To explore the mechanism of the action of Huoluo Xiaoling Dan (HLXLD) in the treatment of psoriasis based on network pharmacology and molecular docking.  The main active components and targets of HLXLD were collected from CMSP, and the targets related to psoriasis were collected from GeneCards, OMIM, TTD, DisGeNET, and DrugBank. Drug disease target genes were obtained by Venny tools, drug-component-target networks were constructed and analyzed, and pathway enrichment analysis was performed. AutoDockTools is used to connect the core components and the target, and PyMOL software is used to visualize the results.  126 active components  and 238 targets of HLXLD were screened out. 1,293 targets of psoriasis were obtained, and 123 drug-disease targets were identified. Key targets included AKT1, TNF, IL6, TP53, VEGFA, JUN, CASP3, IL1B, STAT3, PTGS2, HIF1A, EGF, MYC, EGFR, MMP9, and PPARG. Enrichment analysis showed that 735 GO analysis and 85 KEGG pathways were mainly involved in biological processes such as response to the drug, inflammatory response, gene expression, and cell proliferation and apoptosis, as well as signal pathways such as cancer, TNF, HIF-1, and T cell receptor. Molecular docking showed that there was strong binding activity between the active ingredient and the target protein.  HLXLD could treat psoriasis through multicomponents, multitargets, and multipathways, which provides a new theoretical basis for further basic research and clinical application. Psoriasis was a common inflammatory reactive skin disease with erythema and scaly lesions as the main manifestations, accompanied by varying degrees of pruritus, with a chronic course and easy recurrence . The patTCM treatment of psoriasis is mostly based on blood, and blood stasis syndrome is one of the most common syndromes . In receTherefore, this study through network pharmacology to predict the potential targets and signal pathways of HLXLD in the treatment of psoriasis and combines it with molecular docking technology to assist verification, to provide a certain theoretical basis for the in-depth study of HLXLD in the treatment of psoriasis.https://www.tcmspw.com/), the names of four Chinese herbal medicines were input in succession to obtain the corresponding chemical compounds and related information. According to the principle of pharmacokinetics (ADME), the oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥0.18 were set as the screening conditions to obtain the effective components and corresponding targets of each drug of HLXLD. The Uniprot database [http://www.uniprot.org/) was used to screen the target genes from human attributes and was verified, and the target names were standardized into official symbols.On the Traditional Chinese Medicine Database and Analysis Platform  , OMIM [https://omim.org/), TTD [http://db.idrblab.net/ttd/), DisGeNET [https://www.disgenet.org/), and Drugbank [https://go.drugbank.com/) were searched with “psoriasis” as keywords. In the GeneCards database, the score indicates the closeness between the target and the disease, so the target with a score greater than the median was set as the potential target of psoriasis. The targets obtained from the above disease database were combined, and the repetition was removed to get the psoriasis-related targets, and the Uniprot database is used to standardize the target names through the above methods.To ensure the comprehensiveness and accuracy of the data, the potential targets of psoriasis in GeneCards  (https://), OMIM  (https:/g/), TTD  , “Homo sapiens” was selected, the minimum required interaction score was set to ≥ 0.4, the free nodes were hidden, the PPI network was built, and the corresponding files were exported. The downloaded results were uploaded to Cytoscape3.8.2 software for analysis. The network analyzer and cytoNCA plugins were used for topology analysis. The core targets were screened by taking the median of 2 times of degree, and the median of Betweenness Centrality (BC) and Closeness Centrality (CC) as card values.The potential targets screened above were imported into the STRING  (https:/https://david.ncifcrf.gov/), and the species was defined as “Homo sapiens.” The GO function and KEGG pathway enrichment of common target genes of HLXLD and psoriasis were analyzed. The results were visualized by using Bioinformatics online mapping tool (http://www.bioinformatics.com.cn/), and the network diagram of “disease-pathway-target-component drug” was constructed by using Cytoscape 3.8.2.The previously obtained potential targets were imported into the DAVID database  (https:/https://www.rcsb.org/). The selection criteria [−1, it indicated that there was good binding activity between the receptor and the ligand [Molecular docking was applied for the key components with the top 5 degree values in the drug-compound-target network and the core targets with the top 5 degree values in the PPI network. The protein structure of the core target was downloaded from the PDB  databasecriteria  are as fcriteria  softwarecriteria  softwaree ligand . The resThrough TCMSP database retrieval, DS, DG, RX, and MY had 66, 8, 9, and 45 active ingredients, respectively. A total of 126 active components of HLXLD were obtained after merging and removing duplicates, and the corresponding target proteins were further obtained. After being transformed into standard gene names in the UniProt database and removing duplicates, a total of 238 predicted targets were obtained.After merging and removing the duplication of acne disease target genes collected by GeneCards, OMIM, TTD, DisGeNET, and DrugBank databases, a total of 1,923 related target proteins were obtained. After matching the target genes of the active components of HLXLD with the target genes related to psoriasis, the intersection was taken, and 123 common genes were obtained through the Venn diagram .β-sitosterol (MOL000358) acted on 17 drug targets. The active components and the corresponding targets of HLXLD in the treatment of psoriasis were introduced into the Cytoscape 3.8.2 software to construct the network diagram of the drug-compound-target network which included 225 points and 759 edges . Among t123 intersection targets brought in the STRING database to set up the PPI network . The netP value to draw the bubble chart , 49 cellular component (CC), and 98 molecular function (MF). The top 20 results were selected according to the P value to draw the bubble diagram , TNF signaling pathway, HIF-1 signaling pathway, T cell receptor signaling pathway, etc. At present, more and more pieces of evidence supported the correlation between cancer and psoriasis. Several meta-analyses and retrospective studies –60 have g cancer . The incg cancer . Anotherg cancer . From ang cancer .β-Sitosterol, and dihydrodanshenlide, involving multiple signal pathways such as cancer signaling pathway, TNF signaling pathway, HIF-1 signaling pathway, and T cell receptor signaling pathway, participating in the drug reaction, inflammatory reaction, gene expression, cell proliferation, and apoptosis, to play a role in the treatment of psoriasis, which provided a theoretical basis for the further application of HLXLD in the clinic. However, because this study mainly relied on the network database, there were still some limitations. The specific drug action mechanism needs further experimental verification in vivo and in vitro.To sum up, based on the network pharmacology method, this study systematically expounded the relationship between HLXLD in the treatment of psoriasis through multicomponent, multitarget, and multichannel, and verifies the strong binding activity between key components and core targets by molecular docking technology. The results showed that HLXLD might act on AKT1, IL6, TNF, TP53, VEGFA, EGF, EGFR, CXCL8, MMP9, MAPK8, and other targets through active components such as quercetin, luteolin, tanshinone IIA,


Clinical studies have shown that dapagliflozin can reduce cardiovascular outcome in patients with type 2 diabetes mellitus (T2DM), but the exact mechanism is unclear. In this study, we used the molecular docking and network pharmacology methods to explore the potential mechanism of dapagliflozin on T2DM complicated with cardiovascular diseases (CVD). Dapagliflozin's potential targets were predicted via the Swiss Target Prediction platform. The pathogenic targets of T2DM and CVD were screened by the Online Mendelian Inheritance in Man (OMIM) and Gene Cards databases. The common targets of dapagliflozin, T2DM and CVD were used to establish a protein‐protein interaction (PPI) network; the potential protein functional modules in the PPI network were found out by MCODE. Metascape tool was used for Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis. A potential protein functional module with the best score was obtained from the PPI network and 9 targets in the protein functional module all showed good binding properties when docking with dapagliflozin. The results of KEGG pathway enrichment analysis showed that the underlying mechanism mainly involved AGE‐RAGE signalling pathway in diabetic complications, TNF signalling pathway and MAPK signalling pathway. Significantly, the MAPK signalling pathway was considered as the key pathway. In conclusion, we speculated that dapagliflozin played a therapeutic role in T2DM complicated with CVD mainly through MAPK signalling pathway. This study preliminarily reveals the possible mechanism of dapagliflozin in the treatment of T2DM complicated with CVD and provides a theoretical basis for future clinical research. The prevalence of T2DM is rising year by year, which has become the primary disease threatening the health and life of human beings.Dapagliflozin, a SGLT2 inhibitor, is a novel hypoglycaemic drug and has been widely used in the treatment of T2DM. A number of large double‐blind clinical studies have demonstrated that dapagliflozin reduced the composite end‐point of cardiovascular hospitalization and death in patients with T2DM.Drug targeting interaction is the basis of target discovery of therapeutic drugs.22.1http://www.chemsrc.com/). Based on the method that similar drugs share similar targets,www.swisstargetprediction.ch/).http://www.uniprot.org/).The bioactive component of dapagliflozin was searched from the published literature in PubMed database, with “dapagliflozin” as the key word. Then, the structural formula of bioactive component retrieved in the literature was checked with that in the chemical database (2.2http://omim.org/)http://www.genecards.org/) databases,The pathogenic targets of T2DM complicated with CVD were searched by Online Mendelian Inheritance in Man http://string‐db.org/),http://cytoscape.org/),In order to identify the interaction targets of dapagliflozin in the treatment of T2DM complicated with CVD, we selected the online drawing tool Interactive Venn (2.4https://metascape.org/),P <.01 as the cut‐off criteria. The top 10 GO items and top 20 KEGG pathways that meet the criterion were visualized by bioinformatics online tools (http://www.bioinformatics.com.cn/) and EHBIO Gene Technology Platform (http://www.ehbio.com/ImageGP/).Gene Ontology (GO) functional analysis and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using Metascape ,http://www.rcsb.org/).Figure The “sdf” file of dapagliflozin bioactive component was downloaded from the PubChem database ).After screening the literature and online database, we have identified the bioactive component of dapagliflozin and found 73 candidate genes. The details of these candidate genes are shown in Table 3.2Figure (B)). In order to more accurately elucidate the mechanism of dapagliflozin in the treatment of T2DM complicated with CVD, we used MCODE to conduct cluster analysis on the PPI network and obtained a potential protein functional module with the best score as shown in Figure To estimate the role of the candidate targets in complex disease and found the interactive effects, overlapping targets were submitted to the STRING11.0 platform to establish PPI network, which consisted of 25 targets and 107 interacting edges in total. After analysing the topology parameters of PPI network, the 25 targets were sorted in descending order by degree and arranged in a concentric circle according to the degree . In terms of biological processes, the top 10 items were mainly related to positive regulation of cell migration , MAPK cascade , regulation of reactive oxygen species metabolic process , cellular response to external stimulus (GO:0 071 496) and regulation of protein serine/threonine kinase activity (GO:0 071 900). The cellular components were mainly concentrated in focal adhesion, cell‐substrate adheres junction, cell‐substrate junction, adheres junction and anchoring junction. According to the results of the KEGG pathway enrichment analysis, most involved in MAPK signalling pathway, TNF signalling pathway, AGE‐RAGE signalling pathway in diabetic complications, influenza A, human T‐cell leukaemia virus 1 infection, Ras signalling pathway, Rap1 signalling pathway, focal adhesion, kaposi sarcoma‐associated herpesvirus infection and relaxin signalling pathway. Interestingly, the common targets of dapagliflozin, T2DM and CVD mainly enriched in MAPK signalling pathway and two of the top 10 biological process items were related to MAPK cascade. In addition, most of the molecular function items focused on regulating kinase activity, implying that the MAPK signalling pathway might be the key pathway.3.4Figure Component‐target‐pathway network was constructed with Cytoscape3.7.2 based on the results of KEGG pathway enrichment analysis Figure 5. Degr3.5Table Figure Figure (a)). As shown in Figure In the present study, the interaction activity between the core genes and dapagliflozin was verified by molecular docking. It is generally believed that the lower the energy when the conformation of ligand binding to the receptor is stable, the greater the possibility of interaction. Totally, nine pairs were delivered into the docking simulation, and all binding complexes showed good binding affinity with an average of −6.8 kcal/mol. Nine conformations with the lowest binding energy were visualized, including dapagliflozin‐MAPK1 docking , dapagliflozin‐MAPK3 docking , dapagliflozin‐MAPK14 docking , dapagliflozin‐EGFR docking , dapagliflozin‐ICAM1 docking , dapagliflozin‐GAPDH docking , dapagliflozin‐VCAM1 docking , dapagliflozin‐MMP1 docking  and dapagliflozin‐MMP3 docking  . Based on the analysis of the component‐target‐pathway network, we screened MAPK1, MAPK3, MAPK14 and EGFR as key targets, indicating that the role of dapagliflozin‐mediated therapy in the treatment of T2DM complicated with CVD might be mainly associated with above targets. For instance, MAPK1, as a key kinase of cell stress transmission, is involved in the regulation of a variety of cellular functions and is related to hyperglycaemia, oxidative stress and growth factors in diabetic. MAPK signalling cascade also plays a vital role in the pathogenesis of CVD, such as cardiac remodelling after myocardial infarction, the formation of atherosclerosis and the formation of neovascularization, and its imbalance will lead to the occurrence of corresponding CVD.According to KEGG pathway enrichment analysis and literature review, we hypothesized that dapagliflozin might play a therapeutic role in T2DM complicated with CVD mainly through the regulation of the MAPK signalling pathway Figure .SGLT2 is mainly located in the epithelial cells of the S1 and S2 segments of the renal proximal tubule, responsible for the reabsorption of about 90% glucose in urine.+/H+ exchanger flux and subsequently reducing intracellular free Na+, which was consistent with Durak and coworkers’ findings.Up till now, there has been considerable clinical evidence that dapagliflozin as a SGLT2 inhibitor significantly improves cardiovascular outcome in patients with T2DM. Interestingly, however, no expression of SGLT2 was detected in the human heart,Table Table Figure Figure In addition to dapagliflozin, other SGLT2 inhibitors have also been demonstrated to have cardiovascular protective effects.In conclusion, our research systematically elucidated the underlying molecular mechanisms by which dapagliflozin simultaneously interfered with T2DM and CVD based on the network pharmacology and molecular docking. We predicted 4 key targets from complex networks and concluded that the MAPK signalling pathway is the main pathway for dapagliflozin in the treatment of T2DM complicated with CVD. We also preliminarily predicted that empagliflozin and canagliflozin interacted well with targets on the MAPK pathway. The above results provided scientific evidence for clinical application of dapagliflozin in the treatment of T2DM complicated and CVD, and also provided a new idea for the future research on the mechanism of action of SGLT2 inhibitors.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.Zhaodi Yue: Conceptualization ; Validation ; Writing‐original draft (lead); Writing‐review & editing . Li Li: Conceptualization . Hui Fu: Data curation ; Investigation . Yanyan Yin: Data curation ; Investigation . Bingyu Du: Data curation ; Investigation . Fangqi Wang: Data curation ; Investigation . Yi Ding: Writing‐review & editing . Yibo Liu: Software ; Visualization . Renjie Zhao: Software ; Visualization . Zhongwen Zhang: Conceptualization (lead); Funding acquisition (lead); Supervision ; Writing‐review & editing . Shaohong Yu: Conceptualization (lead); Formal analysis (lead); Supervision .Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.Table S4Click here for additional data file.


Ulcerative colitis (UC), a chronic and nonspecific inflammatory bowel disease, seriously affects the quality of patients' life. Han Re Bing Yong Fa (treating diseases with both cool- and warm-natured herbs) is a classical therapeutic principle of traditional Chinese medicine (TCM), which is often used to treat chronic diseases, including UC. The Gan Jiang-Huang Qin-Huang Lian-Ren Shen decoction (GJHQHLRSD), a representative of Han Re Bing Yong Fa, is effective in alleviating inflammatory symptoms in UC. However, the pharmacological mechanism underlying its anti-inflammatory effect remains unclear.  A network pharmacology strategy, including the construction and analysis of the drug–disease network, was used to explore the complex mechanism of GJHQHLRSD treatment of UC. In addition, molecular docking technology was used to preliminarily examine the binding ability of the potential active components and core therapeutic targets of GJHQHLRSD. BCL2L1, NR3C1, ALOX5, S1PR5, NR1I2, CYP2D6, and LPAR6. The molecular docking results revealed that the following displayed strongest combined effects: EGFR with kaempferol, ERK1 with worenine, STAT3 with Palmidin A, BCL2L1 with diop and VEGFA with ginsenoside Rg3. The KEGG and gene ontology enrichment analyses results indicated that GJHQHLRSD functions by regulating the EGFR signaling pathway in UC treatment. Other effective biological processes involved in UC treatment included cancer-related as well as inflammation and viral infection signaling pathways, such as the “MicroRNAs in cancer,” “TNF signaling pathway,” and “JAK-STAT signaling pathway.”  The network pharmacology results revealed 140 targets of GJHQHLRSD which are involved in UC. The PPI network analysis identified seven target genes:  This study reflects the multicomponent, multitarget, and multipathway characteristics of the action mechanism of GJHQHLRSD in treating UC. Furthermore, it helps better understand the TCM therapeutic principle of Han Re Bing Yong Fa and explore novel candidate drug targets for UC treatment. Ulcerative colitis (UC), a chronic, relapsing, and nonspecific inflammatory disease, affects several million individuals worldwide. UC is an inflammatory bowel disease (IBD), and its aetiology and pathogenesis are not yet fully understood. Currently, it is believed that IBD is a complex genetic disease that is instigated and amplified by the confluence of multiple genetic and environmental variables that perturb the immune–microbiome axis . Howeverβ, and TNF-α [Gegen Qinlian decoction (GGQLD), Wumei pill (WMP), Shaoyao decoction (SYD), and Gan Jiang-Huang Qin-Huang Lian-Ren Shen decoction (GJHQHLRSD) apply this principle and are representative prescriptions for UC treatment. The efficacy of GGQLD, WMP, and SYD has been demonstrated in several pharmacological and animal studies, which showed that formulas based on Han Re Bing Yong Fa can improve intestinal barrier function, alleviate UC, and delay cancer development [Traditional Chinese medicine (TCM) plays an important role in China's public health system, particularly in the treatment and management of chronic diseases such as UC. Currently, studies have been focusing on TCM as an alternative therapy for UC; however, there are some limitations in terms of TCM use in clinical practice, such as the lack of full guidance from the theoretical basis of TCM and the use of complex and multiflavoured herbs which are not used frequently in clinical practice. For instance, the TCM formula Guchang Zhixie Wan (GCZXW) exerts a protective effect on IBD through the STAT3/NF-kB/IL-6 pathway, and the active ingredients of the Banxia Xiexin decoction (BXXXD) primarily act on IL-4, IL-10, IL-1nd TNF-α . Howeverα, IL-1β, IL-6, and IL-10 [In China, GJHQHLRSD is primarily used to treat patients with gastrointestinal diseases, especially those with large intestinal damp-heat syndromes, which lie in the indication scope of Han Re Bing Yong Fa. GJHQHLRSD comprises Gan Jiang (Zingiberis Rhizoma), Huang Qin (Radix Scutellariae), Huang Lian (Coptidis Rhizoma), and Ren Shen (Ginseng Radix et Rhizoma). The Zingiberis Rhizoma decoction has been found to reduce colitis in mice by reducing the expression levels of TNF-nd IL-10 . The resnd IL-10 , 13. Mornd IL-10 . UC is chttps://lsp.nwu.edu.cn/tcmsp.php). The drug feasibility was evaluated by oral bioavailability (OB) and drug likeness (DL) indices. In this study, molecules with OB of ≥30% and DL of ≥0.18 were considered active compounds. The structures of GJHQHLRSD components were obtained from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and were imported into the Swiss target prediction database ; targets with a prediction score of >0 were considered the drug targets. The databases and tools were last accessed on 13 February, 2021.Data on the active compounds and protein targets of four herbs were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform , DisGeNET (https://www.disgenet.org/), and GeneCards (https://www.genecards.org/) databases. The GeneCards database establishes the correlation ranking between genes and diseases and provides the gifts and score algorithm [https://bioinformatics.psb.ugent.be/webtools/Venn/). Finally, Cytoscape software (Version 3.7.1) was used to map the disease network of drug components.Potential disease targets associated with UC were collected from the OMIM (lgorithm . The comhttps://string-db.org/). “Homo sapiens” was chosen, and a confidence score of >0.9 was set to predict the interactions. The protein-protein interaction (PPI) network analysis results were saved in TSV format and imported into Cytoscape software (https://www.cytoscape.org/). Key genes were screened using the CytoHubba module and MCODE plug-ins [The identified overlapping target genes were introduced into the STRING network platform  [https://www.genome.jp/kegg/) was used for the systematic analysis of molecular networks with interacting genes. To assess a possible mechanism of GJHQHLRSD in treating UC, the KEGG pathway enrichment analysis was performed via DAVID Bioinformatics Resources (https://david.ncifcrf.gov). Top 20 significant pathway items were considered important and were presented via a bubble graph. The abovementioned database was last accessed on 14 February, 2021.Gene ontology (GO) analysis was performed using the WebGestalt online tool (lt.org/) . The Go First, the SDF formats of small ligand molecules were downloaded from the PubChem database and then converted to the PDB format using the Open Babel software (version 3.0.0). Second, the PyMOL software (version 2.3.6) was used to remove water molecules; the original ligand was isolated from the core target protein. The processed protein targets were imported into the AutoDock software (version 4.2.0) for hydrogenation, the total charge was calculated, the atomic type was set, and the file was saved in PDBQT format. Finally, the mol2 structures of the corresponding part of the core targets were downloaded from the TCMSP database and saved in PDBQT format. The AutoDock-Vina software (version 1.1.2) was used to perform molecular docking and comprehensively scored the receptor-ligand complex to evaluate its affinity.The flowchart of the network pharmacology approach used in this study is shown in The active components of Zingiberis Rhizoma, Radix Scutellariae, Coptidis Rhizoma, and Ginseng Radix et Rhizoma were identified using the TCMSP database, and 75 potential active components were obtained. A total of 836 drug targets were selected by retrieving GJHQHLRSD from the STP database. The keyword “ulcerative colitis” was searched in the OMIM, DisGeNET, and GeneCards databases, and 906 disease targets were obtained after deduplication. Finally, the intersection images of GJHQHLRSD-UC targets were created using the Venny 2.1 online software. After mapping the UC-related genes with the targets of active compounds, 140 intersected genes were identified .Four active components were deleted owing to a lack of intersection with the disease target, thus obtaining 71 active components. Data of 71 active components and 140 overlapping target genes were entered into the Cytoscape software for creating network diagram. The isolated components were deleted because of the lack of intersection with the targets, and then, a network diagram of the interaction between the drug component and target disease was drawn . A netwoBCL2L1)), sphingosine-1-phosphate receptor 5 (S1PR5)), inflammation (arachidonate 5-lipoxygenase (ALOX5)), hormones (nuclear receptor subfamily 3 group C member 1 (NR3C1)), nuclear receptor subfamily 1 group I member 2 (NR1I2)), a monooxygenase gene with a detoxification effect (cytochrome P450 subfamily IID 6 (CYP2D6)), and a cell signal transduction gene with immune regulation (lysophosphatidic acid receptor 6 (LPAR6)).The PPI network was obtained from the STRING database and visualized using the Cytoscape software. The minimum confidence was set to 0.40 to construct the PPI network and hide independent target protein nodes. The PPI network nodes represent the proteins, and the edges represent the interactions between the proteins. The importance and priority of proteins were analyzed based on network results, and seven target genes were obtained . The sevAfter searching the 140 common targets in the R language software, BP, CC, and MF were selected for the GO analysis. The GO results showed that the intersection genes included multiple biological processes. The effect of GJHQHLRSD on UC is a result of complex multichannel synergy. In addition, the GO enrichment analysis was performed for top 20 BPs Figures . On the P value of <0.05 were obtained. The results of top 20 pathways were visualized as a bubble diagram , signal transducer and activator of transcription 3 (STAT3), and vascular endothelial growth factor A (VEGFA), which play a significant role in the GJHQHLRSD-UC network. Through a series of calculations, small molecules of diop, kaempferol, worenine, Palmidin A, and ginsenoside Rg3 ligands were selected. Molecular docking simulations were performed for selected target genes and small molecules. The docking results showed that five targets could directly couple with five bioactive compounds. Moreover, the following displayed strongest combined effects: EGFR with kaempferol, ERK1 with worenine, STAT3 with Palmidin A, BCL2L1 with diop and VEGFA with ginsenoside Rg3  may alleviate UC through multiple targets and pathways [The reason TCM treatment of UC has become a research hotspot may be related to its complex pharmacological action featuring the multitarget and multipathway approach. UC pathogenesis is related to pathogenic factors such as abnormal gut microbiota, immune response dysregulation, environmental changes, and gene variants . In thispathways . The BTWpathways . As is kpathways .Currently, the primary strategy of IBD is to balance the excessive immune response of the intestinal mucosa so as to restore the epithelial regeneration of colon. Epidermal growth factor is an activated ligand of EGFR, which can alleviate disease by directly targeting intestinal mucosal healing. EGFR activation therapy works well in clinical practice but has not shown progress in the past few decades, partly because its long-term use may cause cancer. Animal studies have shown that early administration of gefitinib, an EGFR kinase inhibitor, can increase the tumour size, whereas its late administration can reduce the tumour size. EGFR plays an important role in the pathological development of IBD, especially CAC , 40. Theα, STAT3, and JAK-STAT signaling pathways [In addition to recent research on EGFR and excessive immune response in UC treatment, research on mitochondrial autophagy demands scientific attention. Because epithelial barrier repair in colitis is dependent on energy, EGFR tyrosine kinase inhibitors and mitochondrial autophagy regulation are particularly important. Xianglian pill reduced DSS-induced acute colitis in mice by inhibiting the secretion of proinflammatory cytokines and enhancing autophagy . Moreovepathways , 55–57. α [In this network pharmacological study, 71 potentially bioactive compounds of GJHQHLRSD were identified, including kaempferol, worenine, Palmidin A, diop, and ginsenoside Rg3. Kaempferol, present in Ginseng Radix et Rhizoma and Radix Scutellariae, exerts anti-inflammatory and antitumour effects by inhibiting inflammatory factors . Woreninα . MoreoveThis study has some limitations. The pharmacological mechanisms of GJHQHLRSD in treating UC were investigated in this study. However, further animal experiments are warranted to ensure the reliability and rationality of the predicted results. In addition, further studies on related mechanisms are required to determine the function of upstream and downstream proteins regulated by key genes. Moreover, key proteins and KEGG signaling pathways must be verified through a scientific experimental design. As GJHQHLRSD is a compound ingredient, further studies are required to scientifically screen its active ingredients, improve OB, and identify adverse reactions.The application of the TCM Han Re Bing Yong Fa therapeutic principle has shown some advantages in UC treatment, especially in improving the intestinal barrier function and delaying cancer development. In this study, network pharmacological analysis revealed the characteristics of the action mechanism through which GJHQHLRSD treats UC, which may involve multiple components, targets, and multiple pathways. On the basis of the network pharmacology analysis, GJHQHLRSD achieves anti-inflammatory effects by regulating 141 pathways, included inflammation as well as cancer-related and viral infection signaling pathways, such as the “EGFR signaling pathway,” “MicroRNAs in cancer,” “TNF signaling pathway,” and “JAK-STAT signaling pathway.” Although these pathways have been shown to be strongly associated with UC, some pathways have not yet been shown to be regulated by GJHQHLRSD. Therefore, further studies on related mechanisms are required, especially on the role of upstream and downstream proteins regulated by key genes.


Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versality of microbial metabolism and a still-increasing number of newly biological pathways, linkage to standard pathway maps such as the KEGG central carbon metabolism is often problematic. We successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called ‘Pathway-Creator’ and ‘Pathway-Calculator’. The ‘Pathway-Creator’ enables an easy set-up of user-defined pathways with specific taxonomic constraints. The ‘Pathway-Calculator’ automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. The MPA_Pathway_Tool is implemented in Java and ReactJS. In the last years, studying the taxonomic and functional composition of bacterial, viral, and archaeal species in the human gut ,2,3,4,5,However, due to the microbial metabolism’s versatility and constantly newly discovered biological pathways , linkageIn general, a good pathway tool needs to meet at least the following six criteria: (i) It should provide an easy and intuitive creation of pathways to enable the fast generation of multiple pathways. (ii) Since new reactions are discovered and pathways might be updated, the tool should support modifying the pathway maps, i.e., appending new and deleting existent reactions. (iii) Already created pathways from different databases should be reusable. Consequently, the pathway tool should provide an import function for standard exchange formats, such as comma-separated values (CSV), JavaScript Object Notations (JSON), and Systems Biology Markup Language (SBML) formats. (iv) The pathway tool should also map experimental data on created pathways and highlight differences between the considered samples. (v) Since metabolic reactions are taxonomy-specific, the pathway tool needs a filter to distinguish between reactions carried out by a specific taxon. One example of this specificity is the hydrogenotrophic methanogenesis and the Wood–Ljungdahl pathway. Both pathways share similar enzymes ). However, hydrogenotrophic methanogenesis is carried out only by archaea , while tThis paper aims to present a new web application called MPA_Pathway_Tool. It enables easy creation of user-defined pathways with specific taxonomic constraints, automatically mapping microbial community data from multiple measurements on selected pathways and visualizing the results (‘Pathway-Creator’). Additionally, the ‘Pathway-Calculator’ enables the mapping of an entire omics data set on multiple pathways to support the automated data analyses. The functionality of the MPA_Pathway_Tool is demonstrated and validated by reproducing the manual assignment of proteins to metabolic pathways from a previous metaproteomics study about biogas plants, focusing on three pathways .The first part of the MPA_Pathway_Tool, the ‘Pathway-Creator’ , enablesThe ‘Pathway-Calculator’  consistsFinally, we tested the performance of the ‘Pathway-Calculator’ by uploading experimental data with different file sizes  and a different number of pathways on a local desktop computer . We utilized 1, 10, and 100 copies of the user-defined Wood–Ljungdahl pathway used in Heyer et al. [Validation of the MPA_Pathway_Tool was carried out by comparing our pathway assignment against a manual pathway assignment of a previous metaproteomics study regarding biogas plants . AdditioFor the evaluation, we created six pathway maps . The user-defined pathways BGP;  and the The summed spectral counts mapped on each user-defined pathway were slightly greater than in the published experimental data, indicating a small information loss in the previous publication .Furthermore, we compared the results of each BGP pathway with the corresponding KEGG pathway. We observed higher spectral counts for the created KEGG MODULEs compared to the respective BGP pathways . Higher We successfully implemented the pathway tool to meet all of our six defined criteria: (i) The MPA_Pathway_Tool provides an easy and fast setup of multiple pathways. Multiple reactions can be imported using various options, e.g., import by EC numbers, import of a KEGG MODULE, or import of entire SBML files. (ii) A further modification of the generated pathways is possible by deleting reactions and adding new reactions (from the KEGG database and user-defined reactions). (iii) As interchange formats, JSON, CSV, and SBML were implemented. (iv) Experimental data from metaproteomics, metatranscriptomics, and metagenomics studies can be automatically mapped on single pathways (‘Pathway-Creator’) and multiple pathways . The results of pathway mapping can also be exported as CSV. (v) The mapping algorithm includes a taxonomic filter that was successfully applied by comparing our results with published experimental data for the stated pathways. (vi) The MPA_Pathway_Tool was implemented as a stand-alone web application to guarantee the independence from users’ operating systems.The MPA_Pathway_Tool is developed as a stand-alone application for the characterization and analysis of microbial community data. To broaden its scope of application, it will be integrated into the next version of the MPA software. However, in the future, other tools such as UniPept  or ProphSince the MPA_Pathway_Tool already provides stoichiometric data, further options such as identification-driven flux balance analysis and flux vector analysis might be added to the workflow using tools such as the CellNetAnalyzer , COBRApyThe MPA_Pathway_Tool represents an intuitive web application for mapping (meta)-proteome and other omics data on metabolic pathways and the creation and modification of pathways. It consists of two different parts. First, the ‘Pathway-Creator’ allows for the creation and modification of pathways. The ‘Pathway-Creator’ also supports single-pathway mapping. The second part is the ‘Pathway-Calculator’, which provides multiple pathway mapping.The MPA_Pathway_Tool is a stand-alone web application consisting of JavaScript (JS), Hypertext Markup Language 5 (HTML), and Cascading Style Sheets (CSS) on the client side and Java on the server side. The client side is built with the help of ReactJS . We usedhttps://github.com/danielwalke/MPA_Pathway_Tool/tree/main/keggcalculator-frontend, accessed on 8 October 2021).A complete list of used dependencies on the client side is listed in the package.json file  of SBML files .For a better understanding of the mapping algorithm, we explain the application with experimental data containing proteins. Of course, the mapping algorithm can be applied for other -omics data too. Each pathway contains a pathway name (filename) and multiple reactions. On the other hand, each reaction contains an ID; a name; substrates, and products with stoichiometric coefficients, EC-numbers, K-numbers, and taxonomic constraints; and a list of matching proteins, which is empty at the beginning of the mapping calculation. For a better overview, only the last four properties are visualized as a scheme . The impExperimental data used for validating the MPA_Pathway_Tool originated from a previous metaproteomics study of 11 different biogas plants sampled at two different time points . As inpuhttps://mpa-pathwaymapper.ovgu.de/ or http://141.44.141.132:9001/home. Further documentation and the complete source code are deposited on GitHub .The MPA_Pathway_Tool is freely available on the web at


Endometriosis is a chronic estrogen-dependent inflammatory disorder that negatively affects the quality of life in women. The Wenjing decoction (WJD) is a traditional Chinese medicine that has been shown to have a therapeutic effect on endometriosis. Our study systematically explored the mechanism of WJD against endometriosis using a network pharmacology approach. Potentially bioactive compounds of WJD and their possible targets were retrieved from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The protein-protein interaction network and herbs-compounds-genes multinetwork were constructed using Cytoscape for visualization. Subsequently, the signaling pathways of common targets were retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, and molecular docking was performed using PyRx software. In total, 48 common targets were screened, such as IL6 and ESR1, which were related to inflammation and the endocrine system. The top five bioactive compounds were quercetin, kaempferol, wogonin, beta-sitosterol, and stigmasterol. KEGG enrichment analysis revealed 65 pathways containing inflammatory- and endocrine-related signaling pathways, such as the “TNF signaling pathway” and the “estrogen signaling pathway.” Taken together, the results of our network pharmacology analysis predicted that certain active ingredients of WJD might treat endometriosis by regulating inflammation and/or endocrine, which provided references for further understanding and exploration of WJD on endometriosis. Endometriosis is one of the most common, benign gynecological disorders, affecting approximately 10% of women of reproductive age and 50% of those with fertility issues . EndometAngelicae Sinensis (Danggui), Rhizoma Ligustici (Chuanxiong), Radix Ginseng (Renshen), Rhizoma Curcumae (Ezhu), Cortex Moutan (Mudanpi), Radix Achyranthis Bidentatae (Niuxi), Cortex Cinnamomi (Rougui), Radix Paeoniae Alba (Baishao), and Radix Glycyrrhizae (Gancao). The efficacy of WJD has been demonstrated in several animal and human studies, which showed that WJD could shrink existing endometriotic implants, alleviate dysmenorrhea, and increase the pregnancy rate. However, the mechanism and active ingredients of WJD have not yet been clarified [In China, traditional Chinese medicine (TCM) is commonly used as an alternative therapy for endometriosis due to its significant therapeutic effect and lower toxicity , 9. Certlarified –14.α (TNF-α) [Endometriosis is classified as an estrogen-dependent chronic inflammatory condition . The loc (TNF-α) –22. In c (TNF-α) . ConsideComplex TCM formulations with dozens or even hundreds of different phytochemicals can act as multitarget therapies, which affect body function by potentially employing various mechanisms that have yet to be explored. In this study, we used network pharmacology to explore the possible bioactive compounds and molecular mechanisms of WJD employed in endometriosis treatment. These results could contribute to a better understanding of the associated molecular mechanisms employed by WJD against endometriosis.http://tcmspw.com/tcmsp.php). The drug feasibility of each candidate was assessed based on oral bioavailability (OB) and drug-likeness (DL) indices assigned from the TCMSP database. A high OB value is a critical criterion for selecting biologically active molecules as candidates in drug development. DL assessments are used in drug design for determining chemical suitability and predicting pharmacodynamic and pharmacokinetic properties. In our study, molecules with OB ≥ 30% and DL ≥ 0.18 were considered active compounds with potentially beneficial pharmacological effects. After obtaining these active compounds, we used the TCMSP database and the UniProt Knowledgebase (https://sparql.uniprot.org) to obtain the corresponding target protein and gene names, respectively.Information about the compounds from nine herbs and their protein targets was retrieved from the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform , Therapeutic Target Database (TTD) (http://db.idrblab.net/ttd/), and DrugBank (https://www.drugbank.ca). The overlapping genes between the bioactive compounds and the disease were identified and visualized using a Venn diagram.A comprehensive list of endometriosis-related genes was obtained by searching public databases, including DisGeNet (https://string-db.org) with the “Homo sapiens” setting and the confidence score > 0.9 to predict the interactions. The Cytoscape software 3.7.2 (http://www.cytoscape.org/) was used to visualize the network.The PPI network included information on the biological processes and molecular functions of cells. The identified overlapping target genes were introduced into the STRING network platform  is suitable for large-scale systematic analysis of molecular networks with interacting genes. To assess a likely mechanism of WJD in the treatment of endometriosis, the KEGG pathway enrichment analysis was performed via DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov). After sorting the results according to the P value, the top 30 significant pathway items were identified and presented via a bubble graph. Bigger and lower bubbles represented more significantly enriched pathway terms.The KEGG database (http://www.wwpdb.org), and the resulting macromolecule structure was preprocessed using PyRx 0.8 software. The molecular docking was achieved through Autodock Vina in the PyRx software. A semiempirical free energy calculation method was used to evaluate the receptor-ligand match.The bioactive composite crystal structures of the target proteins were retrieved from the Protein Data Bank . After removing 18 repetitive compounds, we entered the remaining compounds into the TCMSP database and identified 272 nonrepetitive target points. To obtain the gene names of these proteins, we used the UniProt Knowledgebase for the conversion, and then we identified 269 target sites. The numbers of predicted ingredients, bioactive compounds, and corresponding targets are listed in We identified 1,180 compounds of WJD in the TCMSP database, among which 171 met the screening criteria of OB ≥ 30% and DL ≥ 0.18  . MappingThe herbs-compounds-genes multinetwork included 8 herbs, 50 compounds, and 48 target genes . The disThe PPI network was obtained from the STRING database and visualized by the Cytoscape software. There were 45 nodes and 366 edges representing the target genes and the interactions between the targets, respectively . The meaP < 0.05 . Using the selected proteins with the top 5 active compounds , we performed molecular docking simulations. The docking results showed that these 4 targets could directly couple with the five bioactive compounds  that encoded the following proteins: tumor protein p53 (TP53), IL6, vascular endothelial growth factor A (VEGF-A), and estrogen receptor alpha (ERompounds . FurtherEndometriosis is a chronic, estrogen-dependent, inflammatory disease. Several theories have been proposed for its pathogenesis, including the induction theory, Mayer's coelomic metaplasia theory, and the most widely accepted Sampson's implantation theory . SampsonEndometriosis has a distinct immune microenvironment and endocrine dysfunction, which promotes sustained proliferation, vascularization, and impaired apoptosis of the endometrial foci –28. Our α, an estrogen receptor, is encoded by ESR1. Not only have the levels of ERα been shown to be elevated in ectopic lesions, but they also promote the survival of cells in endometrial tissues by promoting cell proliferation, maintaining vascularization, and enabling cells to evade apoptosis [α, and other cytokines.IL6, which is mainly secreted from macrophages and endometriotic cells, is involved in the inflammatory immune response. Moreover, it can inhibit apoptotic pathways, increase angiogenesis, that is, a process to develop new blood vessels and supply nutrients to growing ectopic tissues, and promote both cell adhesion and proliferation in endometriotic lesions . ERα, anpoptosis . TP53, apoptosis . VEGF-A,poptosis . Based oMoutan, Radix Achyranthis Bidentatae, and Radix Glycyrrhizae, has been previously shown to inhibit cell proliferation, induce cell apoptosis, counteract inflammation, and regulate estrogen, as well as progesterone receptors on endometriosis autoimplanted mouse models [Paeoniae Alba, Cortex Moutan, Radix Ginseng, Radix Achyranthis Bidentatae, and Radix Glycyrrhizae, exerts anti-inflammatory effects by suppressing the release of IL6, IL1β, IL18, and TNF-α [in vivo [Achyranthis Bidentatae, can decrease inflammatory and angiogenic hallmarks in a concentration-dependent manner [Angelicae Sinensis, Radix Paeoniae Alba, Radix Ginseng, and Radix Achyranthis Bidentatae. In many in vitro and in vivo studies, it has been shown to possess various bioactivities, such as immunomodulatory, antimicrobial, and anti-inflammatory activities [Angelicae Sinensis, Radix Ginseng, Radix Achyranthis Bidentatae, Rhizoma Ligustici, Cortex Moutan, Radix Paeoniae Alba, and Radix Glycyrrhizae. It has been reported that rats treated with stigmasterol have significantly suppressed the expression of proinflammatory mediators and increased the expression of anti-inflammatory cytokines [In this network pharmacology study, we established a herbs-compounds-genes multinetwork model using the Cytoscape software and identified 50 potentially bioactive compounds of WJD, including quercetin, kaempferol, wogonin, beta-sitosterol, and stigmasterol. Quercetin, an active ingredient common to Cortex e models , 33. Kaend TNF-α . It also[in vivo , 36. Wogt manner . Beta-sitivities . Stigmasytokines . Moreoveα has a high affinity for estrogen, and its function is mainly mediated through ERα, which is coupled with the “estrogen signaling pathway” [The results of the KEGG pathway analysis indicated that WJD might treat endometriosis via inflammatory- and endocrine-related signaling pathways, such as the “TNF signaling pathway” and the “estrogen signaling pathway.” Concentrations of TNF are elevated in the peritoneal fluid and serum of endometriosis patients, especially in the early stages of the disease , 41. An pathway” .in vitro and in vivo.In this study, network pharmacology was used to illustrate that WJD might treat endometriosis by regulating inflammation and/or the endocrine system. Our results provide guidance for further investigation of the mechanism, but there are still some limitations. Firstly, the acquisition of our active compounds and disease targets is based on existing databases that may not be comprehensive. For example, the active components of cinnamon in WJD did not meet the search filter criteria of the TCSMP database. Secondly, although we have identified possible related compounds and targets of WJD against endometriosis and performed molecular docking, it is still necessary to verify the involved mechanisms in vitro and in vivo experimental validation is needed to corroborate our research further.In this study, we employed a network pharmacology-based approach to identify the bioactive compounds of WJD and their potential targets in endometriosis. The results suggested that the bioactive compounds of WJD against endometriosis included 48 targeted genes, among which IL6 and ESR1 were closely related to inflammation and the endocrine system, respectively. The mechanisms employed by WJD against endometriosis were related to 65 signaling pathways, including inflammatory- and endocrine-related signaling pathways, such as the “TNF signaling pathway” and the “estrogen signaling pathway.” Thus, based on the network pharmacology analysis, we concluded that the mechanisms for treating endometriosis by WJD included the modulation of inflammation and/or the endocrine system, but


A high number of LC-based analytical methods for the quantification of HArg, in combination with the l-arginine (Arg)-related pathway metabolites, have been reported. However, these methods usually consider a limited panel of analytes. Thus, in order to achieve a comprehensive picture of the Arg metabolism, we described an improved targeted metabolomic approach based on a multiple reaction monitoring (MRM) mass spectrometry method for the simultaneous quantification of the Arg/nitric oxide (NO) pathway metabolites. This methodology was then employed to quantify the plasma concentrations of these analytes in a cohort of individuals with different grades/types of coronary artery disease (CAD) in order to increase knowledge about the role of HArg and its associated metabolites in the CV field. Our results showed that the MRM method here implemented is suitable for the simultaneous assessment of a wide panel of amino acids involved in the Arg/NO metabolic pathway in plasma samples from patients with CV disease. Further, our findings highlighted an impairment of the Arg/NO metabolic pathway, and suggest a sex-dependent regulation of this metabolic route.Clinical data indicate that low circulating  Continuous variables normally distributed were compared using the Student’s


To explore the mechanism of the Astragalus membranaceous (AM)-Angelica sinensis (AS) compound in the treatment of diabetic nephropathy (DN) we used network pharmacology and molecular docking. Screen the components and targets of the AM-AS compound in the TCMSP and the BATMAN-TCM, and establish a component-target interaction network by Cytoscape 3.7.2. After searching relevant targets of DN in related databases, the common targets of the AM-AS compound and DN were obtained by comparison. Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis were performed through David database. Molecular docking was performed by PyMoL2.3.0 and AutoDock Vina software. After screening, 142 main targets of the AM-AS compound in the treatment of DN have been identified. Target network was established and the topology of PPI network was analyzed. KEGG pathway enrichment analysis shows that these targets are related to apoptosis, oxidative stress, inflammation, insulin resistance, etc. Molecular docking shows that the target proteins have good combinations with the main active components of the AM-AS compound. AM-AS compound may treat DN by acting on VEGFA, TP53, IL-6, TNF, MARK1, etc., and regulate apoptosis, oxidative stress, inflammation, glucose, and lipid metabolism processes. The in vivo study results suggest that AM-AS compound can significantly reduce the FBG level of diabetic rats, increase the level of INS, improve renal functions, reduce urinary proteins, inhibit glycogen deposition, granulocyte infiltration and collagen fiber proliferation in renal tissue, and restrain the progress of DN. In vivo study combined with network pharmacology and molecular docking methods provides new ideas for the pathogenesis and treatments of DN. About 24 million people in the United States have diabetes, with type 2 diabetes(T2DM) accounting for the vast majority2. T2DM is a chronic multi-system disease. Long-term persistent hyperglycemia affects the microvascular system, causing diabetic nephropathy(DN), retinopathy, neuropathy, and other complications3. In a recent population-based study, the prevalence of DN was reported to be 30.9% in patients with diabetes, in which substandard blood glucose was an important determinant4. DN is one of the major causes of end-stage renal disease (ESRD), damage caused by diabetes can affect almost all structures of the kidney, and progress much faster than non-DN patients, and the long-term prognosis is bad. Clinical treatment focuses on controlling blood sugar and blood pressure, improving renal function, and reducing urine protein5. Traditional Chinese medicine(TCM) has good effects in improving diabetic symptoms, preventing and treating DN and other complications, and improving patients' quality of life. Our previous studies have found that the medicine for invigorating qi and promoting blood circulation can lower blood sugar and delay the progress of apoptosis caused by high glucose7.Recent epidemiological studies show that diabetes currently affects more than 440 million people worldwide. As of 2013, about 11 percent of China's population had diabetes, and a large portion remained undiagnosed8. The predictability is a characteristic of network pharmacology, which emphasizes the multi-channel regulation of signaling pathways, improves the therapeutic effect of drugs, reduces the toxic and side effects, and thus improves the success rate of clinical trials of new drugs and saves the cost of drug research and development9. Molecular docking is a method of drug design based on the characteristics of the receptor and the interaction between the receptor and the drug molecule, a theoretical simulation method for predicting binding patterns and affinity of molecular interactions. In recent years, molecular docking has become an important technology in the field of computer-aided drug research10. In this study, we use network pharmacology methods combined with molecular docking to establish the AM and AS compound-DN-targets interaction network to provide a basis for further exploration of pathogen and the interpretation of the mechanism of the AM-AS compound in treating DN.Network pharmacology is a new discipline based on the theory of systems biology, which analyzes the network of biological systems and selects specific signal nodes to design multi-target drug molecules11, http://tcmspw.com/tcmsp.php) is a unique Chinese herbal medicine system pharmacology platform, which highlights the role of system pharmacology in TCM. We used this database to obtain the relationship between the AM-AS compound, targets, and DN. We retrieved all the components of the AM-AS compound from the TCMSP, and the components’ oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 is used as the screening condition11. Enter the target name in the UniProt12 database (https://www.uniprot.org/). Standardize the genes and record. A Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine  is the first online bioinformatics analysis tool specially designed for the research of the molecular mechanism of TCM. BATMAN-TCM will first predict potential targets for each component, and then perform functional analyses on the above targets, AM and AS compound-targets-DN association network will be shown. These functions contribute to the understanding of the “multi-component, multi-target and multi-pathway” combinational therapeutic mechanism of the AM-AS compound and provide clues for the following experimental validation. We searched AM and AS in BATMAN-TCM. The search conditions were Score cutoff ≥ 20, P-value cutoff < 0.0514, and the components comply with OB ≥ 30% and DL ≥ 0.18. Standardize the genes and import all the above results into EXCEL. Merge predicted targets of the two databases, establish the AM and AS compound-component-targets database, and construct the network diagram by Cytoscape 3.7.2 software.The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSPhttp://ctdbase.org/), the Online Mendelian Inheritance in Man database , and the Human Gene Database  with the keyword of "diabetic nephropathy".Take the intersection with the AM-AS compound targets.Search disease targets in the Comparative Toxicogenomics Database . Predicted protein–protein interactions (PPI) were got with the condition of confidence score > 0.9. The above results were imported into Cytoscape 3.7.2 software for visualization, and the MCODE plug-in was used to screen important PPI network modules. The GO function  analysis and KEGG pathway enrichment of co-action targets were conducted by the BINGO plug-in and the David database(https://david.ncifcrf.gov/). P < 0.05 indicates significant differences16.We collected these targets and got the AM and AS compound-targets-DN interaction network. The core targets were imported into STRINGhttps://www.rcsb.org/) database and download the mol2 format file of the 3D structure of the core active component from the TCMSP database. DN clinical recommended drugs  were searched in DRUNGBANK17 (https://go.drugbank.com/). The SDF format files of the 2D structure of the drugs were downloaded from the DRUNGBANK database and were converted to the mol2 format file by Open Babel 3.1.1. Molecular docking with the main active components of the AM-AS compound recommended drugs, and core target proteins were performed by PyMoL 2.3.0 and AutoDock Vina18. The binding activity is evaluated by the lowest binding efficiency.The top 5 target proteins in the PPI network were selected for molecular docking. We download the PDB format file of the 3D structure of the targets in the RCSB PDB (Streptozotocin (STZ) was purchased from Sigma company, the SGLT-2 inhibitor(SGLT-2i) canagliflozin  was obtained from Janssen-Cilag S.p. A.. AM and AS granules were purchased from the Affiliated Hospital of the Shandong University of Traditional Chinese Medicine (specifications: 10 g/package). Rat insulin (INS) ELISA kit, rat β2-microglobulin (β2-MG) ELISA kit, and rat microalbuminuria (MAU) ELISA kit were purchased from Wuhan Huamei Biological Engineering Co., Ltd. Rat blood urea nitrogen (BUN) mensuration reagent kit, serum creatinine (Scr) mensuration reagent kit and glycosylated serum proteins (GSP) mensuration reagent kit were purchased from Changchun Huili biotech Co., Ltd. Ultrasonic cell crusher , automatic biochemical analyzer , enzyme label detector  and microscopes  were provided by the laboratory of Affiliated Hospital of Shandong University of Traditional Chinese Medicine.20 and was approved by the requirements of the Experimental Animal Ethics Committee of the Affiliated Hospital of Shandong University of Traditional Chinese Medicine(AWE-2019-007). The rats were divided randomly into 4 groups, 5 in each group, including blank control (BC) group, negative control (NC) group, astragalus membranaceous-angelica sinensis compound (AM-AS) group, and canagliflozin (SGLT-2i) group. The latter two are positive controls(PC). The rats of the BC group were fed with a normal diet, and the rests were fed with high-fat and high-sugar diets for 6 weeks. After fasting for 12 h, STZ (30 mg kg−1) was injected intraperitoneally. Rats with 3 consecutive times fasting glucose levels ≥ 16.7 mmol L−1 72 h after the injection were considered diabetic and were included in the study22.20 SPF male Sprague–Dawley (SD) rats were provided by Jinan Pengyue Experimental Animal Breeding Co., Ltd. The whole study followed the requirements of relevant guidelines−1 AM-AS compound solution (5.40 g kg−1 day) by stomach irrigation. The SGLT-2i group was given a canagliflozin solution, and the dose was converted according to the relevant guidelines24. During the medication period, the BC group was given a normal diet, and the rests were given high-fat and high-sugar diets. The general conditions of rats were observed daily, and the bodyweight (WB) and FBG were measured weekly. After 12 weeks of intragastric administration, the rats were killed and the renal tissues were separated quickly. Paraffin sections were made and were treated with HE staining and Masson staining. The pathological and ultrastructural morphological observations were carried out, and the degree of renal tissue damage, fibrous connective tissue hyperplasia, and inflammatory cell infiltration were compared. One-way ANOVA was used to analyze the data by IBM SPSS 19.0. P < 0.05 was considered statistically significant.The rats of each group were given intragastric administration on the second day after the successful establishment of the model. The AM-AS group was given 1 g mLAfter combining the results we searched in TCMSP and BATMAN-TCM, 208 components of the AM-AS compound were obtained Fig. . These c142 common potential targets of AM and AS compound-DN were obtained by further comparing and screening, which correspond to 18 active components  in the PPI network whose degree > 10 in the "AM and AS compound- DN-targets" interaction network. The core active components  were molecularly docked by AutoDock Vina, as shown in Table 3.0 Fig. .Table 3DP < 0.01). Compared with the NC group, the general conditions of the positive control groups (AM-AS group & SGLT-2i group) were significantly improved (P < 0.01). The comparison between the two groups showed that the effect of reducing FBG and interfering with WB in the SGLT-2i group was more significant than that in the AM-AS group (P < 0.05), as shown in Table The levels of FBG and WB relief of rats in the NC group were higher than those in the BC group (P < 0.01). Compared with the NC group, the AM-AS group has huge ameliorations in BUN, INS, β2-MG, and MAU (P < 0.01), and has many improvements in GSP and Scr (P < 0.05). All of the above was more significantly different in the SGLT-2i group than in the AM-AS group (P < 0.01), especially in reducing INS, β 2-MG, and MAU. Both positive-control groups have great effects on regulating BUN, GSP, and Scr, as shown in Tables NC group and BC group have apparent disparities in GSP, BUN, Scr, INS , β2-MG, and MAU  and excess in superficiality. Early lesions are qi and yin injuries, liver and kidney deficiency, blood stasis blocking. Then yin deficiency causes yang deficiency, spleen, and kidney deficiency, resulting in water retention and overflowing to the skin. The deficiency of qi and yang can make blood flow unfavorable and aggravate stasis. In the end-stage, the water stays and gathers due to the decline of the kidney yang. Critical symptoms occur as a result of damp toxins, which attack the stomach and heart. Therefore, spleen deficiency is the key pathogen of DN; lack of spirit qi is the root pathogen of DN, and blood stasis is involved in the whole course of DN.According to the clinical manifestations, diabetes mellitus (DM) is the same as “Xiaoke” in TCM, and the earliest records of etiology and pathogenesis can be traced back to "Jin Gui Yao Lue” records effective prescriptions such as “White Tiger Plus Ginseng” decoction and “Shenqi” pills, which have been highly praised by clinical physicians so far. "Tai Ping Sheng Hui Fang" contains dry Rehmannia prescription and “Shen Li Yuan” prescription. "Sheng Ji Zong Lu" proposed “Liu Wei Di Huang” pills, “Zi Cui” decoction, “Zuo Gui” decoction, and many other famous prescriptions. Zhang Xichun, a famous doctor in the Qing dynasty, reused AM and Chinese yam in the "Yuye” decoction, which meant to invigorate the qi and invigorate the spleen to cure diabetes.The principle of TCM treating DN is to " strengthening the body resistance to eliminate pathogenic factors" and "balance the yin and yang". In clinical treatment, the urgency of the syndromes and symptoms must be distinguished. Treat symptomatically in acute cases, and remove the primary disease in chronic cases. “26. When proteinuria occurs in DN, the activity of clotting factors in plasma is higher27. Therefore, we believe that DN occurs because of the long course of diabetes, leading to the deficiency of the spleen and kidneys, and the inability to transport water and dampness, which causes the overflow. Patients often have "blood stasis" symptoms, such as hyperlipidemia, hyperviscosity, microcirculation disorders, etc. Therefore, the treatment should be based on strengthening the spleen and kidney, replenishing spirit, and promoting blood circulation, and removing blood stasis. Treating both symptoms and primary disease can often receive a satisfactory curative effect. AM-AS compound is one of the representative Chinese herbal medicine pairs, which has a large number of theoretical foundations and wide clinical applications. Because it can not only form a party on its own but also can be used as a basic drug pairing prescription, it has been valued by the doctors of the past generations. The prescription principle of the AM-AS compound is the distribution theory of qi and blood, which includes nourishing qi and blood, replenishing qi with invigorating blood, and replenishing qi with promoting blood circulation. "Qi is the commander of blood, and blood is the mother of qi", which means that sufficient spleen qi can transport and transform the essence into the lungs, and sufficient lung qi can combine with heart qi to generate blood, which can spread throughout the body. That combination also implies the mutual use of yin and yang. Qi belongs to yang and blood belongs to yin. The mutual nourishment of yin and yang facilitates the vitality of qi and metaplasia of blood. AM-AS compound is one of the common clinical prescriptions. Therefore, we studied the AM-AS compound by network pharmacology method and performed preliminary verification by molecular docking.A large number of studies have concluded that the blood system of DM patients is usually hypercoagulable. Long-term hypercoagulability is an important cause of impaired renal function, and DM patients have higher incidences of thrombosisThrough the analysis of the AM and AS compound-DN-targets network, we found that the main active components of the AM-AS compound treating DN included quercitrin, kaemferol, isorhamnetin, βsitosterol, stigmasterol, etc. By topological analysis of the PPI network, we found that the core targets were TNF, IL-6, MAPK1, MAPK8, AKT1, JUN, etc. Quercetin mainly affects IL-6, VEGFA, and TP53. Kaempferol mainly affects TNF. GO analysis showed that the BP of AM-AS compound against DN mainly concentrated in the direction of apoptosis, positive regulation of RNA polymerase II promoter transcription, hypoxia response, inflammatory response, etc. The main pathways obtained by KEGG analysis include PI3K-Akt signaling pathway, TNF signaling pathway, NF-κB signaling pathway, MAPK signaling pathway, HIF-1 signaling pathway, FOXO signaling pathway, etc. 31 pathways contain IL-6, such as HIF-1 signaling pathway and insulin resistance pathway, etc. 104 target genes connect closely with IL-6. 33 pathways contain TP53, such as MAPK signaling pathway and P53 pathways, etc. 100 target genes connect closely with TP53. 13 pathways contain VEGFA, such as the PI3K-Akt signal pathway. 100 target genes are most closely related to VEGFA. 41 pathways contain TNF, such as the hepatitis B signaling pathway and cancer proteoglycan pathway. And 99 target genes are most closely related to TNF. Molecular docking showed that the core targets IL-6, TP53, VEGFA, TNF, and MARK1 had a certain binding activity with the main active components such as quercetin, kaempferol, and isorhamnetin. AM-AS compound may improve oxidative stress, inhibiting inflammation, and reducing insulin resistance to treat diabetic glomerular disease and renal fibrosis by acting on IL-6, TP53, VEGFA, TNF, and other targets to regulating TNF signaling pathway, insulin resistance, tumor necrosis factor signaling pathway, etc. The possibility of treating DN with the AM-AS compound was preliminarily verified by molecular docking.28. AM and its extract can lower blood sugar levels, increasing glomerular filtration rate, reducing urinary protein, preventing glomerular mesangial thickening29, and delaying the progression of DN32. AS compound help reduces the expression of NF-κB, transform growth factor-β1(TGF-β1), glycosylation end products (AGEs), the blood glucose and urinary albumin excretion rate. AS has a certain renal protection effect, such as regulating creatinine clearance rate in diabetic rats33. Quercetin can improve renal function by reducing oxidative stress, the overexpression of TGF-β1, and connective tissue growth factor (CTGF) in renal tissue of diabetic rats34. Kaempferol decreases the expression of tumor necrosis factor-α (TNF-α), interleukin-1β(IL-1β), and TGF-β1 in NRK-52E cells induced by high glucose. Kaempferol restrains the processes of oxidative stress, inflammatory response, and fibrosis35, promotes insulin release36. By inhibiting the NF-κB signaling pathway, isorhamnetin interferes the expression of downstream TNF-α, IL-1β, IL-6, intercellular adhesion molecule-1 (ICAM-1), and TGF-β1, thereby alleviating the inflammatory response and oxidative stress37, improving fasting blood glucose and lipid metabolism, and protecting kidney38.It was found that the AM-AS compound significantly reduces the level of insulin resistance and affects lipid metabolism in early atherosclerosis of diabetic rats40. VEGF interferes with angiogenesis and transformation of renal tubular epithelial cells to mesenchymal cells (EMT) by affecting PI3K/Akt signaling pathway41. TGF-β1 can stimulate cell proliferation and regulate ECM synthesis42, and the MAPK pathway can mediate the matrix deposition in the mesangial region. By blocking the TGF-β/MAPK/PPAR-γ pathway, the AM compound improves the blood glucose level, blood urea nitrogen (BUN), 24 h proteinuria, and other renal function indexes in diabetic rats44. HIF-1 plays a critical role in the prevention of early response to tissue damage caused by diabetes, and abnormal HIF-1 signaling pathways can accelerate kidney damage45. HIF can activate NF-κB46. The NF-κB signaling pathway is a transduction pathway of inflammatory signals, which is closely related to the development of DN47. Hypoxia can inhibit the activity of PHD1, leading to the activation of IKK, which in turn phosphorylates IκB, and leading to the transcriptional activation of downstream genes, such as inflammatory factors48. Our previous research found7 that the AM-AS compound can improve the related clinical symptoms of DN rats by regulating NF-κB and IL-6 related genes or pathways. Astragaloside IV combined with ferulic acid can intervene NF-κB, TNF-α pathway and improve the endothelial dysfunction of diabetic vascular disease. TNF signaling pathways are mainly related to immune function and inflammatory response. TNF-α can activate NF-κB, induce inflammatory cell infiltration, aggravate renal fibrosis, and eventually lead to renal injury48. It was found that the AM-AS compound could affect the concentration of TNF-α28, and their extracts inhibit the proliferation and fibrosis of glomerular mesangial cells (GMCs) in diabetic rats49. AM polysaccharides can reduce the levels of serum IL-6 and AngII in DM rats, and inhibit the expression of TGF-β1 and TNF-α50.PI3K/Akt signaling pathway is closely related to glucose metabolism and is one of the downstream pathways of insulin. Overactivation of the PI3K/Akt signaling pathway can lead to structural damage and functional abnormalities of podocytes, which cause proteinuriaThe results of in vivo study show that the AM-AS compound can inhibit collagen fiber proliferation and inflammation in diabetic rats. Combined with the results of molecular docking, we can speculate that AM-AS compound may act on key signal pathways such as TNF pathway, insulin resistance pathway, HIF-1 pathway, NF- kappa B pathway, and cAMP pathway through core targets such as TNF, IL-6, VEGFA, TP53, CASP3, JUN, AKT1 and so on. By this means, AM-AS compound can regulate the synthesis of NO, inhibit inflammatory reactions, oxidative stress, glycogen depositions, and collagen fiber formations, prevent abnormal morphologies of renal cells and dilatations of renal tubules, reduce urinary protein leakages, improve renal functions, and restraint renal functions damage caused by high glucose. The results of this study also suggest the accuracy of target prediction in network pharmacology.Through analysis of the main biologically active components of the AM-AS compound and their pharmacological mechanism, it is found that the AM-AS compound acts on multiple targets and proteins of multiple signal pathways, intervenes inflammation and oxidative stress delays the progression of DN. In the follow-up study, we plan to design animal pharmacological experiments in vivo and in vitro to conduct in-depth observations on the mechanism of the AM-AS compound in treating DN, to provide more references for its clinical application and development.


Cardiometabolic disorders are among the leading causes of mortality in the human population. Dietary polyphenols exert beneficial effects on cardiometabolic health in humans. Molecular mechanisms, however, are not completely understood. Aiming to conduct in-depth integrative bioinformatic analyses to elucidate molecular mechanisms underlying the protective effects of polyphenols on cardiometabolic health, we first conducted a systematic literature search to identify human intervention studies with polyphenols that demonstrate improvement of cardiometabolic risk factors in parallel with significant nutrigenomic effects. Applying the predefined inclusion criteria, we identified 58 differentially expressed genes at mRNA level and 5 miRNAs, analyzed in peripheral blood cells with RT-PCR methods. Subsequent integrative bioinformatic analyses demonstrated that polyphenols modulate genes that are mainly involved in the processes such as inflammation, lipid metabolism, and endothelial function. We also identified 37 transcription factors that are involved in the regulation of polyphenol modulated genes, including RELA/NFKB1, STAT1, JUN, or SIRT1. Integrative bioinformatic analysis of mRNA and miRNA-target pathways demonstrated several common enriched pathways that include MAPK signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, focal adhesion, or PPAR signaling pathway. These bioinformatic analyses represent a valuable source of information for the identification of molecular mechanisms underlying the beneficial health effects of polyphenols and potential target genes for future nutrigenetic studies. Polyphenols are plant secondary metabolites with important physiological functions ,2 and thEpidemiological studies have reported positive effects of polyphenol intake on cardiometabolic health in humans ,10. ThesAlthough there are a lot of studies pointing to the direction of beneficial effects of polyphenols on cardiometabolic health in humans, as yet no clear molecular mechanisms have been clearly highlighted. Several studies have shown that diets, foods, and drinks  can exert important nutrigenomic modifications which present important molecular mechanisms underlying their health properties ,22. NotwIt is particularly difficult to investigate molecular mechanisms underlying positive cardiometabolic effects of polyphenols in humans, and therefore, the number of such studies is limited. Recruitment of participants with similar baseline characteristics, compliance with the intervention and participants’ follow-up in long-term studies, are all very challenging. Availability of samples for analyses is another limiting factor in human intervention studies, most of them being conducted using blood samples for analysis of gene expression, and only a small number of studies included skeletal muscle or adipose tissue ,29. AlthTherefore, we conducted a systematic literature search aiming to identify human intervention studies with polyphenols that demonstrated significant modulation in gene expression in parallel with positive effect/s on cardiometabolic risk factors. In our study, we focused only on studies that adopted a targeted approach, i.e., analyzed changes in the expression of several target mRNAs or miRNAs with RT-PCR methods. We then applied integrative bioinformatic analyses of identified nutrigenomic effects, to gain a better understanding of the overall molecular mechanisms of polyphenols in humans underlying their health properties.All literature relevant to the effect of polyphenols on gene expression and cardiometabolic endpoints in human trials was searched and obtained using the Preferred Reporting Items for Systematic Reviews (PRISMA) statement guidelines with a predetermined search strategy . A comprInclusion criteria for data extraction were as follows: human intervention studies of cardiometabolic disease or cardiometabolic risk factors where polyphenols were used for intervention, and modulation of gene expression was studied at mRNA and/or miRNA level, which was analyzed with RT-PCR methods. Furthermore, in order to be included in our analysis, the publications should have reported at least one beneficial cardiometabolic outcome, such as: improved plasma lipid status , improved oral glucose tolerance test, decreased fasting glucose, glycated hemoglobin, insulin resistance, blood pressure, body weight, waist circumference, systemic inflammation , or decreased oxidative stress. Studies reporting an unfavorable cardiometabolic outcome, for example, increased LDL-cholesterol, were excluded from our analysis. In addition, studies that did not include a control of polyphenol intervention, or studies of co-interventions , were also excluded.p < 0.05) were extracted from the eligible papers, and subsequently subjected to bioinformatic analyses. Extracted data were cross-checked by two participants. In case of doubts or disagreement, a third participant was consulted.A template for data extraction was designed specifically for this study. The template was pilot tested to verify the accuracy of the data extraction. The final version of the template was distributed among the participants. Extracted data include: details about the paper , information about the study population , information about the intervention , study design, information about the cardiometabolic outcomes (including both studied and significantly modulated), and information about gene expression . Only genes that were significantly modulated by the intervention  [p-value computation)—two-sided; method to adjust p-values—Benjamini-Yekutieli; significance level—0.05. All supported genes in the NCBI database were taken as a reference.Pathways enrichment analyses were conducted using GeneTrail2 (ry 2020) , versionhttps://cytoscape.org/, accessed on 1 June 2020) [Interactions between functional groups of genes were analyzed with Cytoscape software  , using tne 2020) , connectne 2020) .https://string-db.org/, accessed on 25 January 2020) [Protein-protein interactions (PPIs) were analyzed using the database STRING (ry 2020) , versionhttps://amp.pharm.mssm.edu/Enrichr/, accessed on 25 January 2020) [https://cytoscape.org/, accessed on 1 June 2020) [Transcription factors that regulate the expression of polyphenol modulated genes were identified using Enrichr (ry 2020) ,39, as ary 2020) . Interacne 2020) .http://www.mirbase.org/, accessed on 8 February 2020) [https://syngoportal.org/, accessed on 8 February 2020) [http://www.interactivenn.net/, accessed on 8 February 2020) [https://cytoscape.org/, accessed on 1 June 2020) [http://metascape.org, accessed on 3 April 2020; the option “Multiple Gene List”) [http://circos.ca/, accessed on 3 April 2020) [To identify mRNAs regulated by polyphenol modulated miRNAs, i.e., predicted miRNA targets, we used miRBase (ry 2020) , as a plry 2020) . Interacry 2020)  was usedne 2020) . To compe List”) , where til 2020) . Enrichehttps://cytoscape.org/, accessed on 1 June 2020) [https://github.com/mrdwab/splitstackshape, accessed on 16 June 2020), data.table , dplyr , and string . Pathway networks were built separately for pathways enriched in each category and pathways considering all categories’ components together in a global pathway enrichment analysis. To obtain the pathways with the highest degree (number of connections of one node to other nodes), the Cytoscape Network Analyzer application was used .To compare KEGG pathways associated with mRNAs extracted from the literature and predicted miRNA targets, the enriched pathways obtained in our previous steps were used to build a network of pathways; two pathways were considered interconnected where at least one of the mRNAs or miRNA targets involved in them are common to both. Networks were constructed and visualized using Cytoscape software  . Data prhttps://www.omicsnet.ca/, accessed on 10 February 2020) [https://www.genecards.org/, accessed on 22 May 2020) [https://www.uniprot.org/, accessed on 22 May 2020) [For integrative analysis of extracted mRNAs, their associated TFs, and extracted miRNAs, we used the 3D-layer option in the bioinformatic tool OmicsNet (ry 2020) ,48. Offiay 2020) . Where aay 2020) .A comprehensive search on PubMed and Web of Science, conducted in July 2018, with an update in November 2019, resulted in 8678 documents. After removal of duplicates, and using “Human” and “RCT” and “Clinical study” and “Clinical trial” and “Controlled Clinical Trial” and “Multicenter Study” filters, this number dropped to 465 manuscripts, which were further screened for eligibility. Based on titles and abstracts, 89 papers were selected for data extraction and distributed among the participants . After dAll studies used peripheral blood mononuclear cells (PBMCs), except one in which white blood cells were used, as biological material for analysis of modulations in gene expression . PolypheCCL20, CCL22, CCL3, CCR1, CCR5, CCR7, CD40, CD40LG, CX3CR1, CXCL10, CXCL16, CXCL6, CXCL9, CXCR1, CXCR2, CXCR3, CXCR6, IL1B, IL1R2, IL23A, IL6, IL7R, TNF); chemokine signaling pathway ; cell adhesion molecules ; toll-like receptor signaling pathway ; adipocytokine signaling pathway ; TNF signaling pathway ; PPAR signaling pathway ; NF-kappa B signaling pathway ; PI3K-Akt signaling pathway ; nuclear receptors in lipid metabolism and toxicity ; ABC transporters ; hematopoietic cell lineage ; selective expression of chemokine receptors during T-cell polarization .To better understand the biological meaning of genes extracted from the literature, we first conducted bioinformatic analyses to identify pathways significantly associated with polyphenol modulated genes. Using GeneTrail2 as a platform to access KEGG and BioCarta databases, we identified N = 71 KEGG and N = 42 BioCarta pathways that are significantly associated with extracted genes, modulated at the mRNA level. Among KEGG pathways retrieved with this analysis, N = 32 pathways are related to cellular processes, whereas the others are related to various diseases. Among the top 25 BioCarta pathways, N = 24 are related to cellular processes. A deeper insight into KEGG and BioCarta pathways related to cellular processes demonstrated that these pathways are mainly involved in endothelial function, cell signaling, inflammation, and lipid metabolism, as depicted in TNF and NFKBIA are shared among at least three of the identified clusters of pathways, depicted in different colors in Analysis of interactions between functional groups of differentially expressed genes was conducted using the applications ClueGO and CluePedia in Cytoscape software, calculating not only the interactions between polyphenol-affected pathways, but also the role and involvement of modulated genes within the network. Similar to pathways enrichment analyses, disease-related pathways were excluded from the graphical presentation . AnalysiFurthermore, we performed protein-protein interactions analysis for proteins encoded by polyphenol modulated mRNA transcripts, using the bioinformatic tool STRING. This analysis also revealed N = 15 neighboring proteins, ten of which were within the first shell of interactions, and five within the second shell. We also used the functionality of STRING for the organization of proteins in functionally differentiated clusters, which allows better interpretation of extracted data. For our set of differentially expressed genes, three well-defined protein clusters are clearly distinctive A, mainlyp-value < 0.05). The top 5 transcription factors retrieved with this analysis include: RELA and NFKB1 with more than 15 hits each, STAT1 with 9 hits, SPI1 and CEBPD . Some of these pathways are associated with cellular processes, whereas others are related to various diseases. A deeper insight into the top 60 pathways associated with cellular processes , Wnt signaling pathway , Ras signaling pathway , or PI3K-Akt signaling pathway .We also conducted bioinformatic analysis of pathways that are significantly associated with the predicted miRNA targets. To this aim, targets of all 5 miRNAs were taken together, and duplicates were removed. In that way, 720 targets were identified and analyzed with GeneTrail2 for KEGG and BioCarta pathways. We identified in total N = 86 KEGG and N = 21 BioCarta pathways that are significantly associated with miRNA targets , focal adhesion , cell adhesion molecules , gap junction , or adherens junction . Interestingly, some of the top pathways are also related to the function of the nervous system such as: axon guidance , or glutamatergic synapse .Some of the pathways are involved in the regulation of endothelial function, such as: regulation of actin cytoskeleton  but also with 6 genes  that are targets of miRNAs. Among these genes, OLR1 was identified both as differentially expressed and target of hsa-miR-21-5p, suggesting the polyphenols by modulating expression of this miRNA can affect level of mRNA of OLR1  was grouped and shown in  of OLR1 B. This iTo visualize interactions between polyphenol modulated genes (N = 58) and miRNAs (N = 5), as well as the predicted transcription factors (N = 37) that regulate the expression of polyphenol modulated genes, we used the bioinformatic tool OmicsNet. PPIs of proteins that are coded by polyphenol modulated genes are retrieved using the STRING database, and are presented in the middle of the 3D-layer presentation .Transcription factors, retrieved using the TRRUST database, are presented above the PPIs, in green color. Modulated miRNAs by polyphenols are presented in blue color. This study presents several limitations. We only used genomic data available from studies that used targeted gene expression analysis. There are several studies that have used untargeted genomic analysis, and provide significant information on genomic modifications by plant food bioactives. However, because of the large difference in number of differentially expressed genes identified due to approaches used, we did not include studies which used untargeted approaches. Moreover, this systematic analysis only included studies with positive effects on cardiometabolic endpoint analysis, however there are also studies that reported changes in the expression of specific genes related to other health effects.Cardiometabolic disorders are among the leading causes of mortality in human population and therefore attract much interest for finding effective solutions for prevention and treatment. Since diet and lifestyle are important factors influencing the onset and progression of cardiometabolic disorders, preventive measures are largely directed towards their modification. In terms of diet, polyphenols have an important role as plant food bioactives with protective effects. Namely, numerous epidemiological and human intervention studies indicate that polyphenols generally have positive effects on human cardiometabolic health ,12. MoreTNF, NFKBIA, PPARG, and CCR7. Among transcription factors, the most prominent role is demonstrated for RELA/NFKB1, STAT1, and JUN, but SIRT1, or KLF4 are also significantly associated. Most of these genes and molecules are important mediators of inflammatory response, which is the major underlying mechanism of cardiometabolic disorders [Bioinformatic analyses of polyphenol modulated mRNAs demonstrated that these genes are mainly involved in processes such as inflammation, lipid metabolism and endothelial function. Network analyses pinpointed several genes with central positions within the functional clusters and the highest number of interactions, such as isorders . Indeed,isorders , furtherisorders ,62. The isorders ,64. The isorders . This obisorders . It has isorders . The modisorders . These cisorders . These risorders ,70. Ther+ dependent deacetylase, which was identified in our bioinformatic analysis among the TFs significantly involved in the regulation of polyphenol modulated genes. In particular, SIRT1 has the ability to deacetylate the p65 subunit of NF-kappa B, thus inhibiting its transcriptional activity [LOX-1  as significantly modulated by polyphenols within both mRNAs extracted from the literature and predicted miRNA targets retrieved with our bioinformatic analyses, which strongly indicates its importance in the atheroprotective effects of polyphenols. Besides resveratrol that has been extensively studied as a SIRT1 activator, other SIRT1 activators and NAD+ boosting compounds also demonstrate promising effects on cardiometabolic health [The activity of NF-kappa B is also modulated by SIRT1, an NADactivity , which ractivity ,73. SIRTactivity . In addiactivity ,76. The activity . It is oc health .In addition to their ability to modulate the expression of protein-coding genes, polyphenols are also capable of modulating miRNA expression, which has also been demonstrated in our systematic literature search. Namely, we have identified miRNAs that are involved in inflammation associated with cardiometabolic disorders as significantly modulated with polyphenol intervention. For example, it has been demonstrated that grape polyphenols enriched with resveratrol significantly upregulate miR-21 and miR-181b in PBMCs of diabetic men with hypertension and coronary artery disease, which was accompanied with beneficial cardiometabolic outcomes . These rOpposite to miR-21 and miR-181b, the upregulation of miR-34a is associated with impaired cardiometabolic health. For example, it has been reported that circulating miR-34a is increased in hypertensive subjects , as wellPPP2R3A, expressed also in blood cells, was found to promote activation of NF-kappa B via coupling to Gα12/13, the small GTPase protein RhoA and RhoA-activated kinase, mechanism which increases expression of adhesion molecules and inflammatory mediators [GLUL, SLC1A2, HOMER1, or GRIN2D were observed to be expressed in immune cells ). Expression of some of these genes has been observed to be affected in patients with neurological disorders. For example, HOMER1 gene was observed to be expressed in patients with Alzheimer’s diseases , suggesting that polyphenols could also affect neurological disorders. Indeed, it has been suggested that polyphenol consumption could be involved in prevention of neurodegenerative disorders and improvement of cognitive function [Bioinformatic analyses demonstrated that identified miRNA targets play a role in different cellular functions and cell signaling. Among the pathways identified are those regulating actin cytoskeleton, focal adhesion, adherens, and gap junction, actin organization and cell adhesions. The adhesion of immune cells to vascular endothelium and their trans-endothelial migration are controlled by the combined action of these pathways. The permeability-regulating factors act through small GTPases that regulate the architecture of the cytoskeleton, which impacts the morphology of the cell and cell–cell junctions and facilitates cell transmigration . Proatheediators . Other gfunction ,95.In summary, this systematic literature search and the subsequent integrative bioinformatic analyses allowed us to add new value to the existing data. Applied bioinformatic methods transformed the list of polyphenols modulated genes into valuable sources of information for a better understanding of some of the molecular mechanisms of action of polyphenols, but also toward the identification of potential target genes for future nutrigenetic studies.