval number: AEC-19-002).\u003c/p\u003e\n\u003cp\u003eThe rats in the model group and the RRP group underwent ovariectomy, while the ovaries in the sham operation group were not removed. After the operation, the vaginal secretions of the rats were collected, and the keratinized epithelial cells were not observed as a key indicator of successful ovariectomy.\u0026nbsp;Both the sham operation group and the model group were intragastrically administered with distilled water, and the RRP group was intragastrically administered with a dose of 5.4 g/kg of RRP daily. The rats were dissected and their femurs were taken after 16 weeks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBone density examination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe rats were anesthetized by intraperitoneal injection of 3% sodium pentobarbital (1 ml/kg), and the right femur and the third lumbar vertebra were peeled off. A dual-energy X-ray bone densitometer (Lunar, United States) was used to detect the bone mineral density of the femur and lumbar spine of rats.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation of key targets through qRT-PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree key targets were randomly verified by Real-Time quantitative reverse transcription (RT-PCR). Primers were designed and synthesized by the solid-phase phosphoramidite triester method, and he sequence of primer was as follows: AKT1 forward primer: 5\u0026apos;- GGCCCAGATGATCACCATCAC-3\u0026apos;; AKT1 reverse primer: 5\u0026apos;-CTATCGTC CAGCGCAGTCCA-3\u0026apos;; ESR1 forward primer: 5\u0026apos;- CCAACCAGTGCACCATTGAT-3\u0026apos;; ESR1 reverse primer: 5\u0026apos;-TTTGATCATGAGCGGGCTTG-3-3\u0026apos;; SRC-1 forward primer: 5\u0026apos;-CAACCAGCAAAGGCTGAGTCCA-3\u0026apos;; SRC-1 reverse primer: 5\u0026apos;-\u0026nbsp;AGTACCTCCTGAGGGGTTAGAG-3\u0026apos;. RNA of rats left femur were extracted with EasyPureTM RNA Kit (TransGen, China).\u0026nbsp;TransScript first-strand cDNA synthesis SuperMix kit (TransGen, China) was used for reverse transcription reaction. The program used consisted of a pre-denaturation step of 95\u0026deg;C for 3 min, 40 cycling of denaturation 94\u0026deg;C for 15 s, annealing temperature 50\u0026deg;C for 30 s, extension 72\u0026deg;C for 1 min, and a final extension step of 72\u0026deg;C for 5 min. The gene expression data was analyzed by using the 2\u003csup\u003e-\u0026Delta;\u0026Delta;CT\u003c/sup\u003e method.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were performed using SPSS19.0 software. All data were expressed as mean \u0026plusmn; standard deviation ( \u0026plusmn;s). One-way analysis of variance was used to analyze the data from multiple groups. P-Values of 0.05 or less were regarded as statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eActive ingredients and targets of RRP in the treatment of osteoporosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 76 active ingredients of RRP were searched, and 2 active ingredients were screened based on oral bioavailability (OB)\u0026gt;30% and drug-likeness (DL)\u0026gt;0.18, including \u0026beta;-sitosterol (MOL000359) and stigmasterol (MOL000449). It was reported in the literature that 5-HMF could promote osteoblast production and might be one of the components of RRP in the treatment of osteoporosis. Therefore, although the DL value of 5-HMF (MOL000748) did not meet the standard, it was also included as an active ingredient\u0026nbsp;(Table 1). We searched three online Platforms with the keyword \u0026ldquo;Osteoporosis\u0026rdquo; and identified 1179 osteoporosis-related targets. And we also obtained 428 RRP targets after removing duplicates. Finally, we found that there were a total of 118 overlapping targets for RRP and osteoporosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eActive ingredients of RRP\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.72151898734177%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMolecule ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.880650994575046%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMolecule Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.815551537070526%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStructure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.743218806509946%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOB\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.839059674502712%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.72151898734177%\"\u003e\n \u003cp\u003eMOL000449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.880650994575046%\"\u003e\n \u003cp\u003estigmasterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.815551537070526%\"\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1628525232.png\" alt=\"image\"\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.743218806509946%\"\u003e\n \u003cp\u003e43.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.839059674502712%\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.72151898734177%\"\u003e\n \u003cp\u003eMOL000359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.880650994575046%\"\u003e\n \u003cp\u003esitosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.815551537070526%\"\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img162852523256.png\" alt=\"image\"\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.743218806509946%\"\u003e\n \u003cp\u003e36.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"12.839059674502712%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.72151898734177%\"\u003e\n \u003cp\u003eMOL000748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.880650994575046%\"\u003e\n \u003cp\u003e5-HMF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"33.815551537070526%\"\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/69519_bce2c0439cd956a6/69519_custom_files/img1628525231.png\" alt=\"image\"\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.743218806509946%\"\u003e\n \u003cp\u003e45.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.839059674502712%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eNote: RRP: \u003cem\u003eRehmanniae Radix Preparata\u003c/em\u003e;\u0026nbsp;OB:\u0026nbsp;oral bioavailability;\u0026nbsp;DL:\u0026nbsp;drug-likeness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNetwork construction and analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the overlapping targets were uploaded to STRING (at 70% confidence), the PPI network with 98 nodes and 378 edges was constructed using Cytoscape 3.7.2 software (Fig. 2). In the generated network, nodes represented targets, and edges represented the interaction between targets. We used the Cytohub plug-in to analyze the network topology properties. The degree value of node reflected the importance of the node in the network. In the PPI network, the node color changed from yellow to green reflected the degree value changed from low to high. The top 10 genes were MAPK1, MAPK3, AKT1, MAPK8, ESR1, PTG stigmasterol, EGFR, FGF2, SRC, MMP9. Their degree values were more than two fold of the median degree of all nodes in the network [23].\u003c/p\u003e\n\u003cp\u003eThe MCODE plug-in was used to decompose the PPI network, and seven closely connected sub-modules in the network were identified, including two 16-cores (the connectivity of each node in the module is at least 16), one 7-cores, one 6-cores, two 4-cores and one 3-cores (Fig. 3). This sub-module reflected the closely related proteins interaction that completed specific molecular functions. The genes in these sub-modules were closely related to the following molecular functions: enzyme binding, phosphotransferase activity, signaling receptor binding, protein kinase binding, protein tyrosine kinase activity, ion binding, steroid hormone receptor activity, phosphatidylinositol-4,5-bisphosphate 3-kinase activity, heme binding, G protein-coupled receptor activity. And these genes were involved in many important biological processes related to osteoporosis, such as regulation of cell population proliferation, positive regulation of nitrogen compound metabolic process, activation of protein kinase activity, positive regulation of reactive oxygen species metabolic process, regulation of phosphorylation, steroid metabolic process, vitamin D metabolic process, bone development, regulation of protein binding and G protein-coupled receptor signaling pathway.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnrichment analysis of key targets\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the results of the enrichment of KEGG pathways, the pathways of basic biological processes were screened with false discovery rate (FDR) less than 0.01, and an enriched cluster containing 162 pathways was obtained (enrichment score = 2.12). According to the FDR value of these pathways, 10 pathways related to osteoporosis were screened out, including Estrogen signaling pathway, HIF-1 signaling pathway, VEGF signaling pathway, TNF signaling pathway, Ras signaling pathway, FoxO signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, Osteoclast differentiation and Inflammatory mediator regulation of TRP channels (Table 2). Then we classified and visualized the pathways based on the number of key genes in these pathways (Fig. 4). The classification of these pathways belongs to endocrine system, signal transduction, development and regeneration and sensory system, which were the key target pathways of RRP to interfere with the biological process of osteoporosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e KEGG signaling pathways regulated by important targets\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePathway\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of genes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMapped targets\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFDR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eEndocrine system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eEstrogen signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e8.91\u0026times;10\u003csup\u003e-7\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eHIF-1 signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e4.82\u0026times;10\u003csup\u003e-5\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eVEGF signaling pathway signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e1.33\u0026times;10\u003csup\u003e-4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eTNF signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e4.21\u0026times;10\u003csup\u003e-4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eRas signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e5.69\u0026times;10\u003csup\u003e-4\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eFoxO signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eMAPK signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSignal transduction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003ePI3K-Akt signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eDevelopment and regeneration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eOsteoclast differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.082585278276483%\"\u003e\n \u003cp\u003eSensory system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"27.10951526032316%\"\u003e\n \u003cp\u003eInflammatory mediator regulation of TRP channels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.28725314183124%\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.26032315978456%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: KEGG: Kyoto Encyclopedia of Genes and Genomes; FDR: False discovery rate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVerification of molecular docking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking could effectively predict whether the ligand and the receptor could interact with each other through the complementarity of the spatial structure and the principle of energy minimization in the region of the receptor active site [24,25]. The lower the docking score between the ligand and the receptor, the greater the docking activity of the two and the more stable the structure. The molecular docking results showed that the molecular docking score between the active ingredients of RRP and the key targets was all less than -4.2 kcal/mol, suggesting that these active ingredients have a certain affinity and binding activity with the key targets (Table 3). Docking score of the ligand and the receptor was less than -7.0 kcal/mol, which indicated that they had strong binding activity.\u0026nbsp;A total of 14 binding conformations have docking scores less than -7.0. The top 9 binding relationships with the highest docking activity are AKT1-stigmasterol, AKT1-sitosterol, MAPK1-stigmasterol, MAPK1-sitosterol, ESR1-stigmasterol, SRC-stigmasterol, MMP9-stigmasterol, ESR1-sitosterol, MMP9-sitosterol (Fig. 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eDocking score of the active ingredients of RRP and key targets\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"22.54901960784314%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMolecule name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" width=\"18.235294117647058%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePDB ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" width=\"59.21568627450981%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDocking score(kcal/mol)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"37.41721854304636%\"\u003e\n \u003cp\u003estigmasterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"31.125827814569536%\"\u003e\n \u003cp\u003esitosterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"31.456953642384107%\"\u003e\n \u003cp\u003e5-HMF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eMAPK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e4s33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-9.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eMAPK3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e6ges\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eAKT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e6hhf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eMAPK8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e3pze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eESR1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e2iok\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003ePTGS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e4cox\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eEGFR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e5y9t\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eFGF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e4fgf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eSRC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e4u5j\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.504892367906066%\"\u003e\n \u003cp\u003eMMP9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.199608610567516%\"\u003e\n \u003cp\u003e6esm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"19.765166340508806%\"\u003e\n \u003cp\u003e-5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eBone densitometry results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCompared with the sham operation group, the femur and vertebral bone mineral density of the model group were significantly decreased (P \u0026lt;0.01). Compared with the model control group, the RRP group could significantly increase the bone mineral density of the femur of ovariectomized rats (P \u0026lt;0.01), and could significantly increase the bone density of the vertebral body (P \u0026lt;0.05), as shown in Fig. 6-7\u003cem\u003e.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEffect on AKT1, ESR1and SRC-1 mRNA expression\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe relative quantitative expression levels of AKT1, ESR1and SRC mRNA were calculated by the \u003csup\u003e2-\u0026Delta;\u0026Delta;\u003c/sup\u003eCT method. The results showed that compared with the sham operation group, the expression levels of AKT1, ESR1and SRC mRNA in the bone tissue of the model group decreased significantly (P\u0026lt;0.05). Compared with the model group, the expression of AKT1, ESR1and SRC mRNA in the bone tissue of the RRP group increased significantly (P\u0026lt;0.05). The results showed that RRP could increase the expression levels of AKT1, ESR1and SRC mRNA in the bone tissue of osteoporotic rats (Fig. 8).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe high morbidity and mortality of osteoporosis and osteoporotic fractures not only seriously affect the quality of life of the elderly, but also cause a huge economic and social health burden [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. RRP can effectively prevent and treat osteoporosis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], but the material basis and molecular mechanism of its treatment of osteoporosis are still unclear. A total of 76 active ingredients of RRP were searched, and 3 active ingredients were screened: β-sitosterol, stigmasterol and 5-HMF. After removing the duplication, we obtained 428 RRP targets and 1,179 targets related to osteoporosis, of which 118 overlapping targets were the common targets of RRP and osteoporosis. We used the Cytohub plug-in to analyze the PPI network topology properties. According to the node degree value, the top 10 genes are MAPK1, MAPK3, AKT1, MAPK8, ESR1, PTGS2, EGFR, FGF2, SRC, MMP9. Results of molecular docking showed that AKT1, MAPK1, ESR1, SRC, MMP9 and Stigmasterol had strong binding activity. AKT1, MAPK1, ESR1, MMP9 and Sitosterol also had high binding activity. The main signal pathways of RRP in the treatment of osteoporosis, including Estrogen signaling pathway, HIF-1 signal pathway, MAPK signal pathway, PI3K-Akt signal pathway, VEGF signal pathway, osteoclast differentiation of TRP channel and regulation of inflammatory mediators, etc. The classification of these pathways belongs to endocrine system, signal transduction, development and regeneration and sensory system, which were the key target pathways of RRP to interfere with the biological process of osteoporosis.\u003c/p\u003e \u003cp\u003eMAPK is the main carrier for signal transmission from the cell surface to the nucleus, mainly involved in the growth, differentiation and apoptosis caused by extracellular stimulation, and is a positive regulator of osteoblast differentiation and bone formation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. MAPK1, MAPK3 and MAPK8 are important members of the mitogen-activated protein kinase family. MAPK protein binds to the receptor complex, leading to inactivation of the cytosolic complex and degradation of β-catenin. Theβ-congenial protein can accumulate in the cytoplasm, and then transferred to the nucleus to promote the expression of specific genes in the bone, ultimately resulting in osteogenic differentiation to reduce and promote osteoblasts [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Activation of the MAPK pathway increases the proliferation and migration of osteoblasts, which can promote bone healing. Inhibition of MAPK signaling reduces the expression of specific genes in mature osteoblasts [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Estrogen is an important factor in increasing bone density and preventing bone loss after menopause. ESR1 is a nuclear biological macromolecule that mediates the biological effects of estrogen. Under the stimulation of EGF or IGF, the activated MAPK phosphorylates the serine of ESR1, allowing the receptor to bind to the specific coactivator of ESR1 to activate target genes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhen estrogen is insufficient, TNF-α promotes the proliferation and differentiation of osteoclast precursor cells and inhibits the formation of osteoblasts. Estrogen can also biphasically activate nitric oxide synthase in endothelial cells through MAPK and PI3K/Akt pathways [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In osteoblasts and osteoclasts, estradiol rapidly activates MAPK, which may be involved in cell proliferation and anti-apoptotic effects to prevent osteoporosis [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. VEGF is an important downstream gene of the HIF-1 signaling pathway, which can promote the formation of osteoclasts and increase the activity of osteoclasts [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The VEGF produced by mature osteoblasts is essential for the angiogenesis-osteogenesis coupling. VEGF can promote the production of osteochondral progenitor cells during bone repair and endochondral bone formation [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. PI3K/Akt signaling pathway is also involved in regulating the proliferation, differentiation and apoptosis of osteoclasts and osteoblasts [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Studies have found that the lack of Akt1 in osteoclasts can lead to cellular dysfunction and impaired bone resorption [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. SRC-1 is an important nuclear receptor co-activator, which can enhance the effect of estrogen in many tissues and positively regulate the bone formation related to estrogen [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Experimental results showed that RRP could significantly increase the expression levels of Akt1, ESR1 and SRC-1 mRNA in bone tissue.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study applied network pharmacology and molecular docking methods to study the material basis and potential mechanism of RRP in the treatment of osteoporosis. RRP interferes with the biological process of osteoporosis through the endocrine system, signal transduction, development and regeneration, and sensory system. The experimental animal study showed that RRP could significantly increase the expression levels of Akt1, ESR1 and SRC-1 mRNA in bone tissue to promote bone formation. This study explained the coordination between multiple components and multiple targets of RRP in the treatment of osteoporosis, and provided new ideas and basis for its clinical application and experimental research.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eRRP: \u003cem\u003eRehmanniae Radix Preparata\u003c/em\u003e; PPI: Protein-protein interaction; GO: Gene ontology; KEGG: Kyoto encyclopedia of genes and genomes; OB: Oral bioavailability; DL: Drug-likeness; RT-PCR: Real-Time quantitative reverse transcription; FDR: False discovery rate\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors would like to thank to the Laboratory of Clinical Chinese Pharmacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eO.L, L.ZY, K.WQ designed the study, analyzed the experiments, and wrote the paper. G.F, D.TW, W.PF, and L.M carried out the data collection and data analysis and revised the paper. The authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National Natural Science Foundation of China (No. 81903877); Shaanxi Provincial Department of Science and Technology Project (No. 2020JM-589); Shaanxi University of Traditional Chinese Medicine Innovation Team Project (No. 2019-QN02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data will be available upon motivated request to the corresponding author of the present paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in agreement with the Declaration of Helsinki and its later amendments or comparable ethical standards and had been approved by the ethics board of Shaanxi University of Traditional Chinese Medicine (No: AEC-19-002).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCollege of Pharmacy, Shaanxi University of Chinese Medicine, Xian yang 712046, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGates BJ, Das S. 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Mol Cell Endocrinol. 2017;44821-7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.mce.2017.03.005\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Rehmanniae Radix Preparata, network pharmacology, mechanism, osteoporosis, bone","lastPublishedDoi":"10.21203/rs.3.rs-773165/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-773165/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003e\u003cem\u003eRehmanniae Radix Preparata\u003c/em\u003e (RRP) can effectively improve the symptoms of osteoporosis, but its molecular mechanism for treating osteoporosis is still unclear. The objective of this study is to investigate anti-osteoporosis mechanisms of \u003cem\u003eRRP\u003c/em\u003e through network pharmacology.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThe overlapping targets of RRP and osteoporosis were screened out using online platforms. A visual network diagram of PPI was constructed and analyzed by Cytoscape 3.7.2 software. Molecular docking was used to evaluate the binding activity of ligands and receptors, and some key genes were randomly verified through pharmacological experiments. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eAccording to topological analysis results, AKT1, MAPK1, ESR1, SRC, and MMP9 are key genes for RRP to treat osteoporosis, and they have high binding activity with stigmasterol and sitosterol. The main signal pathways of RRP in the treatment of osteoporosis, including Estrogen signaling pathway, HIF-1 signal pathway, MAPK signal pathway, PI3K-Akt signal pathway, etc. Results of animal experiments showed that RRP could significantly increase the expression levels of Akt1, ESR1 and SRC-1 mRNA in bone tissue to promote bone formation. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study explained the coordination between multiple components and multiple targets of RRP in the treatment of osteoporosis, and provided new ideas and basis for its clinical application and experimental research.\u003c/p\u003e","manuscriptTitle":"Investigation of Anti-osteoporosis Mechanisms of Rehmanniae Radix Preparata Based on Network Pharmacology and Experimental Verification","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-09 18:02:25","doi":"10.21203/rs.3.rs-773165/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-08-29T06:30:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-08-26T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"editorInvitedReview","content":"","date":"2021-08-20T13:58:55+00:00","index":0,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-08-20T00:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-08-05T07:04:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-08-04T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-08-03T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-08-03T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2021-08-01T06:36:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8550de84-6688-4083-aad2-bbedf6c4c043","owner":[],"postedDate":"August 9th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":6327145,"name":"Orthopedic Surgery"}],"tags":[],"updatedAt":"2021-09-23T16:19:11+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-09 18:02:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-773165","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-773165","identity":"rs-773165","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}