Cordyceps sinensis in the treatment of OLP and provides a theoretical support for improving current treatment regimens for OLP.  Oral lichen planus (OLP) is the most common potentially malignant disorder of the oral cavity. This study aimed to investigate the mechanism of action of Cordyceps sinensis were predicted and screened using the TCMSP, SymMap, PubMed, HIT 2.0, and PharmMapper databases, while the relevant OLP targets were predicted and screened using the DisGeNET and GeneCards databases. Protein-protein interactions (PPI) were examined using the String database, and Cytoscape was used to combine and illustrate the findings. GO and KEGG pathway enrichment analyses were carried out using RStudio, and AutoDock Vina and Pymol were used for molecular docking and visualization, respectively.  The active components and therapeutic targets of Cordyceps sinensis. Potential therapeutic targets included 67 targets that matched and overlapped with OLP, including TNF, IL-6, CD4, EGFR, and IL1B. Key targets were predominantly engaged in the PI3K-Akt signaling pathway and the MAPK signaling pathway, according to the GO and KEGG analyses. These targets have a connection to biological processes including apoptosis signaling pathway regulation, T cell activation, and oxidative stress response. The molecular docking results showed that TNF, IL-6, CD4, EGFR, and IL1B could bind to their corresponding active components.  A total of 404 potential target genes were discovered after evaluating 21 active compounds from Cordyceps sinensis contains multiple components and acts on multiple targets and multiple pathways. Particularly, Cordyceps sinensis targets TNF, IL-6, CD4, EGFR, and IL1B, regulates PI3K-Akt and MAPK signaling pathways, as well as takes part in biological processes including apoptosis, T cell activation, and oxidative stress. Cordyceps sinensis could be a crucial choice in the therapy of OLP. Oral lichen planus (OLP) is a chronic or recurrent inflammatory autoimmune disease of the oral mucosa, with an incidence of 1% worldwide and substantial regional variation . CurrentIn recent years, Chinese herbal medicine has achieved results in the treatment of OLP, such as Liuwei Dihuang , Tripterβ, IFN-γ, TNF-α, and others, produced during the development of OLP can lead to immunodeficiency, allergy, and autoimmunity [With a multifactorial etiology and malignant transformation tendency, OLP has been substantially studied; however, its pathophysiology and etiology remain elusive . It is bimmunity . An imbaimmunity . The divCordyceps sinensis, a traditional Chinese medicine, is mainly distributed in alpine zones with a wide variety of species. The majority of them are entomopathogenic fungus that infects insect larvae and pupae [Cordyceps sinensis includes a wide variety of chemical elements, including nucleosides, sugars, sterols, proteins, and sphingolipids [Cordyceps sinensis and its bioactive molecules have a variety of pharmacological effects, including anti-inflammatory, antioxidant, antitumor, antihyperglycemic, antiapoptotic, immunomodulatory, nephroprotective, and hepatoprotective properties [κB (NF-κB) signaling pathways, inducing the production of nitric oxide (NO), reactive oxygen species (ROS), and more [Cordyceps sinensis and its preparations might cure OLP via antioxidant, immunomodulatory, and anti-inflammatory mechanisms. In China, Cordyceps sinensis preparations  are clinically effective as adjuvant therapeutic agents for OLP, but the specific mechanisms are not yet clear.nd pupae . Researcgolipids . Researcoperties . Based oand more . By incrand more , 17. Witand more . More anCordyceps sinensis and OLP.Network pharmacology is an approach to predict disease-specific targets from biomedical data available in systems biology and polypharmacology . With thCordyceps sinensis for the treatment of OLP, we conducted this study using a network pharmacology and molecular docking approach. This study will provide a framework for further research into the pharmacological processes by which Cordyceps sinensis works to cure OLP. The procedure of this study is displayed in In order to examine the possible targets of the active components of Cordyceps sinensis were searched in the TCMSP [https://tcmspw.com/tcmsp.php) and SymMap [https://www.symmap.org/) databases with Cordyceps sinensis as the keyword, and oral bioavailability (OB) ≥ 30% and drug-like quality (DL) ≥ 0.18 (a screening threshold of TCMSP database) [https://pubmed.ncbi.nlm.nih.gov) was added to include active ingredients that did not meet the above criteria but had significant pharmacodynamic effects or high levels. Finally, the active compounds of Cordyceps sinensis were identified and the active ingredient structures were acquired using the MOL2 format files on the TCMSP platform.The compounds of he TCMSP  (https:/d SymMap  (https:/atabase) . In addihttps://www.badd-cao.net:2345/) is an evidence-based comprehensive search and management platform for herbal ingredients and target information [https://www.lilab-ecust.cn/pharmmapper/) for target prediction. Human Protein Targets Only is selected on the “Select Targets Set,” and the rest of the parameters are kept as default settings. Results obtained from the PharmMapper platform for each active ingredient are used for subsequent analysis based on the targets selected with Z′-score > 1. Finally, all of the target proteins identified during the screening are annotated into gene names using the UniProt database (https://www.uniprot.org/), excluding any nonhuman targets.HIT2.0   and GeneCards databases (https://www.genecards.org) using “oral lichen planus” as the keyword. To increase the reliability of the findings, the targets obtained from the GeneCards and DisGeNET databases were filtered for results that had a relevance score ≥ 5 and GDA ≥ 0.01, respectively.The OLP-related targets were retrieved from the DisGeNET , and a “component-target” network was created using the Merge function.To create a Venn diagram and determine the common targets of https://www.string-db.org/) was used to create the protein-protein interaction network (PPI). The potential targets of Cordyceps sinensis for OLP treatment in the “multiple proteins” section were entered and the species was set as “Homo sapiens.” The “high confidence (0.700)” was selected as the confidence level to obtain the PPI network related to the effectiveness of Cordyceps sinensis. The network was then loaded into Cytoscape for visualization, and the topological parameters of the nodes in the network were calculated using the app CytoHubba.The STRING database .Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the ClusterProﬁler package of R programming language, and a screening criterion of https://www.rcsb.org/) was used to obtain the protein crystal structures, while the TCMSP database was used to download the compound MOL2 structures. They were processed using AutoDock Tools (https://mgltools.scripps.edu/documentation/links/autodock), including separation of the protein structure from the original ligand, removal of water molecules and charge added to the structure, and converted to “PDBQT” format. The 3D docking photos were created using Pymol 2.4.0 (https://pymol.org/2/) software. According to research studies, when the binding energy of a small molecule medication to a protein is less than −4.25 kcal/mol, it is considered to have binding activity between the two. Additionally, two molecules have excellent binding activity when the binding energy is less than −5.0 kcal/mol [The five core proteins with the greatest node degree values in the PPI network were docked to their active components. The RCSB PDB database , 34 entries for cellular components (CC), and 100 entries for molecular function (MF). The top 10 GO entries , inflammation, and cancer [Hitherto, the pathophysiology of OLP is still not fully understood. However, studies indicate that immunological and psychological variables may be involved , 35. In d cancer .Cordyceps sinensis on OLP and to give pertinent data for additional preclinical or clinical investigations. Through database search and screening, 21 active ingredients and 67 shared targets of Cordyceps sinensis were identified. Through PPI analysis, the main targets of Cordyceps sinensis for OLP treatment, including AKT1 (Degree = 38), TNF (Degree = 36), TP53 (Degree = 34), JUN (Degree = 33), and IL-6 (Degree = 32) were identified. These targets were suggested to have a significant impact on the improvement of OLP using Cordyceps sinensis treatment.For the first time, network pharmacology has been used to uncover the mechanism of action of AKT1 is one of the three serine/threonine protein kinases  that are known as AKT kinases. These kinases control a variety of functions, such as angiogenesis, cell survival, growth, proliferation, and metabolism , 39. ZhaCordyceps sinensis for OLP treatment. The biological processes involved in the shared targets mainly include regulation of apoptotic signaling pathway, T cell activation, epithelial cell proliferation, response to oxidative stress, regulation of lymphocyte activation, and others. It was hypothesized that the ability of Cordyceps sinensis for the treatment of OLP may be associated with the control of the body's immune system as well as cell growth and apoptosis, which coincides with the possible etiology and pathogenesis of OLP. Numerous investigations have demonstrated a connection between the pathophysiology of OLP and aberrant T cell activation, oral keratin-forming cell death, and the body's redox state [The etiology and pathogenesis of OLP are complex, and its development involves multiple biological processes and pathways. We used the R language to carry out GO and KEGG analysis to understand the mechanism of ox state , 11. Addox state  and thatox state . Additioox state . Mitogenox state . OLP andox state .Cordyceps sinensis to be effective. Previous research has demonstrated that the pathophysiology of OLP is related to a Th1/Th2 imbalance and berberine can suppress the imbalance between Th1 and Th2 cells [in vitro [β-sitosterol, also known as “the secret to life” is a phytosterol that is widely present in natural plants [β-sitosterol has anti-inflammatory and antioxidant properties that can lower TNF and IL-1 levels and boost the activity of antioxidant enzymes such as catalase (CAT) and glutathione (GSH) [Molecular docking results showed that, except for arachidonic acid, the minimum binding energy between adenosine, beta-sitosterol, berberine, cordycepin, and their corresponding key targets AKT1, TNF, TP53, JUN, and IL-6 was less than −5 kcal/mol, indicating that there was a high affinity between the small molecule drugs and the target proteins. Therefore, these components could be the key pharmacological substances for h2 cells , 60. Addh2 cells . Furtherh2 cells . To lessin vitro . An isolin vitro . β-sitosl plants . β-sitosne (GSH) . These rCordyceps sinensis for the treatment of OLP. These components improve OLP by interfering with a number of targets , biological processes , and signaling pathways . More in vivo and in vitro testing are needed to confirm and investigate the efficacy of these active components, targets, and associated pathways identified by network pharmacology. Despite some limitations, this study provides good ideas and directions for future experimental validation and clinical treatment of OLP.In conclusion, adenosine, beta-sitosterol, berberine, and cordycepin are the key active substances of


Oral submucous fibrosis (OSMF) is a chronic, fibrotic disease that affects the oral cavity, showing a high rate of malignant transformation. Curcuma exerts therapeutic potentials in many diseases including OSMF. However, the potential targets and pathways to explain the therapeutic effects of curcuma on OSMF are outside the scope of present knowledge. Herein we intend to reveal the predictive targets and potential pathways of curcuma against OSMF by a network pharmacology-based approach followed by molecular docking technology.  We searched the SymMap, GeneCards, and OMIM database to obtain curcuma and OSMF common targets. The protein-protein interaction (PPI) of curcuma and OSMF common targets were then analyzed, followed by functional enrichment analysis. The best binding mode of curcuma and target proteins was analyzed by molecular docking technology.  We collected 290 putative targets of curcuma molecules and 600 known therapeutic targets of OSMF, with 64 curcuma and OSMF common targets sorted out. In the PPI network, there were 63 nodes with 922 edges. The node indicates protein and the line indicates PPI relation. The most enriched GO term in the BP level is “gland development”, followed by “cellular response to chemical stress”, and then “response to oxygen levels”, while the most enriched GO term in CC and MF is “membrane raft” and “cytokine receptor binding”, respectively. We also found 131 KEGG pathways significantly enriched by curcuma and OSMF common targets. The binding energy of curcuma to ALB, TNF, TP53, IL6, and VEGFA was −9.5 kcal/mol, −3.9 kcal/mol, −3.5 kcal/mol, −3.6 kcal/mol, and −8.9 kcal/mol, respectively, which suggested ALB and VEGFA were regarded as main targets involving in the potential mechanism of curcuma against OSMF.  The present study illustrated that the therapeutic effects of curcuma on OSMF were achieved by targeting ALB and VEGFA, which giving reference to further drug design and development for OSMF. Oral submucous fibrosis (OSMF) is defined as a chronic scarring disease that severely affects the oral cavity, oropharynx, and sometimes the oesophagus , 2. It rCurcumin, as a main bioactive polyphenolic compound, is extracted from the curcuma longa  that is a plant belonging to the ginger family (Zingiberaceae), originated from India, and currently grown in Southeast Asia and China . Curcumahttp://www.symmap.org/, was retrieved to collect putative targets of curcuma. The proteins (only “Homo sapiens”) corresponding to the above active components were transformed into gene symbols using the UniProt database (https://www.UniProt.org/). The targets of OSMF were acquired from two public databases the GeneCards database (https://www.genecards.org/) and Online Mendelian Inheritance in Man database . Briefly, we used “oral submucous fibrosis” as the search term to obtain disease targets (only “Homo sapiens”) in these two databases, with duplicates removed. The Venn diagram of the OSMF-associated targets and the putative targets of curcuma molecules was made using the R software to obtain curcuma and OSMF common targets and the corresponding network was visualized using Cytoscape software.The SymMap database, accessed at https://www.string-db.org/, to perform the PPI analysis. The PPI network was visualized by importing the tsv-based file to Cytoscape software (3.8.1). The species must be “Homo sapiens” and high confidence for interaction score must not less than 0.4. In the PPI network, nodes reflect proteins and connecting lines represent PPIs. The core genes ranked according to degree value obtained using cytoHubba plug-in of Cytoscape.The curcuma and OSMF common targets were mapped into the STRING database, accessed at P value, and the top 20 pathways and top 10 GO functions were visualized as bar plots and bubble plots using the “Pathview” package in R software.Gene ontology (GO) functional analysis and pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) were implemented to harvest the potential functions of the disease-drug common targets by using the “clusterProfiler” package in the R software. The results of GO analysis were presented at the three levels: biological processes, molecular functions, and cellular components. The GO terms at three levels and significant KEGG pathways enrichments were ranked by https://www.rcsb.org/. Then, we converted the pdb-based files containing curcuma and the proteins encoded by core targets into pdbqt-based files and search for active pockets. The AutoDockTools was employed to determine the binding ability of ligands and receptors. The binding energy less than 0 indicates spontaneous binding of ligand and receptor, and smaller values reflect higher binding activity.Molecular docking technology is a well-recognized method to examine receptor-ligand interactions along with binding patterns and affinities. Therefore, we performed molecular docking analysis between curcuma and the top core target genes in the PPI network. The pdb format of the 3D structure of the proteins encoded by the top core target genes were downloaded from the RCSB Protein Data Bank (PDB) database, accessed at After searching the SymMap database, we collected 290 putative targets of curcuma molecules in total and then convert these molecule names into gene symbols in the UniProt database. With regard to the known therapeutic targets of OSMF, 600 targets were identified, with 578 collected in the GeneCards and 22 collected in the OMIM. Then, by using Venny 2.1 drawing software, we sorted 64 druggable targets of curcuma which were also therapeutic targets of OSMF . We thenWe imported 64 curcuma and OSMF common targets into the STRING database for PPI analysis. As shown by the PPI network in P < 0.05). P < 0.05). Next, we further analyzed 64 curcuma and OSMF common targets by GO annotation and KEGG pathway analyses. After GO analysis, 1736 GO terms, in total, were found to be significantly enriched by curcuma and OSMF common targets , which is considered to be a non-toxic and safe substance for food uses and therapeutic purposes. Previous studies has proved its efficacy on various diseases such as type 2 diabetes mellitus , nonalcoα (−308) and IL-6 gene polymorphism [α and IL-6 [α and IL-6 levels increased in OSMF patients [P < 0.001) [In our study, according to network pharmacology method, we identified 64 common targets both acting on curcuma and OSMF through Venny 2.1 drawing software, and sorted the top 5 targets including ALB, TNF, TP53, IL6, and VEGFA as a result of PPI network. Human ALB gene encodes 609 amino acids and its expression is regulated by its promoter, transcription factor and intron. A case report of familial dysalbuminemic hyperthyroxinemia revealed that the patient showed extremely high serum free thyroxine concentration due to p.R242P mutation in the ALB gene . Barasa and IL-6 , and thepatients . TP53 ispatients . TP53 mupatients . VEGFA ipatients . Further< 0.001) .In the present study, we performed molecular docking method to evaluate the binding energy of curcuma to the top 5 targets, and ALB with -9.5 kcal/mol and VEGFA with −8.9 kcal/mol stood out. Previous studies manifested that the conjugation of curcuma and ALB increased the aqueous solubility of the drug, leading to favorable immunomodulatory activity with increase in total leukocyte count, platelet count, and viable cell count in bone marrow. Besides, this conjugation was helpful to inhibit tumor deterioration in model of mice with Dalton's lymphoma ascites . Oral adOf note, our study has several limitations. First, the findings in our study obtained by a network pharmacology-based approach followed by molecular docking technology need to be verified in cellular and animal model. Second, we need more database screening common targets to improve the reliability of analysis or gene expression profiling of OSMF sample compared to control can be used to obtain more validated targets of OSMF. Third, the expression patterns of ALB, TNF, TP53, IL6, and VEGFA, the regulation of curcuma on these targets in the setting of OSMF are warranted to receive experimental validation. Forth, the exact therapeutic mechanism of curcuma against OSMF should be clearly explained in the future, such as anti-inflammatory, antioxidant, or wound healing effects. Network pharmacology has been widely used for drug-target-pathway analysis , where wIn conclusion, the study illustrated that the therapeutic effects of curcuma on OSMF were achieved by targeting ALB and VEGFA. Accordingly, the study thoroughly elucidated the molecular mechanism responsible for the therapeutic effects of curcuma on OSMF, which not only can facilitate the design and application of curcuma but also may bring more profound therapeutics for minimize the symptoms and healing oral mucosal lesion thus improving mouth opening in the context of OSMF.


Using network pharmacology and molecular docking, we explored the mechanism of Angelicae Pubescentis- (AP-) Herba Taxilli (HT) in the treatment of osteoarthritis (OA).  We selected Traditional Chinese Medicine Systems Pharmacology platform (TCMSP) to filtrate the practical components and targets of AP-HT. The disease targets of “osteoarthritis (OA)” were collected by GeneCards, DrugBank, TTD, OMIM, and PharmGKB databases, and the component-target interaction network was established by Cytoscape 3.9.1. Then, we set the protein-protein interaction (PPI) network by the STRING platform and visualized by Cytoscape 3.9.1. We also conducted Gene Ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis via the bioinformatics platform. Finally, we performed molecular docking using PyMOL 2.3.0 and AutoDock Vina software.  11 potential compounds were selected, and 1007 OA disease targets were collected. Ninety-four main targets of the AP-HT compound in the treatment of OA have been defined. PPI network demonstrated that JUN, RELA, TNF, IL6, MAPK1, TP53, AKT1, FOS, IL10, and MYC might serve as the critical targets of AP-HT for the treatment of OA. Moreover, membrane raft, membrane microdomain, cellular response to chemical stress, and cytokine receptor binding may play essential roles in the treatment of OA via GO analysis. The main functional pathways involved in these critical targets include fluid shear stress and atherosclerosis, lipid and atherosclerosis, IL-17 signaling pathway, age-range signaling pathway in diabetic composites, and TNF signaling pathway via KEGG analysis. The results of molecular docking showed that the critical ingredients of AP-HT had an excellent affinity to related nuclear genes. Osteoarthritis (OA), also called degenerative osteoarthritis, degenerative arthritis, senile arthritis, and hypertrophic arthritis, is a degenerative joint disease, mostly occurring in the elderly, and is bound up with many factors such as age, weight, gender, and trauma . The cliThe main methods of OA treatment are regular exercise, proper weight loss, and education about local or oral NSAIDs among patients without contraindications. An intra-articular steroid injection can relieve pain in a short time, such as duloxetine . In the The material basis of efficacy and molecular mechanism of the above two drugs still need to be fully understood. Therefore, this study is aimed at analyzing the active components, targets, and possible approaches of AP-HT treating OA.Network pharmacology is a kind of technology and knowledge involving bioinformatics, multidirectional pharmacology, computer science, and other disciplines . It can TCMSP contains 499 herbal TCM and 12144 components of TCM, a shared database for studying TCM network pharmacology. The compounds stemming from AP-HT were assembled from TCMSP. Use the indexes of absorption, distribution, metabolism, and excretion (ADME) to screen the blood entering active components of AP-HT. To obtain compounds for further analysis, we screened the candidate compounds that met the following parameters, including oral bioavailability (OB) ≥ 30% and drug − likeness (DL) ≥ 0.18.Through the component's target prediction function in TCMSP, the targets of AP-HT components in the blood were collected. For the convenience and accuracy of data expression, the “protein name” of the targets was converted into “gene name” in the UniProt database.This study collected relevant disease target data using GeneCards, DrugBank, TTD, OMIM, and PharmGKB databases. Use “OA” or “osteoarthritis” keywords to search relevant disease genes. Eliminate targets with correlation values below 1 in the GeneCards database to improve data reliability. Map the drug targets with the disease targets, display the results in a Wayne diagram, and then preliminarily obtain the intersection targets of AP-HT and osteoarthritis, that is, the active target of AP-HT in the treatment of OA.The Cytoscape software, as an optical network construction and analysis software, is a typical software for the visual analysis of traditional Chinese medicine network pharmacology. Input target data of AP-HT treating OA, active components, and osteoarthritis collected above into the Cytoscape (version 3.9.1) software. In the network, nodes represent effective ingredients of AP-HT and disease targets of OA. Edges represent the relationship between components and targets. Then, the mechanism of AP-HT treatment of OA was preliminarily discussed by constructing and analyzing the network of compound-disease targets.The STRING database is a commonly used database for constructing protein-protein interaction (PPI) networks. It contains the protein-protein interaction relationships of various methods, including calculation, experiment, and literature. The STRING online database is used to construct the interaction network between overlapping targets to understand their interactions further. When constructing the network, the setting option is “Homo sapiens” and a confidence score ≥ 0.900 (highly trusted). Moreover, export the network diagram as a table and pictures, respectively. Construct and analyze the network by Cytoscape (version 3.9.1).p value is defined as < 0.05 and the q value as < 0.05.Use the bioinformatics platform to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to analyze the critical target mechanism of AP-HT in the treatment of OA. When species select “human,” the We selected molecular docking to verify the correlation of compounds in pharmacological network research. Its simulation is also applicable to promising targets. Select the PubChem database to download the 2D deconstruction of compounds and then save it as a file in mol2 format. The 3D structure of the OA docking targets (top 5 degrees in the PPI network) treated by AP-HT was downloaded from the Worldwide Protein Data Bank (PDB) database. They were imported to AutoDock Tools for hydrogenation, dehydration, and other pretreatments of dehydration. Then, the receptor molecules were docked, and the ligand was analyzed for its binding activity. The commonly used molecular image software PyMOL was used to visualize molecular docking results.By searching the TCMSP database, 99 different active ingredients of AP and 46 of HT were screened. After screening the conditions (OB and DL), 11 active compounds were included, including 9 compounds from AP (81.82%) and 2 compounds from HT (18.18%) (Supplementary Table 1).Excluding the intersecting targets in the database, 1007 OA disease targets were collected, including 885 targets in the GeneCards database, six in the OMIM database, 142 in the DrugBank database, 11 targets in the TTD database, and four targets in the PharmGKB database. See A total of 175 targets of active components of AP-HT and 1007 targets of OA disease were collected. See The network of compounds targeting disease was constructed using the nine significant components and 94 core targets . It can The PPI network is constructed and analyzed to further explore the interaction between overlapping targets. The intersection targets were imported into the STRING database to construct a PPI network. Set the PPI reliability to 0.9 (highly reliable) and then output the network information. The PPI network is constructed by using Cytoscape (version 3.9.1) . The larSome areas with high density in PPI complex networks are called communities or modules. The network inside the module is the potential subnet of the PPI network. The subnet connection density is high, and the regional part has few connections. Therefore, the module is considered to be a collection of biological significance. In order to more accurately analyze the mechanism of action of AP-HT in the treatment of OA, it is necessary to further identify its intrinsic modules after obtaining the PPI network of AP-HT in the treatment of OA Figures .The molecular function GO enrichment analysis was performed on the expected action targets. Four 4161 GO items were obtained, including 3642 BP, 199 CC, and 320 MF. The results showed that AP-HT treatment of OA mainly involved BP, CC, and MF, three aspects of mediation. BP mainly includes response to lipopolysaccharide, response to molecule of bacterial origin, cellular response to chemical stress, reactive oxygen species metabolic process, regulation of reactive oxygen species metabolic process, response to oxidative stress, cellular response to oxidative stress, response to reactive oxygen species, response to the metal ion, and response to oxygen levels. CC (cellular component) is mainly enriched in “membrane raft,” “membrane microdomain,” “transcription regulator complex,” and “RNA polymerase II transcription regulator complex.” MF (molecular function) is mainly enriched in cytokine receptor binding, cytokine activity, receptor live activity, signaling receptor activator activity, and others .KEGG biological pathway enrichment analysis was carried out for the overlapping action targets. KEGG pathway analysis of the core targets enriched two hundred seventeen signal pathways. See −1, showing reasonable binding force.The top 5 targets of the degree are JUN, RELA, TNF, IL6, and MAPK1. The docking targets with active components with the highest degree of quercetin of AP-HT were docking . As showSome data show that OA affects about 300 million people every year and could affect many joints of the whole body. The commonly involved joints involve the knee joint, hip joint, spine joint, and small joints of the hand . OA has κB pathway. These signal pathways can effectively inhibit the production of proinflammatory cytokines and reduce the loss of type II collagen so Duhuo-Jisheng decoction can slow down the joint disease process [Duhuo-Jisheng decoction is a traditional recipe for treating osteoarthritis. Cartilage erosion is an essential indicator of OA. Studies by Liu et al. show that Duhuo-Jisheng decoction can participate in SDF-1/CXCR4/NF- process . The res process . Zhang e process .β-sitosterol, acetate, and Angelica sinensis ketone are the main practical components of AP-HT drug pair. The research conducted by Hu et al. showed that quercetin could not only increase osteoblast differentiation but also inhibit osteoclast bone resorption and induce its apoptosis to maintain the balance of bone metabolism and prevent the further development of OA [κB (NF-κB), activator protein-1 (AP-1), mitogen-activated protein kinase (MAPK), reactive nitric oxide synthase (NOS), and inflammatory C-reactive protein (CRP). A study conducted by Li et al. has shown that quercetin can improve cartilage repair under an OA environment by inhibiting inflammation and apoptosis of chondrocytes, regulating the polarization of synovial macrophages to M2 macrophages, and creating a chondrogenic environment for chondrocytes, thus playing a role in cartilage protection [β-sitosterol could inhibit synovial angiogenesis by affecting the proliferation and migration of endothelial cells, thus reducing joint swelling and cartilage damage in CIA mice. It can inhibit the expression of the VEGF signaling pathway, slow joint inflammation, and improve the damage of bone and cartilage [AP-HT is the central drug pair in Duhuo-Jisheng decoction and has specific therapeutic effects on OA. The internal regulation of disease by the body is a very complex process. A single target or a single signal pathway cannot play a therapeutic role. Different targets and signal pathways must be related and cooperate to play a role. The results of TCMSP database retrieval and “component target” network analysis in this study showed that quercetin, beta-sitosterol, o-acetylcolumbianetin, angelicone, quercetin, nt of OA . Quercetotection . Throughartilage .The PPI network analysis results of AP-HT in the treatment of OA showed that among the 94 target proteins, JUN, RELA, TNF, IL6, MAPK1, TP53, AKT1, FOS, IL10, and MYC ranked in the top of the node degree value, which may be the critical targets for AP-HT to exert the therapeutic effect. Studies by Cen et al. showed that CXCL8 might play an essential role in the migration of CD4+ T cells mediated by bone marrow mesenchymal stem cells (MSCs), and the autophagy of MSCs is positively correlated with the expression of CXCL8 mRNA, thus participating in the inflammatory response . IL6 is AKT1 is a serine/threonine protein kinase. Studies have shown that AKT1 is related to cell apoptosis, and inhibiting the expression of AKT1 can promote chondrocyte apoptosis . HMOX1 cRheumatoid arthritis is an inflammatory disease that invades the joint synovium. Inflammatory factors and proliferative synovium tissue destroy the articular cartilage and subchondral bone, resulting in enhanced osteoclast activity, thus accelerating the process of bone resorption. Inflammatory reactions include human cytomegalovirus infection, hepatitis B, and salmon infection. In the process of disease development of OA, inflammatory factors participate in cartilage erosion and accelerate the development of OA [The results of the KEGG enrichment analysis showed that AP-HT could treat OA through multiple signal pathways. Potential targets are mainly enriched in the AGE-RAGE signaling pathway in diabetes complications, lipids and atherosclerosis, fluid shear stress and atherosclerosis, IL-17 signaling pathway, TNF signaling pathway, and others. They mainly involve complex biological processes such as cell differentiation, apoptosis, metabolism, and inflammatory response. Cell differentiation and apoptosis include the TNF signaling pathway, MAPK signaling pathway, HIF-1 signaling pathway, and C-type lectin receptor signaling pathway. The HIF-1 signaling pathway is a hypoxia signaling pathway, which can effectively enhance the osteogenic and angiogenic differentiation ability of bone marrow mesenchymal stem cells. MAPK regulates cell proliferation and differentiation and plays a vital role in maintaining bone metabolic balance. Metabolic-related signaling pathways include AGE-RAGE signaling pathways in diabetic complications, rheumatoid arthritis, and endocrine resistance. nt of OA .To sum up, the potential practical components of AP-HT for the treatment of OA mainly include quercetin, beta-sitosterol, o-acetylcolumbianetin, angelicone, and others. These components above can play a therapeutic role in OA by directly or indirectly participating in cell differentiation, apoptosis, metabolism, and inflammatory response and have the characteristics of multicomponent, multitarget, and multisystem. Based on the network pharmacology analysis, we can obtain the possible practical components and potential action targets of AP-HT in the treatment of OA. However, this study is only a prediction analysis, and the above conclusions and specific mechanisms of action need to be demonstrated in subsequent studies.


The molecular mechanism of Reduning (RDN) in the treatment of sepsis was analyzed based on network pharmacology. The system pharmacology method was administered to search the active ingredients and targets of RDN, identify the sepsis-related genes, and determine the targets of RDN in the treatment of sepsis. Cytoscape was used to build a “drug component-target” network to screen key compounds. A protein-protein interaction (PPI) network was constructed using STRING, and core targets were revealed through topological analysis. 404 shared targets of RDN and sepsis were introduced into DAVID Bioinformatics Resources 6.8 for GO and KEGG enrichment analysis to predict their possible signaling pathways and explore their molecular mechanisms. GO enrichment analysis highlighted that they were largely related to protein phosphorylation, inflammatory reaction, and positive regulation of mitogen-activated protein kinase (MAPK) cascade. KEGG enrichment analysis outlined that they were enriched in PI3K-AKT signaling pathway, calcium signaling pathway, rhoptry-associated protein 1 (Rap1) signaling pathway, and advanced glycation end products and receptors for advanced glycation end products (AGE-RAGE) signaling pathway. Molecular biological validation results exposed that RDN could significantly improve the protein expression of p-AKT and p-PI3K, alleviate apoptosis-related proteins expression level and decrease apoptosis rate in LPS-induced HUVECs. In conclusion, it was illustrated that RDN could considerably constrain LPS-induced apoptosis by activating the PI3K-AKT signaling pathway, which advocated a basis for fundamental mechanism research and clinical application of RDN in the treatment of sepsis. Sepsis is a common disease in critically ill patients. Despite significant advances in early diagnosis and organ function support in patients with sepsis over the past few decades, sepsis continues to have high morbidity and mortality rates . Anti-inhttps://tcmspw.com/tcmsp.php/). Using oral bioavailability (OB)≥30% and drug-like activity (DL)≥0.18 as screening conditions, a total of 49 active ingredients were screened. We used the Pubchem database (https://pubchem.ncbi.nlm.nih.gov/) to retrieve active TCM ingredients, and then put simplified molecular input line entry system (SMILE) numbers into SwissTarget Prediction platform to acquire targets of TCM.The corresponding active components of Artemisia annua, Honeysuckle and Gardenia jasminoides were searched using the pharmacologic database and analysis platform of TCM System  and OMIM database (https://omim.org/), target identification was conducted with “Sepsis” and disease target genes were obtained.Using GeneCards human genome database, DisGenet database , and the species was set as “Homo sapiens” to obtain the PPI network. Then, TSV files obtained from STRING database are imported into Cytoscape software to conduct topological analysis of PPI network and screen out key target genes of compounds acting on diseases according to degree value ranking.The PPI network was constructed by inputting the common targets of drug and disease into STRING database  to analyse GO enrichment, including biological processes , cell Component (CC) enrichment, and molecular function (MF). p-value Cutoff = 0.05, q-value Cutoff = 0.05, the rest defaults to original settings. The shared targets were imported into DAVID Bioinformatics Resources 6.8 to clarify KEGG pathway enrichment. We chose the top 10 pathway according to p-value and employed microbioinformatics (http://www.bioinformatics.com.cn/) to visualize.Shared targets of RDN and sepsis were imported into DAVID Bioinformatics Resources 6.8 (http://www.rcsb.org/). Then, AutoDock software was administered to prepare the ligands and proteins required for molecular docking. The crystal structure of the target protein was removed water molecules, hydrogenated, modified amino acids, optimized energy and adjusted field parameters, and then the low energy conformation of the ligand structure was satisfied.The compound name, molecular weight and 3D structure of the active ingredients were determined from PubChem database, and the corresponding 3D structure of the active ingredients were downloaded from RCSB PDB database . Goat anti-mouse IgG second antibody, goat anti-rabbit second antibody, anti-cleaved-Caspase-3, and anti-PI3K-AKT signaling pathway antibody were from Abcam (United States). fluorochrome-conjugated secondary antibody was from Biosharp (China). Annexin V -FITC/7-AAD Apoptosis Kit, 10% fetal bovine serum, and Cell Counting Kit were from Beyotime (China).Human Umbilical Vein Endothelial Cells (HUVECs) cultivated by Laboratory of Tsinghua Changgung Hospital were cultured in an Incubator  under standard Conditions . The experiments were performed after two passages. Cells were cultured in Dulbecco’s ModifIed Eagle Medium (DMEM), high glucose  containing.Cell apoptosis level was probed by flow cytometry. HUVECs were washed twice with phosphate-buffered saline (PBS) and resuspended in 100 µl of 1×binding buffer mixed with 2.5 µl of annexin-V–FITC and 2.5 µl of 7-AAD staining solution for 15 min in the dark at room temperature. And then, with 400 µl additional binding buffer added into mix, the cells were finally evaluated using a flow cytometer . 7- AAD and annexin-V assay Q2 + Q3 were used to perform the apoptosis rate.Total protein was extracted from cells using the cell lysate and placed on a shaker for 15 min for full contact at 4°C. Samples were electrophoresed in 10% SDS-Page gel and electrophoresis transferred onto a polyvinylidene fluoride membrane. Then, the membrane was blocked in 5% dried milk at 4°Covernight. After centrifugation, The protein concentrations were quantified using the BCA Protein Assay kit . The membrane was sealed with milk powder and then incubated with primary antibody at 4°C, followed by incubation with goat anti-mouse IgG secondary antibody for luminescence.4/well in 100 μl medium. Then, the cells were stimulated by LPS (and RDN). After treating for certain (6 h/12 h/24 h) hours, 10 μl of CCK-8 reagent was added to each well and then cultured for 2 h. All experiments were performed in triplicate. We applied wells without cells as blanks. The proliferation of cells was expressed by the absorbance. The absorbance was analyzed at 450 nm using a microplate reader .Cell viability was detected by Cell Counting Kit-8 following protocols. Cells were seeded and cultured into 96-well microplates with a density of 2×10The pretreated cover glasses which cells inoculated into were removed after the cells were nearly monolayer, and then washed twice with PBS. The cells were fixed in 4% paraformaldehyde for 15 min and then permeabilized in 0.3% Triton X 100 for 30 min. The cells were blocked with 5% bovine serum albumin (Sigma-Aldrich) for 30 min at 37°C and exposed to the primary antibody overnight at 4°C. The next day they were washed in PBS and then incubated for 60 min at room temperature with species-appropriate fluorochrome-conjugated secondary antibody. Images were acquired using an Olympus camera and matched software. The operator and analyzer were blinded to the experimental condition and quantified with ImageJ.t-test was used for the comparisons between two groups. ANOVA was used to make comparisons betweenSPSS 22.0 (United States) was used to interpret all statistical analysis. Statistical analysis was completed with the data from three independent experiments. p-value < 0.05 was regarded with statistical significance. Furthermore, Prism 8  was responsible for visualizing.Multiple groups. Data are presented as mean±standard deviation (SD), The corresponding active components of Artemisia annua, Honeysuckle and Gardenia jasminoides were searched using the pharmacologic database and analysis platform of TCM System. Using OB ≥ 30% and drug-like activity DL ≥ 0.18 as screening conditions, a total of 49 active ingredients were screened. We used the Pubchem database to retrieve active RDN ingredients, and then put SMILE numbers into SwissTarget Prediction platform to acquire 782 targets of RDN (supplementary data).Using GeneCardard human genome database, DisGenet database and OMIM database, with “Sepsis” as a search term targets for retrieval, we acquired 3402 sepsis targets (supplementary data).Venny 2.1 online software mapping tool platform was used to input 782 RDN drug targets and 3402 sepsis targets to draw Venny diagram. After intersection of the two, 404 drug-disease common targets were obtained , indicatCytoscape 3.7.2 software was applied to build a network diagram of “RDN-component-target-sepsis”. Potentially active components and drug-disease targets were input into Cytoscape software, and the interaction network of “RDN components target sepsis” was plotted .p-value; the smaller the p-value, the redder the color is; the larger the p-value, the bluer it is.As shown in As shown in Five key target structures and the five key active component structures were docked, and their Affinity  value represented the binding ability of the two. The lower the binding ability, the more stable the ligand and receptor binding. Finally, Discovery Studio software was used to analyze and observe the docking results. The key active ingredients Stigmasterol, Kaempferol, Quercetin, beta-sitosterol and Corymbosin were verified by molecular docking with the key targets AKT1, TNF, IL6, GAPDH and MAPK3. The results show that they all have good binding activity. The four results with the highest beating rank are selected and analyzed in charts. The results are shown in p < 0.05). The OD value in LPS group was not significantly different from that in Con group when LPS was injected at 0.25 μg/ml (p > 0.05). The OD value in LPS group was significantly higher than that in Con group when LPS was injected at 0.5 μg/ml, 1 μg/ml, and 2 μg/ml (p < 0.05). We selected 1 μg/ml LPS for the following experiment. Next, we carried out the study with different concentrations of RDN injection  and LPS to identify effective time point and RDN concentration. The LPS + RDN group was pretreated with cells diluted into different concentrations of RDN injection  for 1h, and then stimulated with 1 μg/ml LPS for 6h, 12h and 24 h to simulate sepsis. As shown in p < 0.05). To make the study more operational, we chose 6 h as the efficient time point.In order to verify the reliability of the main effective targets and molecular mechanism of RDN in the treatment of sepsis predicted by network pharmacology experiments, LPS was selected to mimic septic cell model and RDN injection was selected as intervention. First, the effective time point and concentrations of LPS and were determined by CCK-8. LPS group was treated with different concentrations of LPS  for 6 h, 12 h, and 24 h. Control (Con) group was not treated with intervention. As shown in p < 0.005). Compared with LPS group, the protein expression level of p-AKT and p-PI3K were critically increased in LPS + RDN group (p < 0.001). There is no statistical difference between Con group and RDN group (p > 0.05).To further verify the effect of RDN on PI3K-AKT signaling pathway, western blot was employed to detect the results of network pharmacology analysis. As shown in p < 0.001). Compared with LPS group, the protein expression level of cleaved-Caspase-3 was critically decreased in LPS + RDN group (p < 0.001). Immunofluorescence was also used to investigate the level of apoptosis-related protein. As shown in p < 0.001). Compared with LPS group, the protein expression of cleaved-Caspase-3 was critically decreased in LPS + RDN group (p < 0.001). There is no statistical difference between Con group and RDN group (p > 0.05).Western blot was performed to detect the level of apoptosis-related protein. As shown in p < 0.001), RDN could critically alleviate it (p < 0.001), and the proportions of apoptosis cells were 4.73 ± 0.416, 42.24 ± 1.044, 4.44 ± 0.711, and 15.597 ± 0.662 in Con group, LPS group, RDN group, and LPS + RDN group respectively.Flow cytometry was performed to show apoptosis level. 7-AAD and Annexin-V assay Q2 + Q3 were used to exhibit the apoptosis rate. As shown in Sepsis 3.0 released in 2016 considers the occurrence of multiple organ dysfunction syndrome (MODS) as the key link in sepsis . Howeverin vitro  be passed on indefinitely, has been widely used in investigating apoptosis in sepsis . In our in vivo and in vitro.As with most studies, the design of the current study is apt to limitations. This study sorely investigated the potential mechanism of RDN on LPS-induced HUVECs apoptosis through PI3K-AKT pathway, but fell short of verifying the core target AKT1. However, we have demonstrated the binding ability of AKT1 and RDN in Molecular docking analysis, so this limitation will not cause a very large bias in the results of the study. We will continue to explore the mechanism by knocking out AKT1 In conclusion, this study applied the method of network pharmacology to study the complex molecular network relationship between RDN and sepsis, and found that RDN may regulate core genes such as AKT1, IL-6, TNF, and PTGS2 through active ingredients such as Stigmasterol, Kaempferol, Quercetin, beta-sitosterol, and Corymbosin, thus improving the endothelial cell damage caused by LPS. AKT1 may be the core target, and PI3K-AKT pathway may be the core pathway of RDN to improve the apoptosis of endothelial cells caused by LPS. This study may provide a new clue for molecular mechanism of RDN in the treatment of sepsis, and provide a certain basis for its clinical application.


At present, the world is faced with a shortage and rising prices of high-quality protein feed. Adequate utilization of unconventional feeds can alleviate this problem. China is the largest producer and exporter of seed-used pumpkin, and many byproducts of seed-used pumpkin need to be effectively utilized. In this study, we analyzed nutrient supply and biodegradation characteristics, and correlation and regression equations between them and protein molecular structure were established. This research provides a data basis for the utilization of byproducts of seed-used pumpkin and establishes a new method for evaluating the nutritional value of unconventional feeds.The purpose of this experiment was to explore the relationship of protein functional groups  in byproducts of seed-used pumpkin  with their nutrient profiles and biodegradation characteristics. The experiment was designed to use conventional chemical analysis, combining the Cornell Net Carbohydrate and Protein System (CNCPS) and nylon bag technology to assess the nutritional value and biodegradation characteristics of seed-used pumpkin byproducts. Fourier transform infrared spectroscopy (FTIR) was used to analyze the protein molecular structure properties of byproducts of seed-used pumpkin. In this study, we also applied correlation and regression analysis. The results showed that different byproducts of seed-used pumpkin had different in situ biodegradation, nutrient supplies, and spectral structures in the protein region. Among the byproducts of seed-used pumpkin, acid detergent-insoluble crude protein (ADICP) and neutral detergent-insoluble crude protein (NDICP) contents of the pumpkin seed coat were the highest, resulting in the lowest effective degradabilities (EDs) of dry matter and crude protein. The crude protein (CP) ED values were ranked as follows: pumpkin seed cake > seed-used pumpkin flesh > pumpkin seed coat. Significant differences were observed in the peak areas of amide I and amide II and the corresponding peak heights in the two peak areas in the molecular structure of the protein. The peak areas of amide I and amide II and the corresponding peak heights were at the highest levels for pumpkin seed cake, whereas there was no significant difference between the pumpkin seed coat and seed-used pumpkin flesh. Similarly, the peak heights of α-helices and β-sheets were highest for pumpkin seed cake. Correlation and regression results indicated that amide I and amide II area and height, α-helix and β-sheet heights, and area ratios of amide I: amide II, as well as the height ratios of amide I: amide II, and α-helices: β-sheets effectively estimated nutrient supply and that the height ratio of α-helices: β-sheets was mostly sensitive to biodegradation characteristics in different byproducts of seed-used pumpkin. There were significant differences in CP chemical composition and digestibility of different byproducts of seed-used pumpkin that were strongly related to the changes in protein molecular structures. Today, many countries are facing feed shortages, and high feed costs affect the economic benefits of pastures. The use of agricultural byproducts is an effective way to solve this problem. Seed-used pumpkin, a general term for pumpkins of which the seeds are the main edible organs or processing objects, belongs to the Cucurbitaceae family. China is one of the most important countries producing and exporting pumpkin seeds globally. The planting area and total output of pumpkin seeds in China rank first in the world ; therefoAs reported previously, the protein content of pumpkin seed cake is higher than 500 g/kg , which is higher than that of soybean meal ,3,4, andCompared with traditional wet chemistry analysis, Fourier transform infrared spectroscopy (FTIR) has been proven to be a bioanalytical technique that can quickly, noninvasively, and directly reveal the molecular structure of feeds . With thn = 3) were collected from corresponding byproducts, which were used as replicates. After drying in a forced-air oven at 55 °C for 48 h, all samples were chemically analyzed by a 1.0 mm screen and spectrally scanned twice by a 0.25 mm screen.Seed-used pumpkin collected from Heilongjiang Hexing Agricultural Products Company, Ltd. in Shuangyashan city, China, in early October 2018 was used in this study. In this study, three varieties  were selected as replicates. Fifty seed-used pumpkins were selected for each variety, and each seed-used pumpkin was manually separated into three parts . Additionally, pumpkin seed cake was obtained as a byproduct from oil production through pumpkin seed crushing by a physical cold-pressing method. Pumpkin seeds were processed using a spiral oil extractor (KYL-380 oil extractor) with a controlled temperature of 70 °C, moisture content of 7.5%, rotation rate of 36 r/min, and oil extraction rate of about 47%. Pumpkin seed cake was obtained after oil extraction of the pumpkin seeds. The samples (1 (rapidly degradable protein), PB2 (moderately degradable protein), PB3 (slowly degradable protein), and PC (undegradable protein).The AOAC method  was usedp = a + b (1 − exp(−ct)), where p = the rate of disappearance at time t (h): The in situ rumen degradation characteristics of DM and CP of the three byproducts of seed-used pumpkin were analyzed according to a method described previously . Three Ha = the rapidly degradable fraction (the soluble fraction); b = the slowly degradable fraction; c = rate at which degradation occurred (c > 0);a + b = potentially degradable fraction in rumen degradation. ED) was calculated, assuming a passage rate (kp) of 46 g/kg h−1 (pumpkin seed coat) or 60 g/kg h−1 (pumpkin seed cake and seed-used pumpkin flesh), by the equation:a, b, and c are the constants described above.The effective degradability  were collected by FTIR spectroscopy  in the Laboratory of Chemical Molecular Structure Analysis, College of Science, Northeast Agricultural University (Harbin). The mid-IR spectra were scanned 128 times in the range of approximately 4000~400 cm−1) and peak height position (ca. 1638 cm−1) and the amide Ⅱ band area (baseline: ca.1536~1488 cm−1) and peak height position (ca. 1528 cm−1). Fourier self-deconvolution (FSD) [−1) and β-fold peak height (ca. 1617 cm−1) in amide Ⅰ. Then, the peak height and area were recorded and statistically analyzed. The typical ATR-FT/IR molecular spectra of different byproducts of seed-used pumpkin are shown in OMNIC 8.2 software  was used to analyze the spectral data of all samples. The baseline position of the protein was determined in the software, as well as the amide Ⅰ band area (baseline: ca.1712~1576 cmon (FSD)  or the son (FSD)  was usedThe protein nutritional values, rumen degradation parameters, and spectral values of byproducts of seed-used pumpkin  were analyzed using the ANOVA procedure of the SAS software system . The statistical model was as follows: ijY = μ + iT + iE;ijY = dependent variable;μ = overall mean;iT = treatment effect;iE = error term.Using the Pearson correlation method and the PROC CORR program of SAS 9.4, we analyzed the correlation between the protein nutritional values and protein-related molecular-structure spectral parameters in different coproducts of seed-used pumpkin. Finally, regression analysis was performed using the PROC REG program of SAS 9.4.p < 0.05). Among these, pumpkin seed cake had the highest CP and SCP contents . The highest ADICP content was found in the pumpkin seed coat, which was significantly higher than that of the pumpkin seed cake and seed-used pumpkin flesh (p < 0.05), indicating that the pumpkin seed coat was not easily digested in the rumen. Seed-used pumpkin flesh had the highest NPN content, which was significantly higher than that of pumpkin seed cake and pumpkin seed coat (p < 0.05). From the perspective of CNCPS protein components, there were significant differences in the contents of PA, PB1, PB2, and PC in pumpkin seed cake, pumpkin seed coat, and seed-used pumpkin flesh (p < 0.05). Among these, seed-used pumpkin flesh had the highest PA content, which was significantly higher than that of pumpkin seed cake and pumpkin seed coat (p < 0.05), indicating that seed-used pumpkin flesh can be rapidly degraded in the rumen. Pumpkin seed cake had the lowest PC content (3.2 g/kg CP), indicating that pumpkin seed cake can provide more nitrogen sources for ruminants, whereas pumpkin seed coat had the highest content (498.4 g/kg CP) because its ADICP content was higher, which could make it difficult to digest in the rumen.p < 0.05) for different seed-used pumpkin byproducts . Among these, a, b, c, a + b, and ED of DM and CP in pumpkin seed coat were significantly lower than those of pumpkin seed cake and seed-used pumpkin flesh (p < 0.05). Compared with the pumpkin seed cake, seed-used pumpkin flesh had more rapidly degradable DM and CP (p < 0.05). However, the b and c values were higher in pumpkin seed cake than in seed-used pumpkin flesh (p < 0.05), so it is certain that they had a significant difference in their effective degradability of DM and CP. In the current research, the b, c, and ED values were ranked as pumpkin seed cake > seed-used pumpkin flesh > pumpkin seed coat; the a value was ranked as seed-used pumpkin flesh > pumpkin seed cake > pumpkin seed coat; and the a + b value of pumpkin seed coat was lower in the two other byproducts.p < 0.05). Additionally, the peak height ratio of the amide Ⅰ band and amide Ⅱ band of seed-used pumpkin flesh was significantly higher than that of pumpkin seed cake and pumpkin seed coat (p < 0.05). In addition, the peak height and peak area of the amide Ⅰ band, the peak height and peak area of the amide Ⅱ band, and the peak height and ratio of α-helices and β-sheets of pumpkin seed cake were significantly higher than those of pumpkin seed coat and seed-used pumpkin flesh (p < 0.05), indicating that the nutritional value of pumpkin seed cake protein is high.As shown in 1, and PB2 had a strong positive correlation  with amide I and II height and area. However, a negative correlation  was also found between DM, CP, and NDICP; the area ratio of amide I and amide II and the content of CP and PB2 correlated with the peak height ratios of amide I and amide II . The peak height ratios of α-helices and β-sheets were extremely significantly negatively correlated with DM, ADICP, and PC  and extremely significantly positively correlated with SCP and PB2 . Among them, the c values of DM  and CP  rumen degradation kinetics had a strong positive correlation with peak height, as well as the areas of amides Ⅰ and Ⅱ, the peak heights of α-helices and β-sheets, and the sum of the peak areas of amides Ⅰ and Ⅱ. The peak height ratio of α-helices and β-sheets had a very significant positive correlation with a, b, a + b, c, and their effective DM and CP degradation rates .In 2 = 0.995), CP (R2 = 0.973), SCP (R2 = 0.993), ADICP (R2 = 0.8796), PA (R2 = 0.980), PB2 (R2 = 0.972), and PC (R2 = 0.996) by the regression equation results. The kinetics of in situ degradation of DM and CP  in the rumen were predicted from the spectral features within protein regions.The height ratio of α-helix: β-sheet showed a strong ability to forecast the contents of DM  reached the same conclusion as this experiment [Studies have proven a correlation between the molecular structure of feed protein and its nutritional value, and protein spectral parameters can be used to predict the nutritional value and digestibility of feed ,37. Xin periment . The speperiment , which iperiment . From th2 as high as 0.99. According to Yu et al. (2003), the ratio of spectral parameters can more accurately predict feed quality and nutritional value [Changes in the molecular spectral structure of feed affects the nutritional value, digestive behavior, and utilization of the feed . At presal value . AccordiThere were significant differences in the protein chemical profile, CNCPS subfraction, and rumen degradation kinetics of seed-used pumpkin byproducts. Among these byproducts, seed-used pumpkin flesh and pumpkin seed cake were shown to have high nutritional value and the ability to provide a nitrogen source for ruminants. The significant differences in the chemical profile of CP and the degradability of byproducts of seed-used pumpkin were closely related to the changes in the molecular spectral parameters of the protein. The regression equation shows that the height ratio of α-helices to β-sheets was a strong predictor of the protein chemical profile and degradability. It was initially proven that FTIR could be used to evaluate the nutritional supply and biodegradation characteristics of different byproducts of seed-used pumpkin.


Thyroid-associated ophthalmopathy (TAO) is a disfiguring autoimmune disease, which destroys the structure of orbital tissues and even threatens vision. Metabolic reprograming is critical in autoimmune diseases; however, the metabolic basis of TAO remains to be clarified. Our study aimed to reveal the metabolic profile of TAO.Orbital adipose/connective tissues from eleven TAO patients and twelve control subjects were collected during surgeries and analyzed with liquid chromatograph-mass spectrometer. Orthogonal partial least-squares discrimination analysis (OPLS-DA), variable importance in projection (VIP), heat map, and volcano plot were used to reveal metabolic profile in TAO. Pathway analysis and metabolites-gene analysis were utilized to explore potential metabolic metabolism in TAO.P < 0.05), including 367 increased metabolites and 226 decreased metabolites. Pathway analysis showed that changed metabolites were enriched in cholesterol metabolism, choline metabolism in cancer, fat digestion and absorption, regulation of lipolysis in adipocytes, and insulin resistance. In addition, metabolites-gene analysis illustrated that cholesterol metabolism was involved in the pathogenesis of TAO. Endoplasmic reticulum stress-related genes  expressions were higher in TAO orbital tissues than in control orbital tissues verified by western blot. Additionally, the expression level of diacylglycerol acyltransferase 1 (DGAT1), a key metabolic protein for triacylglycerol synthesis, was increased in orbital tissues of TAO detected by qRT-PCR, indicating disrupted cholesterol metabolism in TAO.3038 metabolites were detected in samples from the TAO patients and the controls. OPLS-DA analysis of the metabolomics results showed two distinguished groups, demonstrating that TAO has a unique metabolome. Univariate tests identified 593 dysregulated metabolites (The present study demonstrated different metabolite profiles and potential metabolic mechanisms in TAO. Thyroid-associated ophthalmopathy (TAO) is an autoimmune ocular condition frequently associated with thyroid dysfunction . Its annProptosis in TAO is primarily caused by an increase in the volume of extraocular muscles and orbital fat tissue. It has been reported that the enlargement of orbital fatty tissue contributes more toward the proptosis observed in TAO patients, than increased extraocular muscles volume . The infMetabolic reprograming has been shown to be a hallmark of TAO. Metabolism has been recognized as a target for modulation in autoimmune diseases . AdditioP < 0.05), including 367 increased metabolites and 226 decreased metabolites. According to the pathway analysis and metabolites-gene analysis, cholesterol metabolism might be involved in the pathogenesis of TAO.The metabolic condition of cell is reflected directly by the cell’s metabolites abundance. Metabolomics using a liquid chromatograph-mass spectrometer (LC-MS) is a quantitative and sensitive assessment for detecting metabolites –18. Here). Detailed characteristics of all TAO patients included in this study were summarized in The study participants were TAO patients who had undergone orbital decompression surgery and normal subjects who had undergone blepharoplasty at the Eye, Ear, Nose and Throat (ENT) Hospital, Fudan University. TAO was diagnosed based on the Bartley criteria , and TAOThe study was approved by the Ethics Committee of Eye & ENT Hospital, Fudan University (identification number: 2021082), and conducted in compliance with the Helsinki Declaration.Internal standard   and extraction solution with pre-chilled methanol in HPLC water  were added to each sample. Steel balls were added to the sample for homogenization. Then, sample was stored at -20°C for 30 min. The supernatant was transferred to a new tube after centrifugation and was then dried in a freeze concentration centrifugal dryer. Samples was reconstituted with methanol in HPLC-water  and then transferred to LC vials. Samples were stored at -80°C before LC-MS.LC-MS was performed as previously described in detail , 22. A DqRT-PCR was done as previously described . Total Rhttp://rsb.info.nih.gov/ij/index.html). Primary antibodies involved in IRE1α , PERK , ATF6 , and β-Actin  were used for western blot.The tissue was lysed by RIPA buffer containing proteinase inhibitors and phosphatase inhibitors . Protein concentration was evaluated by BCA protein assay kit . The proteins were separated on 4-16% gradient SDS-PAGE, and then transferred to PVDF membrane . The detection of chemiluminescence was performed as previously described .Western http://csbg.cnb.csic.es/mbrole2/) based on the Kyoto Encyclopedia of Genes and Genomes (KEGG). Interactions between metabolites and genes were analyzed using the MetScape plugin (v3.1.3) , variable importance in projection (VIP), heat map, and volcano plot . Pathway(v3.1.3)  in Cytos(v3.1.3) and netwo. Then, cross validation test was performed to validate the OPLS-DA model. The Q2 of -0.613 is less than 0.05, indicating high predictive relevance of the OPLS-DA model.We measured 3038 metabolites in samples from the TAO patients and the controls. OPLS-DA revealed a prominent distinction between the two groups in score plots, indicating that the metabolomes of orbital tissue from the patients with TAO were significantly changed. Then, c. To differentiate the altered metabolites in TAO, we performed volcano plot analysis with a threshold of P < 0.05. Among the 3038 metabolites, 593 metabolites (367 increased metabolites and 226 decreased metabolites) were significantly changed in the TAO samples . The changed metabolites were evaluated by calculating VIP score. High VIP score indicates significant group discrimination and 1 was selected as a cutoff for VIP score. Forty-two metabolites (VIP score > 1) were found. Notably, lidocaine, 5β-cholestane, monoethylglycylxylidide, triglyceride, pentadecylic acid, and 3’-deoxystreptomycin were the top altered metabolites (VIP score > 1.8)  . To diff. To diff. To diff. To diffP < 0.05). The significantly altered metabolic pathways were cholesterol metabolism, choline metabolism in cancer, fat digestion and absorption, regulation of lipolysis in adipocytes, and insulin resistance  were involved in predicted pathway (TG(20:0/20:1(11Z)/20:4), 1D-myo-Inositol 3-phosphate, and phosphocholine  are strongly related to cholesterol metabolism, choline metabolism in cancer, fat digestion and absorption, regulation of lipolysis in adipocytes, and insulin resistance. The important differentially expressed mRNAs involved in the pathogenesis of TAO have been clarified in our previous study  in orbital fat tissue samples from the patients with TAO. Pathway analysis and metabolite-genes analysis showed cholesterol metabolism was potentially involved in TAO pathogenesis. Similarly, in our previous KEGG analysis of different circular RNAs of TAO orbital adipose/connective tissue indicates cholesterol metabolism pathway is changed  KEGG pathway . InsulinConsidering that many factors affect metabolite changes in TAO, studies with larger sample sizes and various clinical stages are necessary to clarify the metabolite profiles in TAO. In addition, tracing these changed pathways with stable isotopes and exploring the role of the important enzymes are necessary to reveal the interactions of metabolic pathways.In summary, A total of 593 metabolites differed significantly between TAO and control participates. Our study indicates a significant difference in the metabolic profiles of TAO, showing that TAO alters cellular metabolome, especially cholesterol metabolism. This study should shed light on the molecular pathogenesis of TAO and provide therapeutic benefits of targeting the changed metabolic pathwaysThe original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethics Committee of Eye & ENT Hospital, Fudan University. The patients/participants provided their written informed consent to participate in this study.JH, LW, and CZ designed research. JH, LW, MC, YL, WX, YH, YZ, and CZ performed research. JH, LW, MC, YL, WX, YH, YZ, and CZ analyzed data. JH, LW, and CZ wrote the paper. All authors contributed to the article and approved the submitted version.This study was supported by the Shanghai Natural Science Foundation (20ZR1409800 to LW), the National Natural Science Foundation of China , Shanghai Outstanding Academic Leaders (2017BR013 to CZ), and Excellent Academic Leaders of Shanghai (18XD1401000 to CZ).We thank Professor Jiang Qian  for providing orbital adipose/connective tissues.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Rationale: Fluorescently traceable prodrugs, which can monitor their biodistribution in vivo and track the kinetics of drug delivery in living cells, are promising for constructing theranostic medicines. However, due to their charge and hydrophobicity, most of the fluorescently traceable prodrugs exhibit high protein binding and non-specific tissue retention affecting in vivo distribution and toxicity, with high background signals.Methods: Herein, the zwitterionic rhodamine (RhB) and camptothecin (CPT) were bridged with a disulfide bond to construct a tumorous heterogeneity-activatable prodrug (RhB-SS-CPT). The interaction of zwitterionic RhB-SS-CPT with proteins was detected by UV and fluorescence spectroscopy, and further demonstrated by molecular docking studies. Then, intracellular tracking and cytotoxicity of RhB-SS-CPT were determined in tumor and normal cells. Finally, the in vivo biodistribution, pharmacokinetics, and anticancer efficacy of RhB-SS-CPT were evaluated in a mouse animal model.Results: The tumorous heterogeneity-activatable RhB-SS-CPT prodrug can self-assemble into stable nanoparticles in water based on its amphiphilic structure. Particularly, the zwitterionic prodrug nanoparticles reduce the non-specific binding to generate a low background signal for better identification of cancerous lesions, achieve rapid internalization into cancer cells, selectively release bioactive CPT as a cytotoxic agent in response to high levels of GSH and H2O2, and exhibit high fluorescence that contributes to the visual chemotherapy modality. In addition, the RhB-SS-CPT prodrug nanoparticles show longer circulation time and better antitumor activity than free CPT in vivo. Interestingly, the zwitterionic nature allows RhB-SS-CPT to be excreted through the renal route, with fewer side effects.Conclusions: Zwitterionic features and responsive linkers are important considerations for constructing potent prodrugs, which provide some useful insights to design the next-generation of theranostic prodrugs for cancer. Therefore, it is evident that the physicochemical properties of fluorescent probes, including charge density and distribution, hydrophilicity/hydrophobicity, etc., can influence the in vivo behavior of prodrugs. However, due to the variety of physiological components that exhibit interactions with prodrugs, the in vivo fate of fluorescently traceable prodrugs remains poorly understood.For the precise diagnosis and treatment of cancer, prodrugs are typically created by conjugating drugs to molecular probes via stimuli-responsive linkages that permit the release of bioactive drugs in response to endogenous factors in tumor cells 2O2), the redox-responsive disulfide bond was used to link RhB with CPT Previous studies have demonstrated that electrostatic and hydrophobic interactions are the main driving force for non-specific binding 4. The organic phase was removed, and the crude product was separated and purified by silica gel column chromatography using CH2Cl2:CH3OH  as eluent to give a red solid as RhB-SS-CPT. Yield: 29.3%. 1H NMR  δ (ppm): 8.67 , 8.32 , 8.11 , 7.89 , 7.78 , 7.69 , 7.49 , 7.31 , 7.22-7.16 , 6.84 , 6.58 , 5.34 , 5.12 , 3.47 , 3.17 , 3.04 , 2.13 , 1.22 , 0.93 . 13C NMR : δ (ppm): 169.32, 168.98, 167.45, 157.68, 157.26, 155.59, 146.81, 145.32, 141.76, 133.78, 133.52, 128.51, 128.21, 128.14, 127.93, 127.65, 120.11, 114.30, 114.25, 114.09, 113.98, 96.52, 95.51, 66.36, 50.12, 45.89, 42.51, 42.13, 40.48, 39.49, 31.71, 31.44, 30.20, 29.69, 22.56, 14.16, 12.66, 7.63. MS: calculated for C53H54N6O12S4 (M): 1095.285; found: 1095.168 (M).The CPT-SS-COOH , compound 5 , and HBTU  were dissolved in dichloromethane (25 mL) at 0 °C in nitrogen atmosphere. After stirred for 0.5 h, DIPEA  was added dropwise. The reaction was continued at room temperature for 5 hours, then washed with 5% HCl (10 mL), water (20 mL), and dried over NaSOhttps://www.rcsb.org/) and then prepared by AutoDock 1.5.6, including deletion of ligand and addition of charges. The structure of zwitterion RhB is optimized using GaussView 6.0 with DFT method. We used AutoDock 1.5.6 and Pymol to construct the 3D models of BSA and zwitterion RhB, and simulate the 1:1 bound conformation. The docking results yielded the 30 most-trusted ligand configurations, and the interactions between RhB-BSA were given by Discovery Studio 2016.The crystal structure of BSA (PDB entry: 4f5s) was retrieved from RSCB database  were injected subcutaneously into the right hind leg of female nude mice . When the tumor volume reached approximately 100 mm3, mice were intravenously administrated with free CPT or RhB-SS-CPT nanoparticles at a dose of 5 mg/kg equivalent to CPT (n = 5 for each group). Saline was used as control. The free CPT or RhB-SS-CPT nanoparticles were injected every three days for 20 days. The mice were sacrificed after 21 days of treatment, and the heart, liver, spleen, lung, kidney and tumors were collected for hematoxylin and eosin (H&E) staining and analysis.4T1 cells  effect.The prodrug RhB-SS-CPT is soluble in organic solvents. UV-Vis absorption and fluorescence spectroscopy were used to determine the optical properties of the RhB-SS-CPT prodrug. As shown in Figure M Figure C, which M Figure D. As conM Figure E & 2F. BOur initial expectation was that the zwitterionic probe provided a key structure for the self-assembled nanoparticles to exhibit low protein binding and improved stability in the presence of serum. We characterized the RhB-SS-CPT prodrug in cell culture media (with 10% FBS) using UV-Vis absorption and fluorescence spectroscopy Figure A & B. Ab2O2 and GSH simultaneously, allowing for intracellular drug release on demand. Fluorescence spectra of RhB-SS-CPT upon reactions with GSH or H2O2 were analyzed to determine the active drug release behavior of the prodrug containing a disulfide bond. At H2O2 concentrations above 100 mM . The mass spectra of RhB-SS-CPT treated with GSH showed a molecular weight of 980.034 , 675.083 , and 613.179 , suggesting that a disulfide bond- thiol bond exchange reaction occurred . The zwitterionic RhB-SS-CPT nanoparticles showed much lower cellular uptake in the first 30 min compared to the charged sulforhodamine B Figure A & B. Thin vivo distribution of RhB-SS-CPT nanoparticles in 4T1 tumor-bearing nude mice was investigated. At predetermined time intervals, mice were sacrificed, and their heart, liver, spleen, lung, kidneys, and tumors were harvested for fluorescence signals analysis. As shown in Figure 8 p/sec/cm2/sr) in tumor was achieved at 12 h after injection. The backgrounds in nontumor tissues such as heart (0.45 ± 0.07 ×108 p/sec/cm2/sr), spleen (0.88 ± 0.16 ×108 p/sec/cm2/sr), and lung (1.4 ± 0.4 ×108 p/sec/cm2/sr) were much lower, indicating a higher selectivity for RhB-SS-CPT in tumor  that can track drug delivery kinetics and monitor Supplementary figures, materials and methods.Click here for additional data file.


Crataegus pinnatifida Bge. var. major N.E. Br. or Crataegus pinnatifida Bge) and Alisma rhizoma  Juzep or Alisma plantago-aquatica Linn), a classic combination of herbs, have been widely used to treat dyslipidemia. However, the therapeutic mechanism of this pair still remains unclear. Hence, this study aimed to elucidate the molecular mechanism of the Shanzhaye-Zexie herb pair (SZHP) in the treatment of dyslipidemia with the use of a network pharmacology analysis approach.  Dyslipidemia has become a critical global issue for public health, with elevating prevalence and morbidity closely related to many cardiovascular diseases (CVD) with high incidence rates. Crataegi Folium  and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed on the database for annotation, visualization, and integrated discovery (DAVID 6.8). The compound-target-disease-pathway network was visualized using the Cytoscape software, and SYBYL was used for molecular docking.  Twelve active compounds in the SZHP were screened out, which were closely connected to 186 dyslipidemia-related targets. The network analysis revealed that sitosterol, stigmasterol, isorhamnetin, kaempferol, and quercetin might be candidate agents and CCND1, CASP3, HIF1A, and ESR1 genes were potential drug targets. GO analysis revealed 856 biological processes (BP), 139 molecular functions (MF), and 89 cellular components (CC). The KEGG pathway enrichment analysis indicated that the lipid level and atherosclerosis might influence the treatment of dyslipidemia. Molecular docking showed that quercetin bound well to CCND1, HIF1A, MYC, AKT1, and EGFR genes. These findings were in accord with the prediction obtained through the network pharmacology approach.  This study revealed the primary pharmacological effects and relevant mechanisms of the SZHP in treating dyslipidemia. Our findings may facilitate the development of the SZHP or its active compounds as an alternative therapy for dyslipidemia. Still, more pharmacological experiments are needed for verification. Dyslipidemia is one of the significant risk factors for cardiovascular diseases (CVD) and seriously affects the quality of life of patients. It usually manifests as raised plasma concentrations of total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), a decreased plasma concentration of high-density lipoprotein cholesterol (HDL-C), or a combination of the above features . AccordiThe treatment of dyslipidemia is dominated by statins, used as monotherapy or in combination with ezetimibe, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, and fibrates, which have been demonstrated to be effective in lipid-lowering and cardiovascular risk reduction. Statins act by decreasing the cellular cholesterol content by selectively inhibiting the enzyme HMG-CoA reductase, limiting cholesterol biosynthesis, and lowering hepatic cholesterol concentrations ; thus, iTraditional Chinese medicine (TCM), often used as a complementary and an alternative therapy, has demonstrated beneficial effects among patients with CVD and has been increasingly welcomed worldwide . It has Crataegus pinnatifida Bge. var. major N.E. Br. or Crataegus pinnatifida Bge) and Alisma rhizoma  Juzep or Alisma plantago-aquatica Linn.) form a classic combination of herbal drugs and have been widely used in clinical practice for their significant effects in dyslipidemia. According to the theory of TCM and the Pharmacopoeia of the People's Republic of China, SZ activates blood and removes stasis, regulates qi and promotes blood circulation, removes turbidity, and lowers lipids, whereas ZX promotes urination and drains dampness, discharges heat, resolves turbidity, and lowers lipid [Crataegi Folium  is specifically designed for the identification of the drug-target and drug-disease networks as well as the mechanism of action of TCM [The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform  was used to convert all target proteins into their corresponding gene symbols with the “Homo sapiens” species to standardize gene names and organisms to prevent over annotation of similar proteins.After acquiring the active compounds of the SZHP from the TCMSP, the corresponding targets were obtained. The UniProt database (https://www.genecards.org/) and the OMIM databases  for “Homo sapiens” genes only, with keywords of “dyslipidemia,” “hyperlipidemia,” “hypercholesterolemia,” “hypertriglyceridemia,” “hyperlipoproteinemia,” “hypoalphalipoproteinemia,” and “hypobetalipoproteinemia”; duplicate genes were deleted. All the target genes obtained from the two databases were summarized. Subsequently, active compound targets were mapped to the dyslipidemia-related targets, and therapeutic targets of the SZHP against dyslipidemia were obtained using a Venny 2.1 online tool.We searched GeneCards (https://www.string-db.org/) for PPI network construction. To screen out key target genes with a high degree of connectivity with the SZHP against dyslipidemia, the CytoNCA tool (a plug-in of Cytoscape) was used to analyze the topological properties of the targets. Topological analysis was performed using a network analyzer tool for the estimation of three parameters, i.e., degree centrality (DC), betweenness centrality (BC), and closeness centrality (CC), with a greater node connection degree centrality indicating higher importance of a node in the PPI network. Targets showing above-average values of the three parameters were selected by the value of DC.The common targets of drugs and diseases were entered into the Search Tool of the Retrieval of Interacting Genes database  and BioGrid databases were used. The resultant network contained the subset of proteins that formed physical interactions with at least one other member in the list. If the network contained 3 to 500 proteins, the molecular complex detection (MCODE) algorithm was to be applied to identify densely connected network components.https://geneontology.org/) and KEGG pathway enrichment analysis (https://www.genome.jp/kegg/) were used. By entering a list of target genes and limiting the species to human only, all target genes were corrected to their official gene symbol. GO terms and KEGG pathways with a p value of <0.01 after Bonferroni correction were considered significant; to avoid false positiveness, Benjamini–Hochberg's FDR multiple comparison correction was used, with a minimum count of 3 and an enrichment factor of >1.5 in the KEGG pathway enrichment analysis. Finally, the first 20 entries were selected and plotted into a bar chart for visualization using an online gene function analysis .To further explore the underlying mechanisms of the SZHP for the treatment of dyslipidemia and to elucidate the biological processes of the target proteins in different clusters and their roles in signaling transduction, GO function annotation (https://www.rcsb.org/) and exported in the PDB format. Finally, the water and small molecule ligands were removed using the SYBYL software, and the terminal residue repair, hydrogenation, and charge calculation were performed to complete the molecular docking.Molecular docking is a crucial technology of network pharmacology that combines known proteins with small compounds and validates compound-target interaction . Using tAfter ADME screening on the TCMSP database, 12 candidate active compounds and 186 targets were screened out . The resA total of 2,255 related genes were retrieved from the GeneCards database, and 493 genes were obtained from the OMIM database. After merging and deduplicating the genes, 2,597 genes were obtained. A Venn diagram was constructed by inputting the screened drug targets and disease targets into the Venny software, and a total of 132 shared targets were obtained. Details are presented in The common targets of drugs and diseases were entered into the STRING database to construct a PPI network , which wQ-value, which are presented in Q-values and green color indicating greater enrichment of the GO terms.A total of 856 biological processes (BP), 139 molecular functions (MF), and 89 cellular components (CC) were enriched. Most GO terms of BP were related to response to hormones, cellular response to lipids, cellular response to organic cyclic compounds, response to inorganic substances, positive regulation of cell migration, inflammatory response, response to wounds, response to xenobiotic stimuli, regulation of cell adhesion, response to decreased oxygen levels, etc. The main terms of CC were associated with the binding to DNA-binding transcription factors, nuclear receptor activity, protein kinase binding, cytokine receptor binding, G protein-coupled amine receptor activity, protein homodimerization activity, protein domain-specific binding, serine hydrolase activity, protease binding, protein kinase activity, etc. MF enrichment was mainly involved in membrane raft, transcription regulator complex, side of the membrane, receptor complex, serine-type peptidase complex, extracellular matrix, endoplasmic reticulum matrix, serine protease inhibitor complex, vesicle lumen, axons, etc. The top 10 terms of BP, CC, and MF were ranked based on their The KEGG pathway enrichment showed that a total of 35 signaling pathways were enriched after FDR correction, with the first 20 pathways including lipid and atherosclerosis, pathways in cancers, chemical carcinogenesis-receptor activation, human cytomegalovirus infection, MAPK signaling pathway, chemical carcinogenesis-reactive oxygen species, HIF-1 signaling pathway, relaxin signaling pathway, amoebiasis, and thyroid hormone signaling pathway. After hierarchical clustering of the enrichment results, the network with a similarity of >0.3 was considered a sub-network. The most significant pathway was used as the representative of the enriched networks .p value have been retained as the functional description of the corresponding components, as shown in Key genes were screened out through MCODE analysis, network construction, and MCODE analysis in the total dataset of STRING, OmniPath, InWebIM, and BioGrid for the independent enrichment analysis of gene clusters. The pathway and process enrichment analysis has been independently applied to each MCODE component. The three highest-scoring terms by the G = −2.303 RT × TS, where R is the ideal gas constant of the molecule and T is the thermodynamic temperature of the ideal gas), with a greater total score indicating higher stability of the ligand-receptor binding. It is generally recognized that a total score greater than 4.25 indicates fair binding activity between the active component and the target, a score greater than 5.0 indicates good binding activity, and a score greater than 7.0 indicates excellent binding activity [The SYBYL 2.1.1 software was used to verify the molecular docking of some important active ingredients. Based on the protein binding pocket of the target proteins and ligands, the docking effect was evaluated using the function of the total score (TS), which simulated the binding capacity in the unit of the negative logarithm and converted the binding-free energy formula , carnitine palmitoyl transferase 1α (CPT1α) acyl-coenzyme A dehydrogenase (ACADS), and LPL [In this study, we found that the core active components of the SZHP in the treatment of dyslipidemia included sitosterol, stigmasterol, isorhamnetin, kaempferol, quercetin, Alisol B, Alisol B monoacetate, etc. Stigmasterol and sitosterol belong to phytosterols, which have similar chemical structures with cholesterol and are known to decrease the circulating cholesterol levels by competing with cholesterol for intestinal absorption or regulating proteins involved in cholesterol metabolism ; therefod levels , 38. Kaed levels . Zhang eteatosis . Triterpteatosis . Lipoproteatosis . A study and LPL . 1-Monol and LPL . Taken tα (ESR1) is one of its specific receptors involved in the mediation of the physiological function of estrogen. Polymorphic alterations of ESR1 are associated with conditions such as arterial hypertension, altered serum lipid levels, coronary atherosclerosis, and altered HDL-C levels in menopausal women [The common target PPI network analysis showed that the key targets of the SZHP in the treatment of dyslipidemia included CCND1, CASP3, HIF1A, ESR1, ERBB2, MYC, PTEN, TP53, AKT1, and EGFR. Caspase-3 is a protein in the caspase family that can cause an apoptotic cascade. Studies showed that hyperlipidemia could enhance the peroxidation of lipids and the formation of modified oxidative low-density lipoprotein (ox-LDL), which is mediated by caspase-3; it could also increase NF-kB levels, damage endothelial cells, and promote monocyte adhesion; therefore, it is an important link in the development from hyperlipidemia to AS –47. HIF-al women , 51. Theal women . In addiGO function analysis showed that the therapeutic effect of the SZHP in dyslipidemia is mainly exhibited as a response to hormone, cellular response to lipid, the binding to DNA-binding transcription factors, etc. The KEGG pathway analysis showed that it was mainly concentrated in lipid and atherosclerosis, MAPK signaling pathway, HIF-1 signaling pathway, and relaxin signaling pathway, while the MCODE analysis showed that pathways in cancer, human cytomegalovirus infection, and the AGE-RAGE signaling pathway in diabetic complications comprised the most correlated gene cluster. The most significant pathways also included the lipid and atherosclerosis pathway and the IL-17 signaling pathway.It has been well established that lipid metabolism is associated with atherosclerosis. In atherosclerosis, endothelial dysfunction or apoptosis occurs after chronic injury. The normal physiological function and integrity of the intima are affected, resulting in increased infiltration of lipids into the subintima, which is the initial link to atherosclerosis. Lipids, especially LDL, are oxidized and modified to form ox-LDL after entering the subintima, which leads to endothelial damage, local inflammation in the wall of blood vessels, as well as the formation of foam cells and lipid accumulation, thereby resulting in the aggravation of atherosclerosis . The MAPHence, molecular docking was performed to verify further molecular mechanisms of the SZHP treating dyslipidemia. The results indicated that quercetin had an excellent binding activity with many targets, including CCND1, HIF1A, MYC, AKT1, and EGFR; therefore, it might be a key compound for the effect against dyslipidemia. The above findings were also in line with the results of the network pharmacology analysis. These results might be a significant guidance for further research to determine the molecular targets of the SZHP in the treatment of dyslipidemia as well as for applications of network pharmacology in drug development. It may also provide insights for the subsequent development of novel TCM lipid-lowering drugs with high efficiency, low toxicity, and multiple targets, in order to reduce the mortality of cardiovascular diseases.Despite the strength shown in the present study, some limitations need to be noted. First, the public databases investigated in the study are constantly updated; thus, some other bioactive ingredients and target genes might not have been included in our analysis. Second, the current research on the extraction of the main components of TCM and its drug-like properties is still insufficient, and the important targets have been identified mainly based on computer simulation and verification against existing studies on drugs. Therefore, further studies on the pharmacology of traditional Chinese medicine are still needed.In the present study, a network pharmacology approach in combination with molecular docking was used to explore the targets, mechanism, related signal pathways of the SZHP against dyslipidemia, as well as the binding abilities of herbal ingredients and their targets. The results showed that quercetin, kaempferol, isorhamnetin, Alisol B, etc. were potential active ingredients of the SZHP, and they act on key targets such as CCND1, CASP3, HIF1A, and ESR1 to regulate a variety of biological processes, molecular functions, cellular components, and pathways. This study not only revealed that the SZHP regulates lipid metabolism comprehensively through multiple components, multiple targets, and multiple pathways, but also provided a theoretical basis for the ameliorative effect of the SZHP against dyslipidemia. Hopefully, this study may provide new ideas for the development of the SZHP or its active components as an alternative therapy for dyslipidemia.