PI3k and AKt mRNA were upregulated and the levels of GSK-3β mRNA were downregulated. YXTMD has multicomponent, multitarget, and multipathway effects in the treatment of CHD with BSS, and its mechanism of action may involve activation of the PI3K-AKt signaling pathway, downregulation of GSK-3β, and mediation of in vivo lipid metabolism-based metabolic processes.This study aimed to explore the mechanism of Yangxin Tongmai decoction (YXTMD) in the treatment of coronary heart disease (CHD) with blood stasis syndrome (BSS) using network pharmacology and molecular docking, and to verify these results through clinical trials. The active compounds of YXTMD were identified using the Traditional Chinese Medicine Systems Pharmacology database, and the targets of the active compounds were predicted using the SwissTarget Prediction database. The targets of CHD and BSS were predicted using the GeneCards, OMIM, PharmGKB, TTD, and DrugBank databases. The common targets of “herb-disease-phenotype” were obtained using a Venn diagram, then used Cytoscape software 3.8.2 and its plug-in CytoNCA and STRING database to construct the “herb active compounds-common target” and protein–protein interaction networks. R language software and bioconductor plug-in were used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. AutoDock was used for the molecular docking analysis. Finally, clinical trials were conducted to confirm the results of network pharmacology. Eighty-three active components were obtained, and the core active components were 5,7,4′-trimethoxyflavone, tetramethoxyluteolin, isosinensetin, sinensetin, and 5,7-dihydroxy-2-(3-hydroxy-4-methoxyphenyl)chroman-4-one. A total of 140 common targets were identified, and the core targets were EGFR, VEGFA, AKT1, STAT3, TP53, ERBB2, and PIK3CA. Biological processes identified by the GO analysis primarily involved wound healing, regulation of body fluid levels, and vascular process in circulatory system. The cellular components were primarily located in the membrane raft, membrane microdomain, and plasma membrane raft. The primary molecular functions were activity of transmembrane receptor protein kinase, transmembrane receptor protein tyrosine kinase, and protein tyrosine kinase. KEGG analysis showed that the PI3K-Akt signaling pathway was closely related to the treatment of CHD with BSS by YXTMD. Molecular docking results showed that the core active components had a good binding activity with the core targets. The clinical trial results showed that YXTMD improved the BSS scores and decreased the serum levels of total cholesterol and low-density lipoprotein cholesterol. Moreover, the levels of  This condition triggers stenosis or occlusion of the lumen, resulting in myocardial ischemia and hypoxia as well as clinical symptoms such as chest pain and tightness . The Worblockers . Althougblockers , 6. TherA wide range of Chinese herbal medicines exist with fewer toxic side effects than western medicine , 8. TheyNetwork pharmacology is used to study drugs and their targets and pharmacological activities based on a “drug component–target–disease” interaction network. This network can clarify the mechanism of action of drugs in the treatment of diseases from a holistic perspective and provide new ideas for research on Chinese herbal medicines and their compounds. We therefore aimed to explore the active ingredients, key targets, and specific mechanisms of action of YXTMD in the treatment of CHD with BSS using network pharmacology and molecular docking technology. These results were further verified in clinical trials to provide a theoretical basis for the development and clinical application of the drug. The detailed workflow of the study is shown in https://tcmspw.com/tcmsp.php) was used to identify the chemical components of YXTMD, including renshen, guizhi, danshen, zhishi, and zexie. Oral-bioavailability (OB) [https://pubchem.ncbi.nlm.nih.gov/) database was used to collect and collate candidate compounds, and the data were saved in SDF format as 2D or 3D structures. Swisstarget prediction [https://www.swisstargetprediction.ch/) was used to predict the target of the active compounds by setting the species as “Homo sapiens.” Meanwhile, compounds without chemical structures and targets were eliminated, and the UniProt (https://www.uniprot.org/) database was used to standardize potential targets.The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database  (https:/ity (OB)  ≥30% andity (OB)  ≥0.18 weity (OB)  (https:/ediction  (https:/https://www.genecards.org/), OMIM (https://omim.org/), PharmGkb (https://www.pharmgkb.org/), Therapeutic Target (TTD) (https://db.idrblab.net/ttd/), and DrugBank (https://www.drugbank.ca/) databases were used to collect the targets of the disease and phenotype. We set “coronary heart disease” and “blood stasis syndrome” as the keywords. Related target genes were merged and duplicate values removed to obtain the related targets of CHD with BSS. The common targets of “YXTMD-CHD-BBS” were obtained using VandePeer Labin Bioinformatics Gent (https://bioinformatics.psb.ugent.be/beg), and a Venn diagram was drawn.The GeneCards  database, and the research species was set as “Homo sapiens.” The minimum confidence score was 0.700 [Common targets were imported into the STRING   and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using R software and the bioconductor plug-in with a screen condition of https://www.rcsb.org/) based on the core gene target IDs found in the UniProt database. The PyMOL software was used to remove water molecules, and hydrogen atoms were added to the targets. AutoDock software was used to convert the format of active components and target proteins into the pdbqt format. Finally, molecular docking was performed using AutoDock Vina software and the results were visualized using PyMOL software. A binding energy less than “5 kcal/mol” was used to indicate a good binding interaction between the compound and the target [The 2D structures of the active components were downloaded from the PubChem database and saved in mol2 format using ChemBio3D Ultra software. The pdb formats of the 3D structures of the targets were downloaded from the Protein Data Bank (PDB) ; those with malignant tumors, blood system diseases, connective tissue diseases, mental disorders, tuberculosis, and other infectious diseases; those with serious complications of liver and kidney dysfunction; those with poor compliance and incomplete clinical test data; and those who refused to accept the study and provide informed consent.A total of 26 patients with CHD with BSS admitted to the cardiovascular department of the First Affiliated Hospital of Hunan University of Chinese Medicine between April 2021 and January 2022 were recruited for this study. This study was approved by the Ethics Committee of the First Affiliated Hospital of Hunan University of Chinese Medicine (No. HN-LL-GZR-201820).α (TNF)-α and interleukin-1β (IL)-1β ELISA kits ; ethylenediaminetetraacetic acid (EDTA) ; Tris ; Trizol ; UltraSYBR ; and a blood collection needle and 5 ml blood collection tube .The following instruments and reagents were used: a fluorescence quantitative PCR instrument; fluorescence PCR plate ; desktop freezing centrifuge ; electrophoresis instrument; horizontal agarose electrophoresis tank ; biological sample homogenizer ; enzyme-labeling analyzer ; ultra-microspectrophotometer ; mRNA reverse-transcription kit ; superoxide dismutase (SOD), nitric oxide (NO), and malondialdehyde (MDA) enzyme-linked immunosorbent assay (ELISA) kits ; tumor necrosis factor-Trial groupn = 7) and the treatment group (n = 7). The control group included 5 males and 2 females (average age = 64.14 ± 4.95 years), and the treatment group included 5 males and 2 females (average age = 59.29 ± 5.94 years). No significant differences were observed in the general data between the two groups (P > 0.05).Data from 14 eligible patients were collected according to the criteria for diagnosis, inclusion, and exclusion. Patients were divided into two groups according to the random-number table method: the control group , atorvastatin calcium tablets (20 mg po qd), metoprolol succinate sustained-release tablets (23.75 mg po qd), and benazepril hydrochloride tablets (5 mg po qd). Antiangina drugs were discontinued during the treatment period. If angina pectoris broke out, nitroglycerin tablets were administered sublingually as appropriate.Patients in the treatment group were administered YXTMD combined with routine western medicine. The YXTMD comprised Radix Panacis Quinquefolii (6 g), Ramulus Cinnamomi (8 g), Radix Salviae Miltiorrhizae (10 g), Fructus Aurantii Immaturus (10 g), and Rhizoma Alismatis (10 g). All Sanjiu granule types were produced by China Resources Sanjiu Pharmaceutical Co. Ltd. and one dose was administered per day and taken twice.The treatment period for the two groups was 28 days. Patients were evaluated before and after treatment to determine the curative effects of the drugs according to the “Evaluation Criteria of Angina Pectoris and Electrocardiogram in Coronary Heart Disease”  and “EffSample collectionBefore and after treatment, 12 mL of elbow venous blood was taken from each patient after 8 h of fasting using a red common tube, sodium citrate blood collection tube, and EDTA-K2 anticoagulant blood collection tube. An ice-bag incubator was used to transport the blood samples, of which 4 ml was sent to the biochemical laboratory of the First Affiliated Hospital of Hunan University of Chinese Medicine within 2 h to determine the level of blood lipids. The remaining 8 mL was sent to the Intermediate Diagnosis Laboratory of Hunan University of Chinese Medicine within 2 h; 4 mL was poured into a cryopreservation tube, and the remaining 4 mL was centrifuged. The serum was poured into a cryopreservation tube, and all samples were stored at −80°C.ELISAα, and IL-1β.Blood samples were strictly analyzed according to the manufacturer's instructions. The curve formula was calculated using the standard concentration and absorbance  of the standard well. The measured OD values were substituted into the corresponding curve formulas to calculate the concentration of MDA, SOD, NO, TNF-Real-time PCRPI3k, AKt, NF-κB, eNOS, and GSK-3β mRNA. The steps of the reaction included an initial denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 95°C for 15 s and annealing at 60°C for 30 s. GAPDH served as an internal control, and gene expression was analyzed by the 2−ΔΔCt method. Primer sequences were designed using Primer 5 and synthesized by Shanghai Bioengineering . For normally distributed data, the t-test was used when the variance was homogeneous and the Wilcoxon test was used when the variance was not homogeneous. Count data are expressed as frequency , and comparisons between two groups were analyzed using the χ2 test or Fisher's exact test was appropriate. Statistical significance was set at P < 0.05.SPSS26.0 software was used for statistical analysis. Data are expressed as the mean ± standard deviation , vascular endothelial growth factor (VEGF) A, AKT1, STAT3, TP53, ERBB2, PIK3CA, HSP90AA1, mTOR, SRC, CASP3, matrix metalloproteinase 9 (MMP9), IL2, NRAS, PTPN11, TNF, PTGS2, and FGF2. These findings indicate that these may be core genes targeted by YXTMD in the treatment of CHD with BSS.Common targets were imported into the STRING11.5 database to construct the PPI network diagram; isolated nodes were removed . The netIn total, 2710 were enriched in the GO analysis, including biological processes (BP), cell composition (CC), and molecular function (MF). The top ten items were selected for visualization . BP was A total of 158 signaling pathways were identified by the KEGG enrichment analysis. The top 30 items were selected for visualization , which pAkt1 plays an important role in vascular remodeling, formation, vasodilation, and wound healing by regulating downstream signaling molecules . In addiThe results show that the binding energies were less than −5 kcal/mol, indicating that 5,7,4′-trimethylapigenin, tetramethoxyluteolin, isosinensetin, sinensetin, and 5,7-dihydroxy-2-(3-hydroxy-4-methoxyphenyl)chroman-4-one bound strongly to Akt1 and VEGFA .P > 0.05) , but the difference was not significant ( > 0.05) . The smaP < 0.05). The BSS score also decreased in the control group, but the difference was not significant (P > 0.05). The BSS scores of the treatment group showed a more significant decrease compared with those of the control group after treatment (P < 0.05)  .P < 0.05). Total cholesterol (TC), triglyceride (TG), and low-density lipoprotein (LDL) cholesterol (LDL-C) levels were lower in the treatment group, but the difference was not significant (P > 0.05); TC and LDL-C levels were higher in the control group (P < 0.05). The TC and LDL-C levels of the treatment group showed a greater decrease than those of the after treatment (P < 0.05)  level of the two groups increased after treatment ( < 0.05) .P > 0.05). The serum levels of IL-1β and TNF-α were lower in the treatment group, but the difference was not significant (P > 0.05). The serum levels of IL-1β were significantly higher in the control group (P < 0.05), and although the serum levels of TNF-α were also higher, the difference was not significant (P > 0.05). Compared with the control group after treatment, no statistical difference was observed in the treatment group . The level of GSK-3β mRNA was significantly lower in the treatment group (P < 0.05), and although it was lower in the control group, the difference was not significant (P > 0.05). Compared with the control group after treatment, the levels of PI3k and AKt mRNA increased to a greater extent in the treatment group, and the level of GSK-3β mRNA decreased significantly (P < 0.05)  . AmplifiThe pathogenesis of CHD is complex and is primarily related to lipid metabolism disorders, vascular endothelial injury, platelet aggregation, and thrombosis . Diseaseβ, IL-6, and TNF-α [The results of our study showed that the core active components of YXTMD in the treatment of CHD with BSS were 5,7,4′-trimethylapigenin, tetramethoxyluteolin, isosinensetin, sinensetin, 5,7-dihydroxy-2-(3-hydroxy-4-methoxyphenyl)chroman-4-one, danshenol B, danshenol A, eriodyctiol, luteolin, naringenin, and kaempferol. The first 10 components belonged to danshen and zhishi. Danshen  activates the blood and resolves stasis, and zhishi (Fructus Aurantii Immaturus) regulates qi and dissipates phlegm, consistent with the principle of treating BSS. Most of the active ingredients were flavonoids, which have the effects of antioxidation, anti-inflammation, vasodilation, inhibition of platelet aggregation, and regulation of blood lipid levels, thus exerting beneficial therapeutic effects on cardiovascular and cerebrovascular diseases –41. Modend TNF-α . In addind TNF-α . Danshennd TNF-α . Luteolind TNF-α . It can nd TNF-α . Naringend TNF-α  and can nd TNF-α . Kaempfend TNF-α . This suIn the present study, we identified 18 key targets of YXTMD for the treatment of CHD with BSS: EGFR, VEGFA, AKT1, STAT3, TP53, ERBB2, PIK3CA, HSP90AA1, MTOR, SRC, CASP3, MMP9, IL2, NRAS, PTPN11, TNF, PTGS2, and FGF2. Previous studies have shown that VEGFA, EGFR, and FGF2 are related to vascular endothelial regeneration, and that vascular endothelial cell damage is a significant feature of atherosclerosis . VEGF caκB, and GSK-3β. Activated Akt can phosphorylate eNOS, thereby promoting the production of endogenous NO, accelerating the regeneration of vascular endothelial cells, and dilating blood vessels. NF-κB promotes cell proliferation, inhibits apoptosis, and is an important inflammatory activator [β is a multifunctional serine/threonine protein kinase that negatively regulates itself by activating the PI3K-Akt pathway, thereby mediating cell metabolism, proliferation, differentiation, apoptosis, and other biological processes [In the present study, GO functional and KEGG enrichment analyses revealed that YXTMD primarily targets the PI3K-Akt signaling pathway, proteoglycan in cancer, Rap1 signaling pathway, MAPK signaling pathway, microRNAs in cancer, and lipids and atherosclerosis in the treatment of CHD with BSS. The primary biological processes involved included wound healing, regulation of body fluid levels, and vascular progress in the circulatory system. The PI3K-AKt pathway plays an important role in growth in vivo, and can activate antiapoptotic mechanisms, glucose metabolism, protein synthesis, and other processes to promote cell proliferation . It alsoctivator . GSK-3β rocesses . Accordiβ and TNF-α), oxidative stress indicators (MDA and SOD), and the PI3K-AKt pathway and its downstream proteins  in patients with CHD with BSS. Results showed that after treatment, the clinical curative effect of the treatment group was better than that of the control group. YXTMD improved the curative effect scores of patients with BSS and reduced the serum TC and LDL-C levels. PCR results showed that, compared with the control group, the serum levels of PI3k and AKt mRNA significantly increased, and the levels of GSK-3β mRNA significantly decreased in the treatment group; however, the levels of NF-κB and eNOS mRNA did not significantly change. ELISA results showed no significant changes in serum MDA, SOD, NO, and TNF-α levels in the two groups before and after treatment, and the serum IL-1β level in the control group was higher than before treatment. The above results demonstrate that YXTMD was clinically effective in treating CHD with BSS. It can improve the efficacy score of BSS and reduce blood lipid levels. The specific mechanism may be related to the activation of the PI3K/Akt signaling pathway, downregulation of GSK-3β, and regulation of lipid metabolism.Based on previous research from our group and the pathogenesis of CHD with BSS, we further verified the accuracy of the network pharmacology results and more intuitively reflected the clinical efficacy and specific molecular mechanism of YXTMD in the treatment of CHD with BSS through a clinical trial. In the trial, we determined the effects of the clinical efficacy, blood lipid level, endothelial injury marker index (NO), inflammatory factor index  This trial was based on a heterogeneous human population, which involves many uncontrollable factors. (2) The difficulty in collecting clinical samples and the problem of patient compliance resulted in a small sample size. (3) The subjects of this study were all patients with BSS. Modern studies have shown that increased blood lipids and viscosity are the biochemical basis for phlegm and blood stasis. This occurs when a large amount of lipids condense in the veins to form phlegm turbidity, and the phlegm is stuck in the veins for a prolonged period and condenses into blocks, leading to endogenous blood stasis. Therefore, BSS formation was closely related to blood lipid levels. These factors affected the trial results to some extent, so large-scale clinical studies or in-depth studies at the animal and cellular levels are needed at a later stage to explore the specific mechanism by which YXTMD treats CHD with BSS.β, and mediation of lipid-metabolism-based metabolic processes. These results provide a theoretical basis for the clinical application of YXTMD and highlight directions for follow-up studies on the development of anti-CHD drugs.Our study explored the mechanism of action of YXTMD in the treatment of CHD with BBS through a combination of network pharmacology and molecular docking. The results demonstrated that 5,7,4′-trimethoxyflavone, tetramethoxyluteolin, isosinensetin, sinensetin, and 5,7-dihydroxy-2-(3-hydroxy-4-methoxyphenyl)chroman-4-one may be the main active components of YXTMD. These components act on key targets, such as EGFR, VEGFA, AKT1, STAT3, TP53, ERBB2, and PIK3CA, in the treatment of CHD with BBS. YXTMD had the characteristics of being multicomponent, multitarget, and multipathway in treating CHD with BBS. Clinical trial results showed that the mechanism of action of YXTMD in treating CHD with BBS may be related to the activation of the PI3K-AKt signaling pathway, downregulation of GSK-3


Dracocephalum moldavica L. (TFDM) has many pharmacological and biological roles, such as cardioprotective, neuroprotective, anti-atherogenic, antihypertensive, anti-diabetic, anti-inflammatory, antioxidant, etc. However, its effect on HF and its molecular mechanism are still unclear. In this study, we used systems pharmacology and an animal model of HF to investigate the cardioprotective effect of TFDM and its molecular mechanism. Eleven compounds in TFDM were obtained from the literature, and 114 overlapping genes related to TFDM and HF were collected from several databases. A PPI network and C-T network were established, and GO enrichment analysis and KEGG pathway analysis were performed. The top targets from the PPI network and C-T network were validated using molecular docking. The pharmacological activity was investigated in an HFpEF (heart failure with preserved ejection fraction) mouse model. This study shows that TFDM has a protective effect on HFpEF, and its protective mechanism may be related to the regulation of proinflammatory cytokines, apoptosis-related genes, fibrosis-related genes, etc. Collectively, this study offers new insights for researchers to understand the protective effect and mechanism of TFDM against HFpEF using a network pharmacology method and a murine model of HFpEF, which suggest that TFDM is a promising therapy for HFpEF in the clinic.Heart failure (HF) is a clinical syndrome of cardiac insufficiency caused by abnormalities in cardiac structure and function that arise for various reasons, and it is the final stage of most cardiovascular diseases’ progression. Total flavonoid extract from  Heart failure (HF) is a complex clinical syndrome caused by structural and/or functional cardiac abnormalities that result in the impairment of ventricular filling and/or ejection, ultimately causing the inability of the heart to supply the peripheral tissues with the required amount of blood and oxygen to satisfy their metabolic demands. Across 60 included studies, 1.5 million people suffered from heart failure . ApproxiDracocephalum moldavica L. (D. moldavica L.) is an annual plant belonging to the family Labiatae [D. moldavica L. (TFDM) has many pharmacological and biological roles, such as cardioprotective, neuroprotective, anti-atherogenic, antihypertensive, anti-diabetic, anti-inflammatory, antioxidant, etc. [Traditional Chinese medicine (TCM) has attracted worldwide attention in recent decades for its precise efficacy, relatively low toxicity, and low cost . TCM hasLabiatae . It is wLabiatae . Total fnt, etc. ,14. The nt, etc. . CurrentIn this study, we used systems pharmacology to estimate the target compounds of TFDM and targets for heart failure by using several databases. We then constructed PPI and C-T networks and conducted Gene Ontology, KEGG pathway enrichment, and molecular docking analyses for the validation of the top targets. Finally, we used a novel two-hit murine model  of HFpEFThrough the PubMed, Wanfang, and CNKI databases, 34 kinds of flavonoids were collected from the literature, among which 11 kinds of flavonoids had related information in PubChem, TCMSP, CTD, and SwissTarget Prediction databases: apigenin, acacetin, luteolin, salvigenin, chryseriol, diosmetin, isorhamnetin, kaempferol, quercetin, tilianin, and astragalin. To identify the pharmacokinetic properties of each compound, two classical ADME parameters, OB and DL, were obtained from the TCMSP database. Among them, eight compounds had an OB greater than 30.0%; only apigenin (23.06%), tilianin (19.66%), and astragalin (14.03%) had an OB less than 30.0%. The DL of all flavonoids in TFDM was greater than 0.18 . The cheTo search for the targets of the 11 flavonoids, TCMSP, CTD, and SwissTargetPrediction databases were used, and 593 targets were identified. A total of 450 known therapeutic targets for heart failure were collected from the TTD, Gene Cards, and DisGeNET databases. The 593 compound targets and 450 disease targets have 114 overlaps. This means that these 114 genes may be key targets for the treatment of heart failure with TFDM. To further clarify the correlations among TFDM targets associated with HF targets, a “target-target network” was built based on the STRING results of the 114 overlapping genes. Nodes and edges represent targets and associations between targets, respectively, in the PPI network. The size and color of nodes indicate the magnitude of the degree. A larger-sized node means a larger degree. A total of 106 nodes and 700 edges were involved in the PPI network, as shown in To uncover the interactions between constituents and potential targets for treating HF, a C-T network based on 11 compounds and 114 potential targets was constructed. The network is composed of 125 nodes and 339 edges, in which green diamonds represent compounds, red ellipses represent targets whose degree is greater than or equal to 3, and blue rectangles represent targets whose degree is less than or equal to 2. An edge represents the interaction between the compound and the target . The higY-axis represents the GO term. The X-axis indicates -Log10 . Black nodes represent the number of genes enriched for the term. We used the first 10 terms from small to large according to the p-value for a brief demonstration. The results indicate that numerous biological processes are involved in the treatment of heart failure, including response to hypoxia, cytokine-mediated signaling pathway, inflammatory response, negative regulation of cell proliferation, positive regulation of nitric oxide biosynthetic process, regulation of blood pressure, positive regulation of MAPK cascade, and others.To verify whether the 114 genes are related to heart failure, we conducted GO enrichment analysis to clarify the relevant biological processes, cellular components, and molecular functions, as shown in Y-axis represents KEGG pathways. The X-axis indicates the gene ratio enriched in the pathway. The redder the color, the smaller the value of p, which also means more credibility and more importance. In this study, we sorted the first 10 pathways from small to large according to the p-value for a brief demonstration. Among these pathways, the AGE-RAGE signaling pathway in diabetic complications, lipid and atherosclerosis, IL-17 signaling pathway, relaxin signaling pathway, TNF signaling pathway, HIF-1 signaling pathway, NF-kappa B signaling pathway, FoxO signaling pathway, cAMP signaling pathway are considered the top priority.KEGG pathway enrichment analysis was performed by using the DAVID database, as shown in Eleven compounds from TFDM were analyzed by molecular docking with the top targets: TNF, IL6, IL-1β, NOS2, and PTGS2 in the PPI network and C-T network, respectively. The molecular docking results showed that the binding energies (Vina scores) of all of the compounds with the top five targets were lower than −7.1 . This meCompared with the normal control group, the model group showed significantly impaired glucose handling. After intraperitoneal injection of 2 g/kg glucose after 6 h fasting, the blood glucose of model group mice increased significantly after 15, 30, 45, and 60 min, while treatment with TFDM significantly reduced impaired glucose handling A,B. LongTen weeks of exposure to HFD plus L-NAME triggered left ventricle diastolic dysfunction but did not affect systolic function C. The E/H&E and Masson staining results revealed that, compared with the normal control group, the myocardium of the model group showed obvious hypertrophy and fibrosis A,B. The D. moldavica L. is one kind of traditional medicine, and TFDM is the total flavonoids extracted from D. moldavica L. In this study, we used several databases to collect 11 known monomeric compounds identified in TFDM, namely, apigenin, acacetin, luteolin, salvigenin, chryseriol, diosmetin, isorhamnetin, kaempferol, quercetin, tilianin, and astragalin. Our study aimed to evaluate the effects and mechanisms of the constituents of TFDM for the treatment of HFpEF. According to the target distribution of constituents in TFDM related to HF, the inflammatory reaction is the main target that TFDM affects, and TNF, IL6, and IL-1β are the major targets of the constituents of TFDM linked to the potential treatment of HF. The results of KEGG pathway enrichment analysis also demonstrate that the therapeutic effect of TFDM on HF may be achieved by inhibiting the IL-17 signaling pathway, TNF signaling pathway, NF-kappa B signaling pathway, etc. Inflammation is accepted as an important pathophysiological factor in HF. Specifically, inflammation has been linked to disease development, progression, and complications [HF is the most rapidly growing cardiovascular health burden worldwide, and approximately half of newly diagnosed HF patients are HFpEF. Furthermore, mortality and morbidity in HFpEF have continuously increased . As the ications . Althougications . TNF-α, ications . TFDM shications . Tilianiications . Apigeniications . Kaempfeications . Luteoliications , cobalt-ications , and LPSications  inflammaications . These sPTGS2, namely, COX-2, and NOS2, namely, iNOS, were also among the main predicted targets in our study, and they play an important role in HF. Clinical data suggest that a systemic imbalance in NO levels and inflammation are crucial in the development of HFpEF . In our Cardiomyocyte death is a common characteristic of heart injury. Apoptosis is the principal cellular pathway that results in cardiomyocyte death. In our study, the PPI and C-T network analysis showed that PIK3CG, namely, PI3K, and AKT are also among the main predicted targets through which TFDM exerts its protective effects on HF. Consistent with our research, other studies also showed that TFDM  and tiliNetwork pharmacology is a useful tool and strategy to predict potential therapeutic mechanisms and can effectively provide research directions . With thIn our experimental study, the echocardiogram results showed that TFDM significantly reduced the E/E’ ratio. In diastolic dysfunction, the E/E’ ratio is markedly increased, and it is one of the criteria used in the differential diagnosis . The sevMolecular docking is an established in silico structure-based method widely used in drug discovery. Docking enables the identification of novel compounds of therapeutic interest by predicting ligand–target interactions at a molecular level . AutoDocIn summary, our research systematically investigates TFDM from a whole action mechanism perspective in the treatment of HF, specifically in the treatment of HFpEF, and provides a basis for exploring multi-compound synergies in subsequent research. TFDM can realize the protective effect of HF through multiple targets, multiple biological processes, and multiple signaling pathways. A total of 11 compounds in TFDM were obtained from the literature, and 114 overlapping genes between TFDM and HF were screened using systems pharmacology combined with target predictions. The PPI network, C-T network, GO enrichment analysis, and KEGG pathway analysis suggested that the pharmacological mechanism of TFDM for the treatment of HF may be related to its involvement in the regulation of proinflammatory cytokines, apoptosis-related genes, fibrosis-related genes, etc. At the end of our research, the protective effect of TFDM was confirmed in an HFpEF mouse model. In general, this study provides a comprehensive understanding of the mechanism of TFDM for the treatment of HFpEF.https://old.tcmsp-e.com/tcmsp.php (accessed on 7 November 2021)). OB represents the percentage of an orally administered dose of unchanged drug that reaches the systemic circulation. High oral bioavailability is often a key indicator to determine the drug-like properties of bioactive molecules as therapeutic agents [All compounds contained in TFDM were identified from the literature by using the PubMed database, Wanfang database, and China National Knowledge Infrastructure (CNKI) database, and then the pharmacokinetic properties of each compound, such as oral bioavailability (OB) and drug-likeness (DL), were obtained from the Traditional Chinese Medicine Systems Pharmacology database ), and SwissTargetPrediction (http://swisstargetprediction.ch (accessed on 8 November 2021)) databases, and the target name was then transformed to the gene symbol using the UniProt knowledge database. To collect the disease targets for heart failure, we searched with the keywords “heart failure” or “chronic heart failure” in TTD (http://db.idrblab.net/ttd/ (accessed on 8 November 2021)), Gene Cards (https://www.genecards.org/ (accessed on 8 November 2021)), and DisGeNET (https://www.disgenet.org/home/ (accessed on 8 November 2021)) databases, and duplicated disease targets were removed. Finally, Draw Venn Diagram was used to analyze the target intersection between heart failure and TFDM.Targets of the compounds in TFDM were retrieved from TCMSP, CTD (https://string-db.org/ (accessed on 9 November 2021)) to perform PPI analysis. The organism was specified as Homo sapiens, and proteins corresponding to genes with high confidence (minimum required interaction score ≥ 0.7) were selected. The results were saved in TSV file format and imported into Cytoscape software  to visualize the PPI network. To evaluate the therapeutic mechanism of TFDM in treating HF, the compound–target (C-T) network was constructed by using Cytoscape 3.7.1 software.The target intersection between HF and TFDM was imported into the STRING database (https://david.ncifcrf.gov/ (accessed on 10 November 2021)) database.To explore the possible biological processes (BPs), cellular components (CCs), molecular functions (MFs), and biological pathways of common compound–disease targets, Gene Ontology and KEGG pathway enrichment analyses were performed on the DAVID (https://www.rcsb.org/ (accessed on 13 November 2021)). The PubChem database (https://pubchem.ncbi.nlm.nih.gov/ (accessed on 13 November 2021)) was used to download the two-dimensional (2D) structures of the eleven compounds. AutoDock Tools software  was used to remove water molecules, isolate proteins, add nonpolar hydrogen molecules, and calculate Gasteiger charges for the structures, which were saved as a PDBQT file. The active site of molecular docking was determined by the ligand coordinates in the target protein complex.The three-dimensional (3D) structures of the five targets were downloaded from the RCSB PDB database (n = 10/group), were purchased from Vital River Laboratories, Beijing, China. Animal care and handling protocols were approved by the Animal Ethics Committee of the Chinese Academy of Medical Science and Peking Union Medical College.TFDM was provided by Xinjiang Institute of Materia Medica . HFD  and L-NAME (Sigma Aldrich) were used for the model. Eight–ten-week-old male mice (n = 10 per group): the control group, model group, and TFDM group. Mice in the model group and TFDM group were fed a high-fat diet and water, and L-NAME (0.5 g/L) was supplied in the drinking water for ten weeks after adjusting the pH to 7.4. Mice in the control group were fed a CHOW diet and drinking water without L-NAME. At Week 6, TFDM  was orally administered every day for 28 days. The control and model groups received the same volume of saline.Mice with similar baseline characteristics were randomly divided in to 3 groups  using a 30 MHz image transducer. Mice were anesthetized with oxygen and isoflurane (1–2%), and systolic function of the left ventricle was obtained from short-axis M-mode scans. Diastolic function was measured using pulsed-wave and tissue Doppler imaging at the level of the mitral valve.Elevated blood pressure is a major risk factor for the development of symptomatic HF . SystoliAn intraperitoneal glucose tolerance test (IPGTT) was performed by injecting glucose  after 6-hour fasting. Tail blood glucose levels were measured with a glucometer before (0 min) and 15, 30, 45, 60, and 120 min after glucose administration. To determine glucose tolerance, we calculated the area under the curve (AUC).Exercise intolerance is common in HF. In the clinic, the 6 min walk test is an alternative way to measure exercise capacity. The distance walked in the 6 min walk test has been associated with prognosis in HF ,52. In tHearts were fixed in 4% paraformaldehyde and embedded in paraffin. Crosswise 5 μm-thick heart sections were cut and stained with hematoxylin and eosin (H&E)  for routine histological analysis. Masson’s Trichrome (Servicebio) was to evaluate cardiac fibrosis following the manufacturer’s instructions. The slides were then mounted with coverslips using neutral gum . The images were captured using high-volume, digital whole-slide scanning . Three samples in each experimental group and three sections from each individual sample were analyzed by Image J software.p < 0.05 were considered statistically significant.The experimental data are presented as the mean ± SEM (SEM), and statistical analysis was performed using Graph Pad Prism 5. One-way analysis of variance (ANOVA) was used to evaluate differences between groups, followed by Tukey’s post hoc test. Results with


Objective: Iguratimod (IGU) is a novel small disease-modifying compound widely used in Asia for the treatment of rheumatic diseases. IGU is a methane sulfonanilide. We applied network pharmacology to investigate the pharmacological mechanisms of IGU act on SLE.Methods: We used PharmMapper, UniProt, and OMIM databases to screen the potential targets of IGU, and the SLE-related disease targets were predicted. Hub target genes among the intersections of the potential targets (IGU) and related genes (SLE) were validated using the PPI network generated by the String database. GO and KEGG enrichment analyses were carried out using the David online platform. Finally, the molecular docking of hub targets and their corresponding compounds were completed through AutoDock Vina and PyMOL software for visualization.Result: A total of 292 potential targets of IGU, 6501 related disease targets of SLE, and 114 cross targets were screened from the aforementioned database. Network topology analysis identified 10 hub targets, such as CASP3, AKT1, EGFR, MMP9, and IGF1. GO enrichment analysis mainly focuses on the negative regulation of the apoptotic process and signal transduction. KEGG enrichment analysis illustrated that the PI3K-AKT signaling pathway, MAPK signaling pathway, and FoxO signaling pathway might play a significant role in the pharmacological mechanisms of IGU act on SLE. Molecular docking confirmed that the IGU ligand had strong binding activity to the hub targets.Conclusion: This study based on network pharmacology and molecular docking validation preliminarily revealed the protein targets affected by IGU acting on SLE through, and explored potential therapeutic mechanism role of IGU in SLE treatment by multi pathways. Systemic lupus erythematosus (SLE) is a significant heterogeneous autoimmune disease characterized by the loss of immune tolerance and defective immune regulation . The etiDespite research studies in therapeutic approaches over the past few years, SLE still leads to relatively high morbidity and mortality increases. The long-term use of immunosuppressants for SLE might lead to serious adverse events, such as infections and toxicity. SLE still lacks safe and effective treatment .In recent years, a new immunomodulatory drug, iguratimod, emerged as a potential candidate for the treatment of autoimmune diseases. It has been approved for the treatment of rheumatoid arthritis (RA) in Northeast Asia .IGU) is a novel immunomodulatory anti-rheumatic drug that is currently only approved in Japan and China -17, IL-6, and NF- κB activated , meaning that it is recalcitrant to previous treatment with at least two immunosuppressive agents  in a dose-dependent manner , and potential action targets of IGU  were predicted by the PharmMapper database (http://www.lilab-ecust.cn/pharmmapper/). The PharmMapper server provided the molecular structures to obtain potential targets, and build a complete drug target database (21) predicts targets from a combination of 2D and 3D structural similarities of known small molecule substances. The way PharmMapper identifies potential drug targets is mainly by mapping the reverse pharmacophore.The PubChem database was used to obtain the molecular structure of database . The SwiIGU ligand  target screening.Then, the simultaneous selection of a Human Protein Target database is generated by optimizing compound structures for multiple structure analysis, in which parameter matching shub (fit shub>2) can be used as an adjudication criterion for the outcome of the https://www.uniprot.org/).The collected protein or gene information was normalized encoded in the UniProt database (https://omim.org/ ), DisGeNet (https://www.disgenet.org/), and the GeneCards databases  to obtain the overlapping targets.We used “Systemic lupus erythematosus” as a keyword to collect SLE-related disease target genes in the OMIM (IGU and SLE were uploaded into the database of String (https://string-db.org), and the protein–protein interaction (PPI) network was constructed. The Cytoscape software (version 3.6.1) network  was conducted to make visualization of the results. The top 10 disease–drug targets were finally obtained from the PPI network using Cytoscape plugin cytoHubba by the Maximal Clique Centrality (MCC) method (The intersection targets of ) method .https://david.ncifcrf.gov/) was used to screen the differentially expressed gene (DEG) analysis. The fold change as well as the p-value was calculated with a t-test. The threshold set for DEGs was a fold change ≥ 2.0 and a p-value ≤ 0.05. GO and KEGG analyses were performed by selecting GO biological processes, GO molecular functions, GO cellular components, and KEGG pathway. GO and KEGG pathway enrichment results were plotted as bar graphs and bubble charts. Analyses of GO and KEGG were conducted.David . The molecular structure file of IGU (PubChem CID: 124246) was downloaded using the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Downloaded target proteins were subjected to manipulation such as removing water molecules and removing protomers using Pymol software (2.3.0 version). QM calculations on the optimal conformation of the IGU ligand were executed in the ORCA software (5.03 version) package as implemented.The molecular structure files of four target proteins, namely, AKT1 (PDB ID: 3o96), CASP3 (PDB ID: 1nmx), EGFR (PDB ID: 1ivo), and IGF1 (PDB ID: 1imx) with inhibitors were searched and downloaded by utilizing the PDB database (IGU and that of SLE (IGU ligand with the target proteins.AutoDock Vina (v.1.2.0 version) was used to verify the molecular docking between selected hub targets of t of SLE . PyMOL s−1 implied that the compound could bind and interact with the hub target, while the binding energy <−5 kcal mol−1 indicated as a strong binding force. The docking scope is set within the active pocket where independent protomers of the target protein reside. Molecular docking binding energy was calculated by running AutoDockTools software (1.5.6 version) after grid and dock parameters were ready. The binding energy ≤0 kcal molIGU were predicted by the PharmMapper database. The 2D and 3D chemical structures of IGU are presented in IGU are transferase (26%), hydrolase (25%), and oxidoreductaselyase (8%), as presented in Potential targets for IGU-related target protein genes into the online Venn platform to obtain the intersection genes, and a total of 114 intersection targets were obtained, as shown in A total of 54, 1883, and 6019 disease targets were obtained from three databases’ collection, and 6501 SLE-related targets were obtained after cleaning of duplicates. We imported SLE-related targets and p < 0.05). The PPI network consisted of 114 nodes and 763 edges  network of the 114 intersection targets was then performed to predict the functionality of interacting proteins and genes. Cluster analysis of the PPI network of genes significantly altered the expression , biological processes (BPs), and cellular components (CCs). The result of GO showed that the potential targets of  binding  while th binding .IGU-PAC potential target using Cystoscape software of the network diagram, and the ingredient potential target network contains 115 nodes (including 114 target genes and 1 drug) and 114 edges , thr-82 (3.28 Å), and leu-213 (3.04 Å) in the AKT1 target protein. It forms two carbon–hydrogen bond interactions (carbon–hydrogen bond) with ser-205 (2.46 Å) and thr-211 (2.62 Å). It forms five π–π interactions with trp-80 . Likewise, it also forms two π with trp-80 (2.55 Å) and val-270 (2.55 Å)-σ effect. The IGU small molecule forms one π–ion bond interaction with asp-292 (4.24 Å). The inhibitor small molecule forms one conventional hydrogen bond interaction with amino acid residue ser-205 (2.89 Å) in the AKT1 target protein. It forms six π–π interactions with trp-80 , and two π–ion bond interactions with arg-273 (4.20 Å) and asp-292 (4.75 Å), respectively. It forms two π with ile-84 (4.42 Å and 4.42 Å)-σ effect and two π–alkyl interactions with val-270 (5.20 Å and 5.26 Å), respectively. The alignments found that both IGU and the inhibitor bound to the same amino acid residues in the docking results for AKT1 target proteins, such as thr-80, ser-205, val-270, and asp-292.n bond. The binding sites of IGU to the four target proteins were nearly the same as that of the inhibitor, and the binding energy of IGU to the four target proteins was all excellent, and the binding force was abundant. Thus, IGU used in this experiment is likely to exert inhibitory effects through docking with four target proteins.As shown in Systemic lupus erythematosus (SLE) is an autoimmune disease, with systemic clinical manifestations including the skin rash, brain, kidneys, heart, and lungs . AbnormaIGU) has been found to be effective in the treatment of SLE  or other cell signaling pathways , as an emerging drug research strategy, has gained wide applications in drug research, enabling the description of relationships among biological systems, drugs, and diseases from a network perspective, such as SLE . The aimIGU-targeted SLE-related gene network consisting of 114 targets. GO and KEGG analyses showed that IGU could regulate immune, apoptosis, and autophagy signaling pathways. We further obtained 10 hub targets from 114 cross targets by constructing the PPI network and compound–target–disease network analysis. We selected four targets closely related to SLE together with a higher node degree in the network , and performed molecular docking to verify the interaction between IGU and the four targets. Our findings demonstrated the effectiveness of IGU in SLE treatment from a bioinformatics perspective and provide possible pharmacological multi-targets and multi-pathway mechanisms of IGU. The results may also facilitate targeted drug design and basic research for SLE in the future.In this study, we constructed an IGU. These target proteins are involved in oxidative stress, inflammation, angiogenesis, and immunomodulator. Based on the previous reports, AKT1 serine/threoe kinase is a key autophagy target of the PI3K signaling pathway, and plays a role in the differentiation of peripheral B cells and in T-cell homeostasis in SLE patients  itself has tyrosine kinase activity and, once combined with EGF, can initiate related genes in the nucleus, thereby promoting cell division and proliferation . A singlwith SLE . Activatwith SLE .Insulin-like growth factor 1 (IGF-1) is a hormone, which stimulates the growth, differentiation, and metabolism of various cell types, and induces angiogenesis . IGF-1 sIGU has an impact on several key pathways that are important in the treatment of SLE. AKT1, CASP3, EGFR, and IGF1 may be targets for the action of IGU in the treatment of SLE.Following GO and KEGG enrichment analyses, it was hypothesized that IGU in SLE treatment. P38 MAP kinase (MAPK) participates in a signaling cascade controlling cellular responses to cytokines and stress. The MAPK signal pathway is known to contribute to the inhibition of nuclear factor-κB (NF-κB), which may be a potential intracellular mechanism leading to excessive lymphocyte activity in SLE  were expressed in several types of cutaneous damages associated with SLE . The phaIGU ligand and the corresponding active targets. We also conducted the docking control of molecular docking between the target protein and the inhibitor of the reference compound. We performed the docking control of the target protein with the inhibitor of the reference compound for further validation. Our study provides a reference for the molecular docking results, space and energy matching correlation between molecules, the chemical compound of IGU.To further verify the mechanism of action, we used molecular docking to analyze the binding energy of IGU had strong binding activity against four hub targets with all binding affinities below—5 kcal/mol, and the binding conformation was steady. For example, CASP3 is a representative apoptotic cytokine and has a good binding affinity with the IGU ligand, which also confirms that IGU may play an anti-apoptotic role in SLE.Meanwhile, molecular docking showed that IGU with hub targets act on SLE may be involved in the immune cell regulation process, apoptosis, regulating immune cell function, angiogenesis, and endoplasmic reticulum stress through the regulation of MARK, PI3K/AKT, FoxO, and chemokine signaling pathways.In summary, the inhibitory effect of IGU targeting these signaling pathways may help to attenuate disease processes such as inflammation and immune disorders in SLE.These studies are consistent with the findings of the present study, and to some extent demonstrate the reliability of the bioinformatic research approach, and the study of IGU binding to target proteins, and molecular dynamics (MD) simulations, mass spectrometry (MS) analysis, and high-throughput nanoparticle assays (HMSA) are needed. Given the objective reasons such as the funding support of this study and the limitation of laboratory conditions, this aspect could be a fun and good warm-up for the latter part of further works in vitro to validate our findings, including MS and high-performance liquid chromatography (HPLC). Also, it is necessary to carry out further studies with the multi center.There are a few limitations in this study which are as follows: it is essential to evaluate the effect of IGU on SLE may be exerted through the hub targets described earlier and the related protein, especially in NF-κB, MAPK, PI3K/AKT, inhibition of abnormal apoptosis, and other pathways. These findings expand our understanding of the mechanism of IGU in the treatment of SLE. IGU might act as a multicomponent, multi-target, and multi-pathway therapeutic agent for SLE.To sum up, we speculate that the mechanism of action of


Shaogan Fuzi Decoction (SGFD), one of the classical prescriptions of Chinese Medicine, has a long history in the treatment of rheumatoid arthritis (RA), but definitive studies on its efficacy and mechanism of action are lacking. This study aims to elucidate the pharmacodynamic role of SGFD against RA and the potential mechanisms based on a combination of network pharmacology and experimental verification. The RA model in rats was induced by intradermal injection of bovine type Ⅱ collagen and incomplete Freund’s adjuvant at the tail root. SGFD was administered once a day by oral gavage for 4 weeks. After SGFD administration, rat’s arthritis index (AI) score and paw swelling decreased to some extent, and synovial inflammation, vascular hyperplasia, and cartilage destruction of the ankle joint were improved. Simultaneously, thymus and spleen index and serum levels of C-reactive protein (CRP) were lowered. Network pharmacology revealed that quercetin, kaempferol, naringenin, formononetin isorhamnetin and licochalcone A were the potentialiy active components, and IL6, TP53, TNF, PTGS2, MAPK3 and IL-1β were potential key targets for SGFD in the treatment of RA. Ingredients-targets molecular docking showed that the components had the high binding activity to these target proteins. The mechanism of SGFD for RA involves various biological functions and is closely correlated with TNF signaling pathway, Osteoclast differentiation, T cell receptor signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, NF-κB signaling pathway, toll-like receptor signaling pathway, and so on. Western blot and ELISA showed that the expression of toll-like receptor 4 (TLR4), nuclear factor kappa-B (NF-κB) p65, phosphorylated c-Jun N-terminal kinase (p-JNK), p-p38, phosphorylated extracellular regulated kinase (p-ERK) and TNF-α was significantly upregulated in the synovium of RA rats, and the levels of serum inflammatory factors were significantly increased. SGFD inhibits the activation of the TLR4/NF-κB/MAPK pathway and the expression/production of pro-inflammatory cytokines. In summary, SGFD could improve the symptoms and inflammatory response in collagen-induced arthritis (CIA) rat model. The mechanism might be related to the regulation of TLR4/MAPKs/NF-κB signaling pathway and the reduction of inflammatory factor release, which partially confirms the results predicted by network pharmacology. As a chronic progressive autoimmune disease, the major pathological features of rheumatoid arthritis (RA) are infiltration of inflammatory cells, the aberrant proliferation of synovial cells, formation of pannus, erosion of cartilage and bone, and ultimately leading to destruction, deformation and loss of function of the affected joints. It is associated with a high prevalence of concomitant diseases such as cardiovascular disease, lung disease and other extra-articular and systemic diseases . RA affeShang Han Lun). It is consists of Paeoniae Radix Alba , Glycyrrhizae Radix et Rhizoma , and Aconiti Lateralis Radix Praeparata  with the functions of reinforcing deficiency and reducing excess, warming and activating meridians, nourishing blood and extending sinew, relieving spasm and pain , RA is classified as a “Bi syndrome” associated with an insufficiency of the body’s vital energy (known as qi), and the intrusion of “wind (feng)”, “cold (han)”, “dampness (shi)”, “heat (re)” and other evil qi from outside, resulting in a blockage of qi and blood in the meridians . Chineseand pain . In the Network pharmacology is a strategy and technology of bioinformatics network construction and network topology analysis based on a network database query, high-throughput histological data analysis, and computer virtual computing . It adopWistar rats  were purchased from Beijing Weitong Lihua Experimental Animal Technology Co., Ltd. The license number for experimental animal production is SCXK (Jing) 2016–0011. All rats were housed in a barrier-free environment at the Beijing University of Chinese Medicine, and the license number for experimental animal use is SYXK (Jing) 2020–0033. The animals were housed in a temperature of 22–24°C, relative humidity of 50–70%, and a light-dark cycle of 12 h. All rats were acclimatized to the environment for 1 week before the experiment. The animal study was reviewed and approved by the Medical and Experimental Animal Ethics Committee of the Beijing University of Chinese Medicine (No. BUCM-4-2019100501-4122).Bovine type II collagen  was emulsified in an equal volume of incomplete Freunds adjuvant . Each rat was immunized on day 0 with 0.2 ml of the cold emulsion by multiple intradermal injections on the back and tail base. On day 7, after the first immunization, 0.1 ml of the emulsified collagen II was injected intradermally at the base of the tail for booster immunization . Normal n = 13/group): the model group, the positive drug tripterygium glycosides tablet group (9 mg/kg) (TG), the SGFD group with low-dose (1.05 crude drug g/kg) (SGFD-L), medium-dose (2.1 crude drug g/kg) (SGFD-M) and high-dose (4.2 crude drug g/kg) (SGFD-H). Meanwhile, the normal group was established.A total of 65 CIA model rats were successfully duplicated and randomly divided into five groups as follows . Each packet contains Bai-Shao 9g, Gan-Cao 9g, and Fu-Zi 3g (in crude drug). TG was purchased from Zhejiang Deende Pharmaceutical Co., Ltd. The tablet and Chinese granules were ground and mixed with distilled water before use. Animals were treated with 10 ml/kg by oral gavage, once a day for 4 weeks (D18 to D45). In addition, rats in the normal and model groups received the same amount of distilled water. The rat’s spontaneous activity, mental status, and weight were observed.The swelling of the hind paws of rats was measured with a paw volume meter  and the AI of each rat was assessed at days 0, 7, 17, 24, 31, 38, and 45 as described previously. The paw swelling rate was calculated as follows:At the end of the experiment, the rats were anesthetized and then sacrificed. The tissues of the right ankle joint were collected and fixed with 4% paraformaldehyde for 24 h and decalcified with 10% EDTA. After processing by conventional histological procedures, including dehydration, transparency, wax immersion, and embedding, the paraffin-embedded tissues were cut into 5-μm-thick sections. Histopathological examination (HE) with staining  was used to assess the pathological and morphological changes in the ankle joint.Thymus and spleen were collected after sacrificed rats, washed in normal saline, blotted with filter paper, and weighed. The thymus and spleen index were calculated as follows:The blood of rats was collected by the abdominal aortic method, and the serum was separated by centrifugation. The serum levels of rheumatoid factor (RF), C-reactive protein (CRP), interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), and IL-17 were determined using the respective ELISA kits. The specific operation was performed according to the instructions of the kit.http://tcmspw.com/tcmsp.php) database (https://pubchem.ncbi.nlm.nih.gov/) and then sequentially imported into the SwissTargetPrediction database (http://www.swisstargetprediction.ch/) for target prediction. Targets with a probability ≥0.5 were selected as potential targets for active ingredients. The TCMSP database was also used to obtain the target information for each active ingredient. RA-related targets were obtained from the Drugbank database (https://www.drugbank.ca/), Therapeutic Target Database (http://db.idrblab.net/ttd/), and DisGeNET database (https://www.disgenet.org/) by searching the keyword “rheumatoid arthritis”. The gene names and Uniprot ID of all targets were obtained from the Uniprot database (https://www.uniprot.org/), and the species was restricted to “Homo sapiens”.The ingredients of Bai-Shao (BS), Gan-Cao (GC), and Fu-Zi (FZ) in SGFD were obtained from the Traditional Chinese Medicine systems pharmacology . The species studied was “Homo sapiens” with a required minimum interaction score of 0.4. The overlapping targets were imported into the DAVID database (https://david.ncifcrf.gov/tools.jsp) to perform a gene ontology (GO) analysis and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, where the GO analysis consists of three modules: biological process (BP), Molecular Function (MF) and Cellular Component (CC). Then, the PPI network and the herb-compound-target-pathway interaction network were visualized using Cytoscape 3.7.2 software (The overlapping targets between active compound targets and RA-related targets were used to construct a protein-protein interaction (PPI) network by STRING database  (http://database  (https:/software .http://www1.rcsb.org/). AutoDock 4.2 was used to further modify the protein by incorporating new polar hydrogen atoms and calculating the Gasteiger charges. Hydrogen atoms, Gasteiger charges, and rotatable bonds were also assigned to the ligands. Molecular docking was then performed using AutoDock 4.2 and visualized using Pymol software.The top six targets from the PPI network, and the main active compounds of SGFD were selected for the molecular docking analysis. The files of active ingredients in Mol2 format were downloaded from the TCMSP database, and the files of the protein targets in PBD format were downloaded from the PDB database (Protein expressions of toll-like receptor 4 (TLR4), nuclear factor kappa-B (NF-κB) p65, c-Jun N-terminal kinase (JNK), p-JNK, extracellular regulated kinase (ERK), p-ERK, p38, p-p38, and TNF-α were measured by Western blotting. RIPA Lysis Buffer containing protease and phosphatase inhibitors was used to lysis synovial tissue from knee joints. Protein concentration was determined using a BCA protein detection kit . The total protein (10 μg) of each sample was added to SDS-PAGE gel, separated by electrophoresis, and then transferred to the PVDF membrane. The PVDF membranes containing the proteins were placed in a closed solution for 1.5 h and subsequently incubated overnight at 4°C with the required primary antibodies, including TLR4 antibody , NF-κB p65 antibody , JNK antibody , p-JNK antibody , ERK antibody , p-ERK antibody , p38 antibody , p-p38 antibody  and TNF-α antibody  and β-tubulin antibody  overnight at 4°C. After incubation with HRP-conjugated Affinipure Goat Anti-Mouse IgG (H + L)  or HRP-conjugated Affinipure Goat Anti-Rabbit IgG (H + L)  for 1 h, the PVDF membranes were washed with TBST solution and then processed with chemiluminescent reagents for exposure and photography. Western blot bands were quantified using ImageJ 1.52V and their relative expression levels were quantified as the ratio of the corresponding protein to β-tubulin.p-value < 0.05.Experimental data were statistically analyzed using SPSS 22.0 and GraphPad Prism 8 software and expressed as mean ± standard deviation (SD). One-Way ANOVA was used when each group’s data were normally distributed and the variances were equal. The Fisher’s LSD post-hoc test was used for comparison between groups. When the data were not normally distributed or the variance was not homogeneous, a nonparametric test was used. The difference was statistically significant when p < 0.05 or p < 0.01). Similar to the trend of paw swelling results, TG and the high dose of SGFD significantly decreased AI from day 38 (p < 0.05 or p < 0.01). At the end of the study (day 45), the paw swelling rate and AI of rats in each administration group were significantly lower than those in the model group, and the hair and mental status of rats in the treatment group gradually recovered  (p < 0.05). Compared with the model group, treatment with SGFD at a high dose significantly decreased the CRP level of rats (p < 0.05). Meanwhile, there was no significant difference in RF levels between groups.The spleen and thymus index of rats in the model group were significantly increased compared with those in the normal group. Compared with the model group, the spleen index in the SGFD-M and SGFD-H groups and the thymus index in the SGFD-H group showed a significant decrease ( < 0.05) . As showFirstly, after ADME screening by OB ≥ 30% and DL ≥ 0.18, 127 active ingredients were obtained for SGFD , and 334p < 0.01, FDR < 0.01). The top 10 terms in BP, CC and MF according to the number of genes are shown in p < 0.01, FDR < 0.01), including TNF signaling pathway, Osteoclast differentiation, T cell receptor signaling pathway, MAPK signaling pathway, NF-κB signaling pathway, Toll-like receptor signaling pathway, etc. , TNF, prostaglandin-endoperoxide synthase 2 (PTGS2), MAPK3 and IL-1β were used as ligands and receptors, respectively. Molecular docking results showed that each component had good binding activity to each target   Figure . Quercetp < 0.05 or p < 0.01). Compared with the model group, SGFD treatment at low and medium doses significantly decreased the levels of IL-17 (p < 0.01); SGFD treatment at low and high doses significantly decreased TNF-α level (p < 0.05 or p < 0.01), and SGFD at all doses notably decreased the serum levels of IFN-γ, IL-1β and IL-6 (p < 0.01).As shown in p < 0.01). Compared with the model group, a high dose of SGFD treatment decreased the expression of TLR4, NF-κB p65, and TNF-α (p < 0.01), and inhibited the increase in phosphorylation of p38 and JNK (p < 0.01). The p-ERK1/2 was slightly suppressed but not statistically significant.As shown in RA is a complex, chronic systemic autoimmune disease characterized by joint or synovium inflammation, angiogenesis, cartilage, and bone destruction, leading to joint swelling, pain and morning stiffness, eventually deformity and functional disability . CurrentTripterygium wilfordii Hook. f.)  . It mainook. f.) . Tripterook. f.) . Therefoin vivo, and when combined with RF, can help avoid misdiagnosis (RF is an autoantibody that reacts against the Fc portion of IgG antibodies, and is produced locally by B cells in lymphoid follicles . The immiagnosis . The serThe pharmacological components and complex molecular mechanism of SGFD on RA were investigated using network pharmacology. By screening the active ingredients and analyzing the Herb-Compound-Target-Pathway network, quercetin, kaempferol, naringenin, formononetin isorhamnetin and licochalcone A were considered as the potential active components of SGFD exerting pharmacological effects on RA. Quercetin  has beenCombined with network pharmacology analysis and related literature, IL6, TP53, TNF, PTGS2, MAPK3 and IL-1β could be potential key targets for SGFD in treating RA. TNF-α, IL-1β and IL-6, as typical pro-inflammatory factors, play important roles in the pathogenesis and development of RA. Currently, TNF-α inhibitory drugs such as the monoclonal antibodies infliximab and adalimumab , and IL-Among the 29 signaling pathways predicted by network pharmacology, the regulation of inflammatory mediators is an interesting pathway described. RA is a chronic autoinflammatory disease with abnormal innate and adaptive immune responses. The markedly increased thymus and spleen indices in RA rats indicate immune system activation . As moduIn summary, this study explored the therapeutic effects and underlying mechanism of SGFD against RA based on a combination of network pharmacology and experimental verification. The results showed that SGFD could improve the symptoms and inflammatory response in the CIA rat model. Its mechanism might be related to the regulation of the TLR4/MAPKs/NF-κB signaling pathway, and the reduction of inflammatory factor release , which p


Radix Angelicae biseratae (Duhuo), has been reported to have multiple pharmacological activities. However, its therapeutic effects against knee osteoarthritis (OA) remain poorly investigated. The present study is aimed at uncovering the core targets and signaling pathways of marmesine against osteoarthritis using a combined method of bioinformatics and network pharmacology.  Marmesine, a major active ingredient isolated from  We utilized SwissTargetPrediction and PharmMapper to collect the potential targets of marmesine. OA-related differentially expressed genes (DEGs) were identified from GSE98918 dataset. Then, the intersection genes between DEGs and candidate genes of marmesine were subjected to protein-protein interaction (PPI) network construction and functional enrichment analysis. The core targets were verified using the molecular docking technology.  A total of 320 marmesine-related genes and 5649 DEGs and 60 ingredient-disease targets between them were identified. The results of functional enrichment analyses revealed that response to oxygen levels, neuroinflammatory response, PI3K-Akt signaling pathway, MAPK signaling pathway, FoxO signaling pathway, and osteoclast differentiation was identified as the potential mechanisms of marmesine against OA. EGFR, CASP3, MMP9, PPARG, and MAPK1 served as hub genes regulated by marmesine in the treatment of OA, and the molecular docking further verified the results.  Marmesine exerts the therapeutic effects against OA through multitarget and multipathways, in which EGFR, CASP3, MMP9, PPARG, and MAPK1 might be hub genes. Our research indicated that the combination of bioinformatics and network pharmacology could serve as an effective approach for investigating the potential mechanisms of natural product. Knee osteoarthritis (OA) is a common chronic osteoarthropathy that is characterized by joint space stenosis, bone hyperplasia, cartilage degeneration, and synovitis . Knee dyRadix Angelicae biseratae (Duhuo) is the root of the Angelica biserrata and has long been used to treat inflammation and arthralgia syndrome by alleviating pain and eliminating dampness [Radix Angelicae biseratae; of these volatile oil and coumarins are the primary constituents. However, the active ingredient of Radix Angelicae biseratae is complex, and the key active ingredient remains unknown. Marmesine is a furanocoumarin compound isolated from Radix Angelicae biseratae. It also has been reported to exhibit multiple pharmacological activities, including anticancer, antiangiogenic, anti-inflammatory, and hepatoprotective effects [Chinese herbal medicine is the most commonly complementary and alternative medicine for OA treatment in China –8. Many dampness . Over 53 effects –13. HoweBecause natural products have multiple targets and exhibit a wide range of pharmacological effects, it is a great challenge to understand the corresponding biological functions and pathways of hub molecular targets. Network pharmacology is a novel and efficient tool to systematically uncover all potential targets, functions, and mechanisms of active ingredients at the system and molecular levels. It also provides a systematic and holistic perspective for analyzing drug activities . In the https://www.ncbi.nlm.nih.gov/). Then, we used the robust multiarray average method to carry out data standardization preprocessing. The limma package of R software was applied to identify the differentially expressed genes (DEGs) between healthy samples (n = 12) and OA samples (n = 12), and the cut-off criteria were set as follows: p value < 0.05 and ∣logFC | ≥0.3 [We downloaded the transcriptome profiles of OA patients (GSE98918 dataset) from the GEO database (C | ≥0.3 . The volhttps://pubchem.ncbi.nlm.nih.gov/). SwissTargetPrediction is a web server that aims to predict the potential targets of small molecules based on a combination of 2D and 3D similarity measures with known ligands [First, the 2D chemical structure of marmesine was downloaded from the PubChem database , the species was chosen as Homo sapiens, and a required confidence score > 0.4 was set to generate the TSV format file [The overlapped genes associated with OA and marmesine were identified as candidate targets by the Venn tool. Then, these candidate targets were introduced into the STRING database , of which the 3D protein conformations with a crystal resolution of smaller than 3 Å were selected. Then, the AutoDockTools 1.5.6 software was used to remove water, separate proteins, add nonpolar hydrogen, charge calculation, and construct the docking grid box. We used the AutoDock Vina 1.1.2 software to perform docking simulation, and the results were visualized via the PyMOL software.The hub target crystal structure was downloaded from the RCSB Protein Data Bank  was performed to assess the intragroup data repeatability, and the results showed that the repeatability of GSE98918 dataset is good . As showThe 2D chemical structure of marmesine is presented in These 60 overlapping genes were further analyzed by enrichment analyses, which showed that marmesine impacted a series of GO-BP, such as cell growth, cellular response to external stimulus, response to oxygen levels, cellular response to environmental stimulus, positive regulation of growth, response to mechanical stimulus, heart growth, and neuroinflammatory response Figures  and 5. BFurthermore, a component-target-pathway interaction network diagram was constructed via the Cytoscape software to further elaborate the relationship between the potential targets and corresponding pathways of marmesine against OA. As shown in The Cytoscape software was applied to construct the PPI network. Nine genes that were not linked to others in the network will be filtered out, including ARHGAP1, GSTA3, CRABP2, F11, BDKRB1, TPI1, CD1A, ITPKA, and ADAM33, and the PPI network contained 51 nodes and 154 edges . FurtherA binding energy lower than -5 kcal/mol shows that bioactive compound had good binding ability with targets .  FigureRadix Angelicae biseratae (Duhuo) has long been used to treat arthralgia syndrome. Marmesine is the primary active component of Radix Angelicae biseratae, which has been reported to exert anti-inflammatory effect. However, the therapeutic effects and potential mechanisms of marmesine against OA have not been reported. Bioinformatics could identify new drug targets and predict the reposition of these licensed drugs in the treatment of additional indications [OA is a severe osteoarthropathy that impacts the whole joint system and often accompanied by the occurrence and development of synovitis . Due to ications . Networkications . TherefoIn the present study, 320 potential targets of marmesine and 5649 DEGs of OA were obtained. 60 cotargets were identified as the therapeutic targets of marmesine in the treatment of OA. Among them, six core targets  were indicated to play an important role via CytoNCA plugin of the Cytoscape software. Furthermore, we performed the molecular docking analysis to further confirm the results of network pharmacology.Epidermal growth factor receptor (EGFR) is a tyrosine kinase receptor, which plays an important role in the maintenance of superficial chondrocytes during the development of articular cartilage. It has been reported that chondrogenic EGFR signaling pathway involved in adult cartilage homeostasis and the progression of OA . PreviouκB signaling pathways [κB signal pathways [κB pathways in a knee OA rat model [The enrichment analysis of these cotargets revealed that cellular metabolism, immune, and inflammatory pathways may be the potential mechanisms of marmesine in the treatment of OA. The representative pathways included PI3K-Akt signaling pathway, MAPK signaling pathway, FoxO signaling pathway, Ras signaling pathway, HIF-1 signaling pathway, osteoclast differentiation, ErbB signaling pathway, and EGFR tyrosine kinase inhibitor signaling pathway. MAPK signaling pathway is associated with the pathogenesis of arthritis and related diseases, especially OA . For exapathways . Wang-Bipathways . Osteoclpathways . For exaat model . IL-4 coat model .Our findings revealed that marmesine had multitargets and multipathways in the treatment of OA. Besides, EGFR, CASP3, MMP9, PPARG, and MAPK1 are the hub targets enriched in the MAPK signaling pathway and osteoclast differentiation and for marmesine to exert its anti-inflammatory and antiapoptosis effects against OA. Furthermore, molecular docking verification was performed to confirm that marmesine could form a stable docking model with these hub targets. Our research provides a systematic view of the potential therapeutic targets and signaling mechanisms of marmesine against OA based on network pharmacology and bioinformatics analyses, which may provide a novel therapeutic strategy for OA.