Background and Objectives: This study aims to illustrate the mechanisms underlying the therapeutic effect of Icariin after myocardial infarction (MI). Materials and Methods: Based on the network pharmacology strategy, we predict the therapeutic targets of Icariin against MI and investigate the pharmacological molecular mechanisms. A topological network was created. Biological process and Kyoto Encyclopedia of Genes and Genomes pathway enrichment were also performed. We also conducted the molecular docking analysis to stimulate the component–target interaction further and validate the direct bind effect. Results: Network pharmacology analysis identified 61 candidate genes related to the therapeutic effect of Icariin against MI. EGFR, AKT1, TP53, JUN, ESR1, PTGS2, TNF, RELA, HSP90AA1, and BCL2L1 were identified as hub genes. The biological processes of the candidate targets were significantly involved in the reactive oxygen species metabolic process, response to hypoxia, response to decreased oxygen levels, response to oxidative stress, regulation of reactive oxygen species metabolic process, and so forth. Overall, biological process enrichment analysis indicated that the protective effect of Icariin against MI might be associated with oxidative stress. Moreover, the pathway analysis showed that the candidate targets were closely associated with lipid and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, etc. We identified the conformation with the lowest affinity score as the docking conformation. The simulated molecular docking was displayed to illustrate the topical details of the binding sites between Icariin and TNF protein. Conclusions: This study provides an overview of the mechanisms underlying the protective effect of Icariin against MI. Myocardial infarction (MI) is a common ischemia heart disease caused by the obstructed arterial inflow to the heart and subsequent myocardium impairment ,2. CurreEpimedii Herba, also referred to as Horny Goat Weed, is a traditional Chinese herbal medicine . EpimediNetwork pharmacology is an integrative computational method that integrates systematic medicine with information science and establishes a protein–compound and disease–gene network . Combinihttps://pubchem.ncbi.nlm.nih.gov/, accessed on 14 October 2022) is a free online database of chemical information created by the National Institutes of Health. It provides a repository of over 39 million chemical compounds with associated data such as chemical structures, 3D models, bioactivities, reactions, and spectra. Compounds can be searched and visualized using the PubChem Structure Search and PubChem Compound Search tools, and data can be downloaded in several different file formats. PubChem also provides access to related resources, such as databases of potential drug targets, gene expression data, and toxicity profiles. We acquire Icariin’s 2D Structure and Canonical SMILES (Simplified Molecular Input Line Entry System) from the PubChem database using the keyword “Icariin”. Canonical SMILES is a molecular representation format used to describe the structure of a chemical compound. It is a text-based representation of a molecular structure, using a string of characters to represent the bonds and atoms in a molecule. It is a standardized system which is used to uniquely identify molecules and aid in searching databases.PubChem  [stitch.embl.de, accessed on 15 October 2022) [The predictive targets of icariin were harvested from the Swiss Target Prediction er 2022)  database  databaser 2022) . It is adb.idrblab.net/ttd, accessed on 15 October 2022) [www.disgenet.org, accessed on 15 October 2022) [Moreover, target genes related to MI were collected with the keyword “myocardial infarction” in TTD (er 2022) , DrugBaner 2022) , and CTDer 2022)  databaseer 2022) . It conter 2022) . It is aer 2022) . It provwww.uniprot.org, accessed on 15 October 2022) [After acquiring target genes, we used the UniProt (er 2022)  databasehttp://string-db.org, accessed on 15 October 2022) [STRING (er 2022)  is a proer 2022) . The dater 2022) . We inpuer 2022) .An analyzer (a plug-in of Cytoscape) was utilized in analyzing topological parameters of mean and maximum degrees of freedom in the PPI network. Further, based on mixed character calculation, we identified the top 10 hub genes using the Cytoscape plug-in software “cytoHubba”.To reveal the biological function of the target genes, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. GO is a controlled vocabulary of biological terms used to describe gene products in any organism. The GO vocabulary is used to classify genes and gene products into three distinct categories: molecular function, biological process, and cellular component. GO is used to aid in the interpretation of gene expression data, to provide insight into the underlying molecular mechanisms of a given phenotype, and to identify network and pathway relationships between genes and gene products. The KEGG pathway database is an online resource that provides comprehensive information on molecular-level pathways, networks and interactions in various organisms, including humans. It contains manually curated information on metabolic, genetic, and regulatory networks, as well as on the evolution and development of biological systems. The information is organized into a series of pathways and maps that connect genes and proteins to their metabolic, regulatory, and signaling functions. KEGG pathways are used to analyze and visualize large-scale omics data, and to infer underlying biological networks and functions. The enriched biological processes and KEGG signaling pathways related to the candidate targets of Icariin against MI were visualized. We used default parameters in the study unless otherwise specified.Computational molecular docking is a computational technique used to predict the binding affinity of a given molecule to a target protein or ligand . Since ihttps://www.rcsb.org/, accessed on 15 October 2022). The AutoDock Tool software was applied to pre-process the protein structure by removing the water molecules and adding the nonpolar hydrogen atoms. The 2D structure of Icariin was obtained from PubChem, transformed by the Open Babel software, and saved in the PDBQT format as a ligand via the AutoDock software. Next, we used the Autodock Vina software to predict the molecular docking site, and the affinity score (binding energy) of each conformation pair was calculated. The lower affinity score indicates a stronger bond. We identified the conformation with the lowest affinity score as the docking conformation. Finally, the conformation between Icariin and the potential target was visualized by PyMOL software.We performed the molecular docking analysis to stimulate the component–target interaction further and validate the direct bind effect. We obtained the three-dimensional structure of the potential hub gene (treated as a receptor) from the RCSB PDB database OC2=C(OC3=C(C2=O)C(=CC(=C3CC=C(C)C)OC4C(C(C(C(O4)CO)O)O)O)O)C5=CC=C(C=C5)OC)O)O)O. The 2D Structure of Icariin is illustrated in PRKCE, XDH, ADRA2C, NOS2, PRKCZ, SLCO1B3, ALOX5, CYP1A2, BACE1, PRKCB, SLCO2B1, EGFR, IKBKB, ADORA1, ALDH2, IL2, BCHE, BCL2, OPRD1, ADRA2A, PDE5A, F7, KCNH2, F10, LDHB, CYP1A1, BCL2L1, TNNI3, ADORA3, HSP90AB1, RELA, PRKCD, NOS3, SLC29A1, ABCB1, PLG, SERPINE1, CYP19A1, TP53, TNF, DRD2, LDHA, AKT1, PRKACA, F2, PTGS2, SQLE, KLK1, NFKB1, ABCC1, NOX4, BAD, ESR1, SCARB1, JUN, ACHE, PRKCA, CYP1B1, APP, RPS6KA3, HSP90AA1.After standardization and duplicate removal, 940 MI-related targets and 109 Icariin targets were obtained. The detailed MI-related genes and Icariin target genes are provided in EGFR, AKT1, TP53, JUN, ESR1, PTGS2, TNF, RELA, HSP90AA1, BCL2L1 . After pre-processing, we performed molecular docking between Icariin and TNF protein. Conformation with high binding energy  was considered a stable structure. We identified the conformation with the lowest affinity score as the docking conformation. The simulated molecular docking is displayed in Based on the integration of the results from the PPI network, we selected the TNF as the potential target in molecular docking. The structure of the human protein encoded by the MI is a clinical event characterized by the acute reduction in or cessation of blood flow to a portion of the heart muscle, leading to ischemic injury and cell death. It is typically caused by the occlusion of a coronary artery by a thrombus or embolus, which is usually formed on top of a ruptured vulnerable plaque. The incidence of MI has been declining, but it remains a leading cause of death and disability worldwide ,31. The Epimedii Herba is a perennial herb native to China and other parts of Asia . It beloEGFR, AKT1, TP53, JUN, ESR1, PTGS2, TNF, RELA, HSP90AA1, BCL2L1. The biological process and KEGG pathway enrichment analysis suggested that the protective effect of Icariin against MI might be associated with inhibited oxidative stress.Network pharmacology is an interdisciplinary field that seeks to understand the complex interactions between drugs, biological pathways, and disease mechanisms . This is-/- mice [In MI, the lack of oxygen and nutrients delivered to the heart tissue leads to cellular damage and death, resulting in the formation of an infarct. Many pathological processes were involved in myocardial infarction, including platelet activation and aggregation, ischemia, inflammation, necrosis, and so forth. Importantly, ROS plays a key role in contributing to the development of many cardiovascular diseases. ROS are highly reactive molecules that are produced by cells as a byproduct of normal cellular metabolism and are also generated by various sources of oxidative stress, such as hypoxia, ischemia, and inflammation. In the development of MI, ROS contribute to the injury and death of heart muscle cells through multiple mechanisms. One of the key mechanisms by which ROS contribute to MI is through the oxidative modification of proteins and lipids, leading to cellular dysfunction and death. ROS can also induce the activation of various signaling pathways that contribute to the development of an inflammatory response, further exacerbating the injury to heart muscle cells. Our results indicated that the potential antioxidative effect of Icariin might benefit MI patients, probably from the polyphenol structure similar to other antioxidant properties. Zhao and colleagues  used a c-/- mice ,45, rats-/- mice , and rab-/- mice .TNF, tumor necrosis factor, is a pro-inflammatory cytokine that plays a crucial role in the pathological processes involved in cardiovascular diseases ,49. The Based on the high-cholesterol diet-induced atherosclerosis rat model, Hu et al.  reportedThis study provides preliminary evidence for Icariin administration to treat MI. Further research is required to demonstrate the clinical benefit of Icariin on the development and progress of MI.


Major depressive disorder (MDD) is a highly heterogeneous psychiatric disorder. The pathogenesis of MDD remained unclear, and it may be associated with exposure to different stressors. Most previous studies have focused on molecular changes in a single stress-induced depression model, which limited the identification of the pathogenesis of MDD. The depressive-like behaviors were induced by four well-validated stress models in rats, including chronic unpredictable mild stress, learned helplessness stress, chronic restraint stress and social defeat stress. We applied proteomic and metabolomic to investigate molecular changes in the hippocampus of those four models and revealed 529 proteins and 98 metabolites. Ingenuity Pathways Analysis (IPA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified differentially regulated canonical pathways, and then we presented a schematic model that simulates AKT and MAPK signaling pathways network and their interactions and revealed the cascade reactions. Further, the western blot confirmed that p-AKT, p-ERK12, GluA1, p-MEK1, p-MEK2, p-P38, Syn1, and TrkB, which were changed in at least one depression model. Importantly, p-AKT, p-ERK12, p-MEK1 and p-P38 were identified as common alterations in four depression models. The molecular level changes caused by different stressors may be dramatically different, and even opposite, between four depression models. However, the different molecular alterations converge on a common AKT and MAPK molecular pathway. Further studies of these pathways could contribute to a better understanding of the pathogenesis of depression, with the ultimate goal of helping to develop or select more effective treatment strategies for MDD. Major depressive disorder (MDD) is the leading cause of disability globally, with over 300 million people suffering from depression worldwide , and it Stress-induced depression models have been widely used and developed as an important tool for exploring the complex pathogenesis of MDD for over 30 years , 8. TherThe hippocampus is regarded as the key stress-responsive brain region involved in memory, learning and mood regulation, and plays an important role in the pathogenesis of depression . HippocaRecent technological advances and efforts in scientific discovery have acquired an in-depth understanding of the molecular mechanisms of depression. Due to the expansion of ‘omics’ technologies, hundreds of putative molecular proteins and metabolites have been discovered whose presence  could indicate depression . MeanwhiHowever, most studies have typically focused on a single stress-induced depression model, and combination of different models can eventually decrease the etiological heterogeneity, and come closer to the clinical situation than a single, or even highly sophisticated model . Thus, tA flowchart of the molecular profiling methods was shown in Supplementary Fig. The animals were used as we published previously study . One hunThe paradigm of chronic unpredictable mild stress (CUMS), chronic restraint stress (CRS), social defeat (SD) and learned helplessness (LH) were reported in our previous studies , 28, andp-value < 0.05 and at least a 1.2-fold change (> 1.20 or < 0.83) relative to the control group. To obtain an overview of the differentially expressed proteins, they were functionally annotated according to biological processes via Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis using DAVID 6.8 (https://david.ncifcrf.gov). KEGG pathway analysis was applied to identify the significantly altered canonical pathways of differentially expressed proteins. In the metabolomic analysis, the details of non-targeted gas chromatography-mass spectrometry (GC-MS) analysis were reported in our previous studies [http://www.ingenuity.com) to summarize the schematic model from the findings of proteomic and metabolic profiling.The methods of sample preparation for iTRAQ-based proteomics analysis were reported in our previous studies . The rig studies . MetabolHippocampal tissue was lysed in RIPA buffer with a protease inhibitor cocktail . After the KEGG and IPA pathways analysis, we screened key proteins in the pathway related to pathogenesis of depression for further verification. The protein levels of 11 proteins were measured by western blot in hippocampus including protein kinase B (AKT)/ phosphor-AKT, extracellular signal-regulated kinase1/2 (ERK 1/2)/ phosphor-ERK1/2, glutamate receptor 1 (GluA1), mechanistic target of rapamycin (mTOR) and phosphor-mTOR, dual specificity mitogen-activated protein kinase mek-1 (MEK1) and phosphor-MEK1, dual specificity mitogen-activated protein kinase mek-2 (MEK2) and phosphor-MEK2, mitogen-activated protein kinase 13 (P38) and phosphor-P38, ribosomal protein S6 kinase (P70S6K) and phosphor-P70S6K, postsynaptic density protein-95 (PSD95) and phosphor-PSD95, synapsin-1 (Syn1), tropomyosin-related kinase B (TrkB), GAPDH and beta Tubulin.The proteins were separated on 7.5–10% SDS gels and then transferred to polyvinylidene difluoride membranes . After blocking in 5% skimmed milk powder for 2 h, incubate the membranes with the primary antibody at 4 °C overnight. After washing with tris buffered saline containing Tween 20 , the membranes were incubated with the appropriate concentration of secondary antibody -HPR Conjugate 1706515, Bio-Rad, California, USA) was placed at room temperature for 2 h. The signals were detected with ECL kit , and analyzed with Quantity One software  –35. The p-value < 0.05 was considered to be statistically significant.The mean ± SEM was used to represent the results of each behavioral test. The results of behavioral tests and western blot protein analysis were compared by SPSS 21.0  using independent two-sample Student’s t-tests or non-parametric Mann-Whitney U-tests as appropriate. A Behavioral results showed in Supplementary Fig. A total of 4950 proteins were identified by iTRAQ-based proteomic profiling of hippocampus between stress and control groups in four depression models. The proteomic results of CUMS and SD models were published in our previous studies , 36. BasKEGG pathway analysis of 529 differentially expressed proteins in these four depressive-like models identified a total of 24 signaling pathways, of which 16 were significantly different (P < 0.05). At the same time, IPA pathway analysis was performed and a total of 422 pathways were identified, 25 of which were significantly different  in the AKT and MAPK signaling pathways were significantly altered in at least one depression model, while three proteins  in the mTOR signaling pathway were not altered. Therefore, AKT and MAPK signaling pathways were considered pathways of interest. Previous studies found that CUMS, CRS and LH models of depression reduced the AKT signaling pathway in the hippocampus of mice and that CUMS activated the MAPK signaling pathway –40. MoreAlthough different paradigms had been used to study stress coping, such as genetic, inheritance and environmental, there were commonalities and differences across models , 45. ForOur results revealed differential proteins changes in four depression models. We found inconsistent changes in p-ERK12, GluA1, TrkB, Syn1, and p-P38 proteins among the four depression models. In detail, ERK was coupled to a number of neurotransmitter receptors, including serotonin, adrenergic, dopamine and glutamate receptors, which were highly associated with depression . ChronicOn the other hand, we found that the expression of p-MEK1 and p-AKT were consistently expressed in four depression models, down-regulated in the CUMS, LH and SD models and up-regulated in the CRS model. Moreover, the p-MEK2 was down-regulated in CUMS and up-regulated in CRS models. The chronic restraint stress may inhibit the response to a second hit of restraint stress through up-regulated MEK and AKT signaling pathways . HoweverIn addition, multi-omics analysis also revealed that differentially expressed metabolites  commonly found in the hippocampus of four depression models , indicatDiverse molecular alterations could converge in similar AKT and MAPK signaling pathways. AKT was a serine/threonine protein kinase that played a central role in the signaling network involving MAPK and mTOR, and which regulates multiple cellular processes including glucose metabolism, apoptosis, cell proliferation, transcription and cell migration . DepressThere were several limitations in this study. First, only a number of classic molecular of depression-related proteins involve in AKT, MAPK and mTOR signaling pathways were detected by western blot, with no evidence of functional effects of cell transduction. Future research should incorporate a broader analysis including the other altered proteins and pathways. Second, although most depression model studies have been conducted with male rats, this would cause a gender bias . FurtherIn summary, we integrated proteomic and metabolomic analysis of multiple stress-induced depression models in the hippocampus of rats, which were mainly involved in AKT and MAPK signaling pathways. Then, nine proteins in AKT and MAPK pathways were identified to be altered by western blot. Finally, AKT and MAPK pathways molecular network were demonstrated when combining with altered metabolites in hippocampus. These findings advance our understanding of the potential pathophysiology and heterogeneity of depression as manifested in the hippocampus, and it could facilitate the development of personalized medicine based on these novel therapeutic targets for depression.Supplementary Materials


Eriodictyol occurs naturally in a variety of fruits and vegetables, and has drawn significant attention for its potential health benefits. This study aims to look into the effects of eriodictyol on acute liver injury (ALI) induced by LPS/D-GalN and elucidate its potential molecular biological mechanisms. A total of 47 targets were predicted for the treatment of ALI with eriodictyol, and the PI3K/AKT signaling pathway played a key role in the anti-ALI processing of this drug. The in vivo experiment showed that eriodictyol can effectively reduce liver function-related biochemical indicators such as ALT, AST, and AKP. Eriodictyol can also up-regulate the levels of SOD and GSH, and inhibit the release of IL-1β, IL-6, and TNF-α. Additionally, TUNEL staining, immunohistochemistry, and RT-PCR experiments showed that eriodictyol activated the PI3K/AKT pathway and decreased the expression of Bax, caspase3, and caspase8 while increasing the expression of Bcl-2 m-RNA. Finally, molecular docking experiments and molecular dynamics simulations confirmed the stable binding between eriodictyol and PI3K, AKT molecules. This study showed that eriodictyol can activate the PI3K/AKT signaling pathway to alleviate ALI-related oxidative stress and apoptosis. Acute liver injury (ALI) is a pathological condition that arises from a variety of etiologies, such as sepsis-induced hepatotoxins, drug-related adverse events, alcohol overuse, metabolic syndrome, hepatitis viral infections, or bacterial infections that invade the liver . The freThe diverse range of biological activities and desirable health benefits have recently made natural products more popular ,5. EriodSwertia cincta Burkill exhibits a specific protective effect on ALI. Notably, eriodictyol was identified as the primary active compound within the Swertia cincta Burkill extract [In prior research, it was observed that the extract derived from  extract . This obEriodictyol (≥98%) was provided by Nanjing Guangrun Biological Products Co., Ltd. . Silibinin (≥98%) and D-galactosamine  were provided by Shanghai Yuanye Biotechnology Co., Ltd. . Lipopolysaccharide (LPS) (055: B5) was bought from Sigma . The assay kits for ALT, AST, AKP, γ-GT, CHE, TP, and ALB were supplied by Nanjing Jiancheng Bioengineering Institute , while SOD, MDA, and GSH were provided by Solarbio, . The tunnel assay kit was purchased from Wuhan Servicebio, , and ELISA kits were purchased from FANKEWEI  used for measuring mice IL-6, IL-1β, and TNF-α.http://pubchem.ncbi.nlm.nih.gov/ accessed on 3 January 2023), the SMILES code for the molecular structure of eriodictyol was obtained. The standard SMILES was then uploaded to the following databases: SwissTarget (http://swisstargetprediction.ch/ accessed on 4 January 2023), PharmaMapper (http://lilab-ecust.cn/pharmmapper/ accessed on 4 January 2023), Herb (http://herb.ac.cn/ accessed on 4 January 2023), ETCM (http://www.tcmip.cn/ETCM/ accessed on 4 January 2023), HIT (http://hit2.badd-cao.net/ accessed on 4 January 2023), and SEA (https://sea.bkslab.org/ accessed on 4 January 2023). These databases were utilized to identify the targets of eriodictyol. UniProt (http://www.uniprot.org/uniprot/ accessed on 4 January 2023) was employed to convert the target names into the official gene target symbol format.In PubChem (https://www.genecards.org/ accessed on 5 January 2023), OMIM (https://www.omim.org/ accessed on 5 January 2023), TTD (http://db.idrblab.net/ttd/ accessed on 5 January 2023), PharmGKB (https://www.pharmgkb.org/ accessed on 5 January 2023), and DrugBank (https://go.drugbank.com/ accessed on 5 January 2023) databases. Subsequently, UniProt database was utilized to standardize the targets and verify their official gene names for accuracy.Employing the search terms “acute liver injury”, “liver injury”, and “hepatic damage”, targets were predicted using the Genecard (http://bioinformatics.psb.ugent.be/webtools/Venn/ (accessed on 6 January 2023). The resulting overlap of targets was then utilized to discern potential candidates for the treatment of ALI using eriodictyol.The transformed targets of eriodictyol and related to ALI were uploaded to the Draw Venn Diagram online platform at https://string-db.org/ accessed on 9 January 2023). In the interface, constrain the species to “Homo sapiens” and set the confidence score threshold to >0.4 for online PPI network construction. In the Export section, opt for the tsv file format for downloading and saving. Import this file into Cytoscape (https://cytoscape.org/ accessed on 9 January 2023) for visualization purposes. Utilize the network analyzer  to evaluate degree distribution, clustering coefficient, and edge centrality. These analyses will yield the final network graph and provide an initial insight into the core targets.Incorporate the shared targets of eriodictyol and ALI diseases into the STRING database (https://david.ncifcrf.gov/ accessed on 10 January 2023), we performed Disease Ontology (DO) analysis, Gene Ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to assess the shared targets, employing criteria of FDR < 0.05 and p < 0.05. Additionally, bubble charts were constructed utilizing online resources available at http://www.bioinformatics.com.cn/ (accessed on 10 January 2023). R software (Version 4.1.1) was employed for visualizing the outcomes.Utilizing the Database for Annotation, Visualization, and Integrated Discovery (DAVID) (http://bar.utoronto.ca/efp_human/cgi-bin/efpWeb.cgi (accessed on 20 February 2023), offers additional details regarding prospective candidate genes [The Human eFP (Electronic Fluorescence Pictogram) browser, accessible at te genes . In the https://www.rcsb.org/ accessed on 16 January 2023). The three-dimensional configuration of the eriodictyol ligand was obtained from the PubChem database. AutoDockTools (Version 1.5.6) software was used to prepare the protein and ligand structures for docking, including the addition of charges and hydrogen atoms, as well as setting up the binding site. Molecular docking simulations were carried out using AutoDockTools, and the process was repeated three times to enhance the reliability of the results. The results were analyzed by determining the active site positions and calculating the binding energy and hydrogen bond numbers. A negative binding energy indicates the ligand’s ability to spontaneously bind to the receptor, while a lower binding energy value signifies a stronger binding affinity. Ligplot+ software (version 2.2.4) (http://www.ebi.ac.uk/thornton-srv/software/LIGPLOT/ accessed on 20 January 2023) and PyMOL (Version 4.6.0) software were employed for visualizing and examining the ligand-receptor interactions, facilitating the identification of crucial residues involved in the binding process.The crystal structures of the PI3K (ID: 5DXT) and AKT (ID: 3QKK) receptors were retrieved from the Protein Data Bank (PDB) website (ROMACS (version 2020.6) was utilized to conduct molecular dynamics (MD) simulations. The CHARMM36 force field, along with the TIP3P water model, was employed to model interactions. The simulation system comprised a solvation box with a cubic shape, where the edge length was set to 1.2. Periodic boundary conditions of the adjoint type were applied for a duration of 1 ns. Following solvation, ion equilibration was performed to attain an ion concentration of 0.145 M, simulating the human environment and achieving initial conformational equilibration. Subsequently, the equilibration phase was executed in two steps: first, 100 ps in the ensemble of constant particle number, volume, and temperature, followed by 100 ps in the ensemble of constant number, pressure, and temperature. The temperature and pressure were adjusted to 310 K and 1 bar, respectively. Finally, a 100 ns MD simulation encompassing the entire system was carried out. The nonbonded interaction cut-off value was set at 1.2 nm, and the PME algorithm was employed to calculate long-range electrostatic interactions. A time step of 2 fs was utilized, and the conformations were saved at intervals of 10 ps.In preparation for drug administration, eriodictyol was accurately weighed and dissolved in PBS to obtain concentrations of 1, 2, and 4 mg/mL. Silibinin was dissolved in PBS to achieve a concentration of 10 mg/mL. The dosage and administration method for eriodictyol were determined based on previous investigations .ad libitum access to food and water. After a 7-day acclimatization period, the mice were randomly divided into six experimental groups as follows: (1): The control group (n = 10) received an intraperitoneal injection of physiological saline. (2) The LPS/D-GalN group  received an intraperitoneal injection of physiological saline. (3) The LPS/D-GalN+eriodictyol low-dose treatment group  received an intraperitoneal injection of eriodictyol at a dose of 10 mg/kg. (4) The LPS/D-GalN+eriodictyol medium-dose treatment group  received an intraperitoneal injection of eriodictyol at a dose of 20 mg/kg. (5) The LPS/D-GalN+eriodictyol high-dose treatment group  received an intraperitoneal injection of eriodictyol at a dose of 40 mg/kg. (6) The LPS/D-GalN+silibinin treatment group  received an intraperitoneal injection of silibinin at a dose of 100 mg/kg.Sixty male ICR mice (20 ± 2 g), aged 4 weeks, were obtained from Chengdu Dassy Biotechnology Co., Ltd. The mice were housed in a controlled environment with a constant temperature of (23 ± 2 °C), relative humidity of (55 ± 5%), and a 12-h light-dark cycle. They had g for 10 min at 4 °C to obtain the supernatant, which was then stored at −80 °C.The administration was carried out once a day for a duration of 7 days. On the 7th day, mice in the LPS/D-GalN, LPS/D-GallN+eriodictyol , and LPS/D-GalN+silibinin groups were intraperitoneally injected with 600 mg/kg of D-GalN and 10 μg/kg of LPS, following one hour after the administration of eriodictyol, silibinin, or physiological saline. The control group received a saline injection alone. After 6 h, all mice were euthanized to collect blood and tissue samples. Plasma was collected, followed by centrifugation at 3500× The mice’s liver was obtained and weighed to determine the organ index using the formula: the weight of the organ (in grams) was divided by the body weight (in grams) and multiplied by 100%.g, 10 min, 4 °C) and the supernatant was collected for analysis. The levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), albumin (ALB), total proteins (TP), alkaline phosphatase (AKP), γ-glutamyltransferase (γ-GT), and cholinesterase (CHE) in the serum were determined using assay kits specific to ALT, AST, ALB, TP, AKP, γ-GT, and CHE.The blood was centrifugated  and tumor necrosis factor α (TNF- α) in liver tissue were quantified using a commercial ELISA kit, following the manufacturer’s instructions.The protein expression of PI3K and AKT in mouse liver tissues was detected via immunohistochemistry in mice liver sections by using standard immunohistochemistry methods . The antTotal RNA was extracted from liver tissue using Trizol reagent , followed by performing a measurement of the concentration of total RNA in the sample. Subsequently, synthesis of cDNA was accomplished utilizing a High capacity RNA to cDNA kit .The expression of the indicated genes was analyzed using RT-PCR amplified with SYBR Green . QX400  was used for qPCR. A list of primer sequences is presented in t-test and ANOVA were utilized as statistical assessments. The significance level was established at p < 0.05.The data were reported as the mean ± SEM and statistical analyses were performed using GraphPad Prism 9.0 software . Both Through database analysis, a total of 169 targets for eriodictyol and 786 disease targets were identified. Additionally, 47 potential targets for the treatment of ALI with eriodictyol were pinpointed A.The PPI network is shown in The GO enrichment analysis conducted in this study focuses on three domains: cell components (CC), molecular functions (MF), and biological processes (BP) as outlined by Zheng et al. in 2020. Among the initial set of 20 enriched KEGG pathways, the “PI3K-Akt signaling pathway” has been recognized as a crucial pathway for the treatment of ALI using eriodictyol. The KEGG enrichment pathway map, illustrating the pertinent details of the 20 enriched pathways, was acquired through importation into “WeChat” D. The enIn the analysis, we examined the gene expression profiles of AKT1 and PI3K using the human eFP browser, which provides an overview of gene expression levels in the liver. The analysis shows that AKT1 and PI3K are highly expressed in the liver , indicatp < 0.01) in mice treated with LPS/D-GalN. However, when compared to the model group, the positive control silibinin group and the medium dose group of eriodictyol demonstrated a significant reduction effect on the liver index. The results also indicated that LPS/D-GalN-induced significantly increased the levels of ALI, ALT, AST, AKP, and γ- GT, while decreasing TP, ALB, and CHE levels significantly  when compared to the control group. Conversely, treatment with eriodictyol resulted in a significant increase in the expression of p-PI3K and AKT in the liver tissue of mice compared to the model group (p < 0.05). TUNEL staining revealed a significant increase (p < 0.01) in the population of apoptotic cells in the liver tissue of the model group compared to the control group  and a significant decrease in SOD and GSH activities (p < 0.01) compared to the control group. These findings indicated the induction of robust oxidative stress in mice induced by LPS/D-GalN. Eriodictyol treatment can decrease oxidative stress in a dose-dependent manner, by down-regulating the release of MDA in comparison to the model group. Additionally, all doses of eriodictyol substantially elevated the expression of SOD and GSH. These findings suggested that eriodictyol administration alleviates ALI induced by LPS/D-GalN by enhancing the synthesis of antioxidant enzymes and suppressing lipid peroxidation. As illustrated in p < 0.01), demonstrating the occurrence of pronounced liver inflammation. In comparison to the model group, the eriodictyol treatment group exhibited a significant reduction in IL-6 . Conversely, both eriodictyol and silibinin substantially enhanced the mRNA expression levels of PI3K, AKT, TSC2, and mTOR of ALI mice (p < 0.05). These findings suggest that the hepatoprotective effect of eriodictyol may be attributed to the activation of the PI3K/AKT signaling pathway. Moreover, both the eriodictyol and silibinin groups exhibited a significant increase in Bcl-xl mRNA expression while decreasing the mRNA expression of Bax, Bid, Caspase-8, and Caspase-3 (aspase-3 E–I.Molecular docking analysis showed that eriodictyol can bind to the active pockets of PI3K and AKT crystal structures, and the overall binding conformation can be observed in the 3D diagram. The 2D diagram depicts the formation of robust hydrogen bonds between eriodictyol and specific amino acid residues of PI3K A, namelyALI is an abrupt clinical syndrome that typically arises from viral infections, toxic substances, excessive alcohol intake, and drug overdose, and severe liver injury can result in failure of the liver and even death ,19. The The network pharmacology offers insights into the potential mechanism of eriodictyol in ALI by facilitating the prediction of the targeted distribution and pharmacological action of active compounds found in traditional Chinese medicine . By leveBP analysis of GO function in network pharmacology showed that eriodictyol can act as an antioxidant . MDA serThe PI3K-Akt-mTOR signaling pathway engaged in numerous cellular functional activities, including apoptosis, migration, and cellular invasion . Anne-KaApoptosis, a pivotal cellular process, is essential for maintaining the physiological balance of organs . In our Nevertheless, it is important to acknowledge the limitations of our current study. While the PI3K/Akt pathway has been implicated in the influence of eriodictyol, it is essential to recognize that eriodictyol may exert its effects through additional pathways. A more comprehensive investigation is warranted to elucidate the precise mechanism by which eriodictyol operates in ALI. This study uses an animal model of ALI, but its protective effect on chronic liver injury needs further study. In conclusion, we have proved that eriodictyol has a significant liver protection effect in the experimental model in vivo and predicted PI3K/Akt as a possible signal pathway using network pharmacology and then verified it through the experiment in vivo. This substantiates the ability of eriodictyol to attenuate ALI by impeding oxidative stress, inflammation, and apoptosis through the activation of the PI3K/Akt pathway.Collectively, we employed bioinformatics analysis techniques to assess the potential targets and underlying signal pathways implicated in eriodictyol’s therapeutic potential for ALI. Building upon this foundation, we established a mouse model of ALI induced by LPS/D-GalN to investigate the molecular mechanisms underlying eriodictyol’s hepatoprotective properties. The outcomes indicated that eriodictyol’s protective effects against ALI involve the activation of proteins within the PI3K/AKT signal pathways, regulation of oxidative stress, attenuation of inflammation, and inhibition of hepatocyte apoptosis. Therefore, we speculate that eriodictyol can be used as a natural liver protector to prevent liver injury.


This study aimed to explore the substance basis and mechanisms of Shen-qi-wang-mo Granule (SQWMG), a traditional Chinese medicine prescription that had been clinically utilized to treat retinal vein occlusion (RVO) for 38 years. Components in SQWMG were analyzed by UPLC-Triple-TOF/MS and a total of 63 components were identified with ganoderic acids (GA) being the largest proportion. Potential targets of active components were retrieved from SwissTargetPrediction. RVO-related targets were acquired from related disease databases. Core targets of SQWMG against RVO were acquired by overlapping the above targets. The 66 components (including 5 isomers) and 169 targets were obtained and concluded into a component-target network. Together with biological enrichment analysis of targets, it revealed the crucial role of the “PI3K-Akt signaling pathway”, “MAPK signaling pathway” and their downstream factor iNOS and TNF-α. The 20 key targets of SQWMG in treating RVO were acquired from the network and pathway analysis. The effects of SQWMG on targets and pathways were validated by molecular docking based on AutoDock Vina and qPCR experiment. The molecular docking showed great affinity for these components and targets, especially on ganoderic acids (GA) and alisols (AS), which were both triterpenoids and qPCR exhibited remarkably reduced inflammatory factor gene expression through regulation of these two pathways. Finally, the key components were also identified from rat serum after treatment of SQWMG. RVO includes two main types: branch retinal vein occlusion (BRVO) and central retina vein occlusion (CRVO). The International Eye Disease Consortium reported the prevalence of RVO studies which shows that the prevalence of RVO was 0.52% for any RVO, 0.44% for BRVO, and 0.08% for CRVO. It suggested that roughly 16 million people in the world suffer from RVO and BRVO is about 5 times CRVO3. The main clinical manifestations of RVO are a sudden loss of vision (CRVO) or blurring in the visual field (BRVO) which is generally asymptotic and painless at the early stages but could aggravate the condition due to intraretinal hemorrhage, retinal edema, and other vascular disorders5.Retinal vein occlusion (RVO) is the second most common retinal vascular disease after diabetic retinal disease and one of the most common causes of sudden painless unilateral vision loss4. With the development of VEGF antagonist injections for eyes, most patients have received surprising vision improvement. Nevertheless, its therapeutic outcomes are not always consistent with expectations. About half of the patients with BRVO and over half of those with CRVO still require anti-VEGF injections for 5 years or more after starting treatment and long-term outcomes are still unknown6. Even more, some patients with RVO followed monthly anti-VEGF injections for about 5 months but it did not eliminate macular oedema6. So there’s more effort to be put into drug research for RVO and the abundant traditional Chinese medicine (TCM) might show us a new way.Clinically, corticosteroids are commonly used in macular edema caused by RVO. Because vascular disorders and inflammation play a significant role in the pathogenesis of RVO, the anti-VEGF monoclonal antibody taking place of corticosteroids becomes crucial in drug therapy. Anti-VEGF drug Ranibizumab was approved by FDA in June 2010 for the treatment of macular edema secondary to BRVO7. The prescription is composed of 13 herbs: Rehmannia Glutinosa Libosch and Rehmanniae Radix Praeparata (SDH), Fructus Ligustri Lucidi (NZZ), Poria Cocos (Schw.) Wolf. (FL), Codonopsis Radix (DS), Angelicae Sinensis Radix (DG), Alisma Orientale (Sam.) Juz. (ZX), Carthami Flos (HH), Lycii Fructus (GQZ), Radix Paeoniae Rubra and Paeoniae Radix Alba (SY), Plantaginis Herba (CQC), and Ganoderma Lucidum (LZ). This prescription has the effects of brightening the eyes, nourishing the liver and kidneys, and promoting blood circulation and diuresis. However, as a component preparation of TCM, its pharmacological basis was unknown and the mechanism of action remained unclear. To overcome the complex obstacles in clarifying the mechanism of TCM, “Network pharmacology” had been introduced and utilized with the development of the multi-omics study, system biology, and chemical biology. By following the route of “prescription-ingredient-component-target-pathway-disease” and constructing the “drug-component-targets” (CTD) network, it provided an efficient way to investigate the pharmacological effects and potential mechanisms of TCM systematically8. It had been successfully applied to explore the mechanism of profound TCM herbal formulae such as Shexiang Baoxin Pill (SBP), and Qingfei Xiaoyan Pill (QFXYP), and diseases including myocardial infarction, cancer, and even COVID-1910.TCM ophthalmology believes that blood stasis, blood deficiency, phlegm, and blood stasis are the main syndromes of RVO. TCM took promoting blood circulation, removing blood stasis, regulating qi, and dredging collaterals as the treatment principle of RVO and achieved good clinical effects. TCM has the characteristics of multi-target, multi-pathway, and multi-mechanism. Shen-qi-wang-mo granule (SQWMG) is a component preparation of TCM for the treatment of fundus diseases in Shanghai General Hospital. The ophthalmology of the hospital is a national key clinical specialty. SQWMG has a remarkable effect on the clinical use of ophthalmology in the hospital and it has been used clinically to treat RVO for 38 years. A clinical study including 120 patients with RVO revealed that the improvement after treatment was statistically significant (P < 0.05) in the SQWMG-Pancreatic kininogenase combination compared to a single drug11. The key components were also identified from rat serum. Together, this study followed the guidelines for network pharmacology evaluation and revealed the potential mechanism and substance basis of SQWMG in treating RVO and provides a certain basis for future exploration, also providing new ideas for developing new drugs12.In this study, as shown in Fig. 7. In the past 6 months (2022/6/1–2022/11/31), the number of outpatient prescriptions for SQWMG in our hospital reached 781, of which 290 were patients with fundus diseases related to retinal vein occlusion. It is worth noting that nearly half of the prescriptions (387) were re-prescription that were repeated more than twice, indicating the efficacy of the drug and the recognition of patients  and 63 components Table  were ide13.The proportion of each herb's ingredients was shown in Fig. Through SwissTargetPrediction, potential drug targets were searched and obtained by selecting the effective results (probability score > 0). A total of 559 targets were included in the next step , NR3C1 (Glucocorticoid Receptor), MMP2 , HSP90AA1  and NOS2 . The inhibition of PKC was believed to be effective in treating VEGF-induced retinal vascular dysfunction16. NR3C1 encodes glucocorticoid receptors, upon which glucocorticoids exert most of their effects. Glucocorticoid had a strong anti-inflammatory function and was also a traditional treatment for RVO patients before anti-VEGF therapy4. MMP2 was a zinc-dependent protease that plays an important role in many diseases, recent research had revealed its connection to vein thrombosis and RVO18. INOS is a key enzyme associated with inflammation, retinal ischemia, and pathologic vascular proliferation and had a relation with the activation of the MAPK signal pathway21. The result of the CTD network offered a primary insight into the mechanism of SQWMG with multi-targets and multi-components.A disease-related target analysis was then conducted based on GeneCards, DisGeNET, and OMIM databases. In GeneCards, RVO-related gene targets show 2015 results, and 1007 targets with higher relevance scores were included. Another 76 genes were obtained in DisGeNET and 212 genes from OMIM. Final RVO-related targets contained 1212 genes by crossing results from GeneCards, DisGeNET, and OMIM. All target information was shown in Supplementary Table https://string-db.org/) to perform a protein-protein interaction (PPI) analysis. As the interaction score was set to “highest confidence” (0.9), results showed 19 targets isolated, meaning they possibly hadn’t laid on an effective pathway in treating RVO , Mitogen-activated protein kinase 3 , Signal transducer and activator of transcription 3 , P53  and Mitogen-activated protein kinase 1 . Then the Gene Ontology (GO) enrichment analysis was conducted by Metascape and the threshold was selected as P < 0.01. The final results of the top 20 terms in GO-BP, GO-CC, and GO-MF were shown in Fig. All 169 potential targets in the CTD network were then introduced to the String database  enrichment analysis was performed to evaluate relevant pathways based on Metascape. A total of 150 targets the in PPI network were found to be involved in 199 pathways (P < 0.01)  by precise m/z and daughter ion 481.2966, 445.2716, and 351.195123. This result also suggested that the hydroxyl group of LZ-3 underwent protonation and subsequent H2O loss during ESI in-source collision-induced dissociation (CID)24. The combination of LZ-3 and MAPK1 reached a binding energy of − 12.5 kcal/mol with multiple polar and hydrophobic interactions to stabilize the binding and it also fitted well with AKT1. Both targets were important in MAPK and PI3K/Akt/mTOR signaling pathways and inhibition of these targets may elucidate a strong anti-inflammatory effect by reducing gene expression of inflammatory factors. For inflammatory factors, TNF and NOS2, DS-3, and LZ-12 exhibited great affinity as shown in Supplementary Figure Among all components, LZ-3 (Ganoderic acid B), exhibiting the highest affinity in these targets, was shown in Fig. The result of molecular docking again showed the mechanism of SQWMG was a multi-component and multi-target process. The high affinity of inflammatory factors like iNOS, TNF-α, and MAPK/PI3K- related targets like MAPK1 and AKT1 with GA and AS being key components, was consistent with the results obtained in the previous analysis in this article.25. As can be seen in Fig. Following the results from molecular docking analysis, we next validated the effects of SQWMG on the expression of MAPK- and PI3K- related downstream factors in vivo using qPCR assay. Dysregulated angiogenesis started by VEGFA involved MAPK and PI3K/Akt signaling pathways causing an abnormal increase of inflammatory factors including iNOS and TNF-αTo investigate whether the main components found above can be absorbed to exert pharmacological activity, we analyzed the serum of rats after treatment of SQWMG by UPLC-Triple-TOF/MS. To make the experimental results closer to the situation of clinical use, the animal dose was converted according to the clinical dosage. A total of 12 components were identified from rat serum at different time points after administration as shown in Table As a TCM prescription used clinically to treat RVO for 38 years, SQWMG had a complex pharmacological network. In this study, we aimed to explore the underlying pharmacological mechanism and substance basis of SQWMG in treating RVO by combining components analysis and network pharmacology.30. Then we employed network pharmacology, investigating the potential targets by target prediction following the network pharmacology evaluation method guidance12. A combination of RVO-related targets and SQWMG-related targets formed a complex CTD network on which some targets exhibited greater importance such as PKC, glucocorticoid receptor, and iNOS. These targets are closely related to RVO and gave a glimpse of the mechanism but were still isolated. Biological analysis was then introduced to find the inner relation of these targets.The aqueous extract of SQWMG and each ingredient was analyzed by UPLC-Triple-TOF/MS and 63 components Table  were ide31. Central to the pathogenesis of RVO is the VEFG and related increased dysfunctional proliferation, migration, and inflammation which contained these two signaling pathways32. Previous studies had found these two tyrosine kinase pathways underwent upregulation during the pathogenesis of RVO and inhibition of these pathways resulted in a decrease of oxidative and inflammatory stress showing a good effect34. PI3K-Akt signaling pathways played a multi-functional role in vascular disorder and response to risk factors including VEGF, LDL, and AGEs. In vascular smooth muscle cells, PI3K/Akt activation induced smooth muscle cell proliferation which contributes to a vascular narrowing that could aggravate retinal vein occlusion35. Research had also revealed that inhibition of PI3K/Akt-IKK  could greatly attenuate TNF-α and iNOS38. PI3k/Akt/mTOR was also proved to be involved in VEGF-induced retinal vascular diseases including RVO and inhibition of mTOR showed great therapeutic effect39. When it came to the MAPK signaling pathway, a more complex network was involved. The MAPK cascades included four major MAPKs: the extracellular signal-related kinases , the c-Jun N-terminal kinases (MAPK8), the p38 kinase (MAPK14), and the big MAP kinase 1 (ERK 5) which were directly regulated by oxidative stress40. The MAPK signaling pathway involved a strong pro-inflammatory effect and production of adhesion molecules by downstream regulation. Once ERK1/2 and p38 were activated by VEGF, TNF-α and endothelial damage, it started signal transduction which eventually phosphorylated the NF-kB p65 subunit and then caused a strong pro-inflammatory effect through upregulation of IL-6, TNF-α, and iNOS as shown in Fig. 842. PI3K pathway also had close cross-talk with the MAPK pathway and contributed to this pro-inflammatory effect43. Many studies had found the effect of VEGF and the production of inflammatory factors were dependent on these two pathways, and the main components GA and AS could inhibit this process, thus SQWMG might regulate dysregulated angiogenesis and vascular inflammation by inhibition of these pathways, and eventually remarkably decrease of gene expression of inflammatory factors.The result of GO analysis and KEGG pathways analysis revealed the significance of the “PI3K-Akt signaling pathway” and “MAPK signaling pathway”. Following the relation between RVO and vascular dysfunction, we focused on these two pathways and found they shared a big part of the same targets, and the key targets shared by these two pathways also took more than half of the place in the top 10 targets in KEGG pathway analysis Figure d. “PI3K-45. This result from molecular docking, together with the fact that GA and AS accounted for the largest proportion of the components, suggests that GA and AS are the main components that account for the therapeutic effects of SQWMG. The component that exhibited the highest affinity, LZ-3, was also identified from rat serum after administration of SQWMG, indicating it indeed could be absorbed into the blood to act with these target proteins.The molecular docking and animal experiment conducted on zebrafish verified this mechanism and involved targets. 20 key protein targets involved in MAPK and PI3K pathways were tested and the results were surprisingly great Figure . For key47. The results of qPCR validated SQWMG’s effect on these two pathways with repressed gene expression in key targets  showed the characteristics of multi-target, multi-pathway, and multi-mechanism. Further analysis of the involved targets revealed the close relation between RVO and vascular risk factors including VEGFA and the crucial role of MAPK and PI3K-Akt signaling pathways through their impact on vascular inflammation. Finally, the results of network pharmacology were validated by molecular docking and qPCR experiment. Based on our findings from previous and current studies, we clarified that SQWMG could alleviate the inflammation and subsequently improve retinal blood supply and vascular obstruction through the regulation of MAPK and PI3K-Akt signaling pathways and downstream iNOS and TNF-α. Main components, including ganoderic acid B, were also identified from rat serum after treatment. Overall, the results provided a novel, theoretical insight into understanding the bioactive components and the pharmacological mechanism of SQWMG. It was also known from the analysis of molecular docking results that the GA and AS played a major role in SQWMG so this study also provided a basis for reducing the prescription of SQWMG. More and further research could be conducted following the CTD network and the above analysis.SQWMG was provided by Shanghai Liantang Pharmaceutical Co., Ltd (Lot No. 20200902). Acetonitrile and methanol for MS analysis were purchased from E. Merck Chemical Co. Ltd. . Formic acid was purchased from CNW Technologies . The zebrafish embryos were anesthetized with tricaine  final concentration of 0.016%). 1-phenyl-2-thiourea (PTU) was purchased from Sigma-Aldrich Co . TRIzol reagent , Hifair II 1st Strand cDNA Synthesis SuperMix reagent Kit with gDNA digester , Hifair qPCR SYBR Green Master Mix (High Rox Plus)  was used for qPCR analysis.Data from the medical records of patients prescribed SQWMG in the outpatient ophthalmology clinic of Shanghai General Hospital in the previous six months (2022/6/1-2022/11/31) were retrospectively collected and analyzed in age, gender, disease, and re-prescription rate.1.0 g of SQWMG was dissolved in 10 mL of 20% (v/v) methanol-water, sonicated  for 30 minutes, and then cooled to room temperature. Next, 2 mL of cooled liquid was centrifuged  to obtain the final sample solution from the supernatant. For more specific analysis, collected 1 mL of each aqueous extract of Rehmanniae Radix Praeparata, Fructus Ligustri Lucidi, Angelicae Sinensis Radix, Alisma Orientale (Sam.) Juz., Carthami Flos, Radix Paeoniae Rubra, Paeoniae Radix Alba, and Plantaginis Herba, and diluted 10 times with 10 mL of 20% (v/v) methanol-water. Then the aqueous extracts were centrifuged  to obtain the final sample solution from the supernatant. The same process was repeated with 2 mL of Poria Cocos (Schw.) Wolf. aqueous extract. Finally, aqueous extract collected from Codonopsis Radix, Lycii Fructus, and Ganoderma Lucidum was diluted with 10 mL of 20% (v/v) methanol-water.Each sample was analyzed on a Sciex Triple TOF 4600 LC-MS equipped with an Agilent UPLC column . The mobile phases consisted of (A) acetonitrile and (B) 0.1% formic acid aqueous solution. The gradient elution program was optimized as shown in Supplementary Table Data were acquired by the software of Analyst TF 1.7.1 and analyzed on Peakview 1.2. The MS and MS/MS data were matched with the database of Natural Products HR-MS/MS Spectral Library 1.0. The database of Natural Products HR-MS/MS Spectral Library 1.0 recorded multistage mass spectrograms of standard substances including different acquisition modes, different adduct ions, different collision energies, etc. Then, the components were further screened according to the score of the chromatographic peak. Finally, the components were identified from relative information of MS and MS/MS. The components which could not be found in the database were identified from a fragmental pattern or relative literature.http://www.swisstargetprediction.ch/)48. Species were set to “Homo sapiens”. Only genes with a high possibility (probability score > 0) were selected as potential targets of drug components. Then RVO disease-related targets were collected from three sources: GeneCards , DisGeNET , and OMIM 49. Only proteins from ‘Homo sapiens’ were selected and included all types of RVO. Then targets shared by drug and disease were retained using “VENNY 2.1” while the other targets were removed.The potential targets of these components were obtained from the website of SwissTargetPrediction (https://string-db.org/). Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis and gene ontology biological process (GO-BP), cellular component (GO-CC), and molecular function (GO-MF) were carried out using the Database of Metascape (https://metascape.org/)50. The p-value is calculated by the hypergeometric test as the probability of obtaining overlapping genes of certain pathway members, forming a cumulative hypergeometric distribution.Drug-Components-Target network, Component-target-disease (CTD) network, protein-protein interaction (PPI) network, and potential target gene-related pathway network were constructed by Cytoscape (ver.3.9.0). Nodes in the networks represent chemicals, diseases or targets, and edges indicate interactions between two nodes. For the topological properties, “degree” (D), “closeness centrality” (CC), and “betweenness centrality” (BC) were calculated to demonstrate the further analysis. Shared targets by drug and disease were performed by a PPI analysis by String database .AutoDock Vina (ver.1.1.2) was used for ingredient-target molecular dockingLarvae zebrafish were maintained, handled, and bred according to standard protocols from the Institutional Animal Care Committee of Shanghai Jiao Tong University. The transgenic zebrafish Tg (kdrl: GFP) are tagged with green fluorescent protein on vascular endothelial cells. Pathogen-free male SD rats (200 g) were provided by Shanghai Silaike experimental animal Co., Ltd. . Rats were housed in an animal room  with the setting of a 12 h dark/light cycle. Animal studies were performed in accordance with the Guide for the Care and Use of Laboratory Animals, the guidelines of ARRIVE , and relevant Chinese laws and regulations, and approved by the Institutional Animal Care and Use Committee of Shanghai Jiao Tong University .2, and 0.33 mM MgSO4) and staged by hours post-fertilization (hpf) and days post-fertilization (pdf). At 24 hpf, the chorion of embryos was removed by a protease . Then the embryos were randomly assigned to 24-well culture plates with fifteen embryos per well in E3 medium plus 0.003% PTU to prevent pigmentation. These embryos were divided into three groups: blank control group, positive control group , and SQWMG group . The medium solution was changed every other day.After normal fertilization, embryos were collected and kept at 28.5 °C in E3 medium  are listed in Supplementary Table After drug treatment for 4dpf, total RNA was extracted from Zebrafish embryos with TRIzol reagent. cDNAs were synthesized from total RNA using the Hifair II 1st Strand cDNA Synthesis SuperMix reagent Kit with a gDNA digester. Hifair qPCR SYBR Green Master Mix (High Rox Plus) was used for qPCR analysis. The qPCR was done in an ABI HT-7900 machine . Results were calculated using the 2−ΔΔCT method with WT embryos as the controlBefore the experiment, rats were given water and fed standard laboratory food for acclimatization for a week. SQWMG 0.72 ml  was orally administrated to the rats twice a day at the dose of 3.6 g/kg (dose volume/body weight) for seven days. The blood collection time is 0.5 h, 1.5 h, and 5 h after the last dosing.The blood samples were drawn into an Eppendorf tube and then centrifuged at 6500 rpm for 10 min at 4 °C. Then, the plasma samples were transferred to Eppendorf tubes and stored at − 80 °C for further analysis. 200 μL plasma was treated with 600 μL of methanol to precipitated protein, then vortex mixed for 5 min at 4 °C and centrifuged at 12000 rpm for 15 min at 4 °C. The supernatant was transferred to another tube for further analysis.The UPLC-Triple-TOF/MS conditions and the process of data analysis were the same as in the analysis of SQWMG components as shown in Supplementary Table All the data have been expressed as mean ± SD. GraphPad Prism  was used to analyze and illustrate the results. The statistical significance is described in the respective figure legends .Supplementary Information 1.Supplementary Figure 1.Supplementary Figure 2.Supplementary Figure 3.Supplementary Figure 4.Supplementary Figure 5.Supplementary Table 1.Supplementary Table 2.Supplementary Table 3.Supplementary Table 4.Supplementary Table 5.Supplementary Table 6.Supplementary Table 7.


This study aimed to investigate the underlying mechanism of Zuogui Pill in its efficacy against liver cancer, employing a combination of data mining approaches and network pharmacology methods. A novel clustering analysis algorithm was proposed to identify the core gene modules of Zuogui Pill. This algorithm successfully identified 5 core modules, with the first large module comprised of twelve proteins forming a 12-clique, representing the strongest connections among them. By utilizing GEO platform, ten key target proteins were detected, including FOS, PTGS2, and MYC. According to the GO annotation and KEGG analysis, desired target proteins were significantly enriched in various biological processes (BP). The analysis showed that ten key targets were strongly associated with signaling pathways mainly centered on MAPK and PI3K-Akt pathway. Additionally, molecular docking revealed strong binding affinities between core active ingredients of Zuogui Pill and these key targets, and the best affinity modes were observed for PTGS2-Sesamin, PRKCA-Sesamin, FOS-delta-Carotene. In order to establish the relationships between clinical symptoms and drug targets, a heterogeneous targets-related network was constructed. A total of 60 key target-symptom association pairs were detected, exemplified by the strongly association between fever and PTGS2 through the intermediary of Shu Di Huang. In summary, symptom-target associations are valuable in uncovering the underlying molecular mechanisms of Zuogui Pill. Our work reinforced the notion that Zuogui pill exhibits therapeutic potential on liver cancer through network targets, as well as synergistic effects of multi-component and multi-pathway. This study provided specific references for future experiments at the cost of less time. The etiology is commonly attributed to be the synergistic effect of multiple oncogenes and gene mutation with multi-factor synergy, though the pathogenic mechanisms remain unclear. Surgical intervention is often employed for liver cancer in modern medicine. Unfortunately, the high reoccurrence rate and poor prognosis still pose challenging. Drawing on the principle of syndrome differentiation and treatment, Traditional Chinese Medicine (TCM) serves as a complementary therapy on liver cancer. By simultaneously regulating multiple components and multiple targets, TCM not only relieves severe postoperative symptoms but also endeavors to prevent the reoccurrence and improve prognosis. It has been known that Zuogui Pill has the certain research basis in treatment of liver cancer. Li et al proposed that it can effectively regulate liver cell proliferation and apoptosis, and mitigate liver tissue damage based on the experimental results. However, the mechanism underlying the therapeutic impact on liver cancer still cannot be clarified. The emergence of modular pharmacology in the biomedical network has introduced new avenues of research concerning the complex mechanism by which TCM exerts its therapeutic effects, employing multi-target and multi-pathway approaches.,5 In this study, we constructed the protein-protein interaction (PPI) network via the common target genes of Zuogui Pill and liver cancer. Subsequently, potential functional modules were identified using clustering analysis algorithm. We aimed to uncover the key targets of Zuogui Pill in combating liver cancer and elucidate the molecular mechanism so that a valuable reference could be provided for future experimental studies.Liver cancer is one of the high-incidence malignant diseases within the digestive system, and approximately, 905,677 new cases of liver cancer were estimated worldwide in 2020 according to the estimation of the World Health Organization.The workflow on the combination of machine learning and network pharmacology in this study was seen in Figure http://tcmspw.com/tcmsp.php), which aimed to analyze the biological mechanism of Chinese herbs at the genetic level. Zuogui Pill is mainly composed of 6 herbs including Shu Di Huang (Rehmanniae Radix Praeparata), Tu Si Zi (Cuscutae Semen), and Niu Xi (Achyranthis Bidentatae Radix). Firstly, the active ingredients of Zuogui Pill were screened if both oral bioavailability (OB ≥ 30%) and drug likeness (DL ≥ 0.18) were assumed. Secondly, the target proteins corresponding to ingredients were extracted in the TCMSP, and then, the selected targets were converted into the SwissProt identifiers in the UniProt database (https://www.uniprot.org/).The active ingredients of Zuogui Pill were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform  and the Online Mendelian Inheritance Man platform , genes related to liver cancer were obtained after removing the duplicate ones. The overlapping targets between liver cancer and Zuogui Pill in Venny2.1 platform (https://bioinfogp.cnb.csic.es/tools/venny/index.html) were identified as potential targets in the treatment of liver cancer.The keywords “Liver Cancer” and “hepatocellular carcinoma” were searched in GeneCards platform (https://string-db.org/), and the data on the PPI was obtained. wij was defined as the interaction coefficient between protein node Ni and Nj, di represented the sum of the weighted degree of node Ni, it was calculated as follows:The common genes of Zuogui Pill and liver cancer were uploaded into the Retrieval of Interacting Genes database . The diagonal matrix D with dii equal to the sum of the elements of row i of W. The Laplace matrix L was defined as follows: L = D-W. And the matrix L was standardized as D−1/2LD−1/2, and the eigenvalues and corresponding eigenvectors of L was calculated. The eigenvectors corresponding to the k largest eigenvalues are stacked as columns to form the n × k matrix U. Each row of U is re-normalized to unit length to matrix Y. The matrix Y is a real valued solution of the clustering problem, the number of columns of Y, k, is defined as the number of clusters. Subsequently, we employed the MCL algorithm in the second phase, which is a graph clustering algorithm based on Markov Chain proposed by van Dongen. Initially, the adjacency matrix of the network is converted into a column stochastic matrix by dividing every non-zero entry by the sum of all entries in the column where the entry belongs. And then the network was divided into communities by alternately applying 2 operators named expansion and inflation on the matrix, until the matrix converges.To identify the functional modules in the PPI network, we proposed a 2-stage clustering algorithm based on Spectral clustering method and Markov Cluster (MCL) algorithm. The spectral clustering algorithm was conducted in the first phase, which has good property because of low sensitivity to the shape of the sample space and adaptability for sparse data. to search for the largest clique in each cluster. The clusters with less than 3 targets were discarded. Gephi 0.9.3 and Cytoscape 3.9.1 software were used to visualize the PPI network, Spectral clustering method and MCL algorithm were utilized via R studio software.The proposed method integrates the advantages of spectral clustering and MCL algorithm, enabling efficient mining of functional modules from noisy data. To identify core modules, we applied the k-clique algorithmThe GEO database platform was used to retrieve the gene expression data of liver cancer. The species was set as “Homo Sapiens.” The differential expression analysis was performed by using the GEO2R platform, and differentially expressed genes (DEGs) with the cutoff criteria of |Log2FC|>1 andP value < .05 and visualized by Rstudio software.https://david.ncifcrf.gov/). The threshold value P ≤ .05 was considered statistically significant.Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomics (KEGG) enrichment analysis were used to validate the biological function of key targets. Functional analysis and pathway enrichment were performed on the key targets using DAVID database for annotation, visualization and integrated discovery (https://www.rcsb.org). The target proteins were processed by removing water motifs and adding hydrogen by AutoDockTools-1.5.7. The protein receptors and ligand were converted to PDBQT format files. The lower the values of binding energy, the more stable the binding between proteins and active ingredients. It was generally believed that the binding energy less than −7.0 kcal/mol indicate stable binding affinity.Ten key targets and the top 5 active ingredients of Zuogui Pill were selected. The 3D structure of key target was downloaded from PDB database (http://www.symmap.org/), treated by both TCM and modern medicine related to 6 herbs of Zuogui Pill, including Shu Di Huang (Rehmanniae Radix Praeparata), Shan Zhu Yu (Corni Fructus), Niu Xi (Achyranthis Bidentatae Radix), Gou Qi Zi (Lycii Fructus), and Tu Si Zi (Cuscutae Semen). Clinical phenotypes related to liver cancer were collected using MalaCards and Orphanet databases.TCM symptoms were collected from SymMap platform , 45 from Gou Qi Zi (Lycii Fructus), 20 from Niu Xi (Achyranthis Bidentatae Radix), 16 from Shan Yao (Rhizoma Dioscoreae), 11 from Tu Si Zi (Cuscutae Semen). As Figure 331 shared target genes of Zuogui Pill and liver cancer were used to construct PPI network, which was composed of 331 nodes and 5613 edges. The thickness of the edge indicated the strength of interaction between 2 nodes. Three topological features were calculated to show the overall centrality of PPI network, the mean clustering coefficient was 0.526, the density was 0.103, and the network centrality (NC) was 0.387. Besides, the weighted degree of each node was calculated, the maximum and minimum were 115.18 and 1.42 respectively, and the mean degree was 22.61.Based on the novel 2-stage clustering analysis, the original PPI network was divided into 20 communities, as it was shown in Figure Three liver cancer-related gene expression datasets GSE60502, GSE84402, and GSE112790 were retrieved through the GEO platform. A total of 1870 differentially expressed genes (DEGs) were obtained from the GSE60502 dataset, 969 of which were up-regulated and 811 were down-regulated. Similarly, 1566 of DEGs were obtained from the GSE84402 dataset, 2361 from the GSE112790 dataset. Subsequently, 2986 of DEGs were included after all of them were merged. 38 target proteins contained in 5 core modules were mapped to 2986 DEGs. And then, 10 proteins were identified as key targets of Zuogui Pill against liver cancer, including FOS, PTGS2, STAT1, IGF1, MYC, JUN, PRKCA, CAV1, MMP1, and SELE. Furthermore, 4 targets were marked as down-regulated, another 6 ones were up-regulated. They were seen in Figure P ≤ .05). 53 of these items were involved in biological process (BP), such as positive regulation of smooth muscle cell proliferation (GO:0048661), response to xenobiotic stimulus (GO:0009410), angiogenesis (GO:0001525), positive regulation of transcription, DNA-templated (GO:0045893), and response to cytokine (GO:0034097). Seven cell component (CC) items, were mainly related to caveola (GO:0005901), RNA polymerase II transcription factor complex (GO:0090575), and transcription factor AP-1 complex (GO:0035976). Additionally, 11 molecular function (MF) entries were identified, mainly including enzyme binding (GO:0019899), transcription factor activity, sequence-specific DNA binding (GO:0003700), and RNA polymerase II core promoter sequence-specific DNA binding (GO:0000979). These results showed that key targets were involved in different biological functions. According to the P value, the top 5 GO entries in each category were shown in Figure According to the GO annotation analysis, a total of 71 GO enrichment items were significantly obtained , PTGS2(PDB ID: 3nt1), STAT1(PDB ID: 3su6), IGF1(PDB ID: 1wqj), MYC (PDB ID: 7r2h), JUN (PDB ID: 2p33), PRKCA (PDB ID: 4ra4), CAV1(PDB ID: 7luc), MMP1(PDB ID: 3shi) and SELE (PDB ID: 5jha). In addition, the top 5 active ingredients were selected, including quercetin (MOL000098), beta-sitosterol (MOL000359), delta-Carotene (MOL010234), sesamin (MOL001558) and matrine (MOL005944). It was displayed from Table To explore the underlying relationship between clinical symptoms and medication use, we mapped 34 Chinese terms of clinical symptoms corresponding to Zuogui Pill into 56 English terms of phenotypes related to liver cancer. And then, 6 clinical symptoms were successfully mapped, including fever, abdominal pain, loss of appetite, soreness and weakness of waist and knees, burning pain, diarrhea. According to the herb-symptom association network,11 herb-symptom association pairs were detected, such as Shu Di Huang to fever, Shan Yao to loss of appetite, and Tu Si Zi to soreness and weakness of waist and knees. Furthermore, based on herb-target association pairs, the relationship network was built between clinical symptoms and key targets. Subsequently, 60 clinical symptom-target pairs were identified. To elucidate the indirect relationships between TCM symptoms and targets, a heterogeneous key targets-related network was seen in Figure –14 have delved into the molecular mechanism of Zuogui Pill in treating Osteoporosis and Ovarian Dysfunction, and Gao et al further substantiated the multi-target and multi-level synergistic effects of active ingredients in the Zuogui Pill, employing a system biology approach. As we know, the holistic perspective of TCM intrinsically aligns with the systematic viewpoint of bioinformatics. Consequently, the utilization of computational algorithms for the identification of key protein targets and the determination of biological pathways in Chinese formulas has emerged as a prominent research area. In our study, we proposed a novel 2-phase community-identification algorithm that integrated spectral clustering and MCL algorithm. These 2 algorithms have been applying to the identification of modules within real PPI network.,18 As anticipated, ten key targets identified by 5 core modules encompass a substantial portion of biological function associated with Zuogui Pill, combining topological properties of PPI network. These key targets well expressed the essentiality feature for protein-protein interaction, because they were all included in the largest k-clique of each module in PPI network. In addition, these key protein targets revealed different biological functions by using GEO database. Among them, PTGS2 can activate PINK1/Parkin-mediated mitophagy and accelerate apoptosis of Hepatoma cell. FOS, MYC and JUN have been testified to regulate the proliferation and apoptosis of hepatoma cells in present experimental results. Besides, FOS modulated plasticity of epithelial hepatocytes and acted tumor suppressive in neoplastic hepatocytes by stimulating cell cycle inhibition and cell death, IGF1 could inhibit the malignant progression of HCC. It was reported that Hepatitis B virus X protein (HBx) induces hepatocarcinogenesis via PKCα-mediated overexpression of cytoplasmic p21. Furthermore, STAT1 exerts tumor-suppressive effected in hepatocarcinogenesis through induction of G0/G1 cell cycle arrest and apoptosis. These key targets validated the multi-target molecular mechanism for Zuogui Pill in the treatment of liver cancer.Zuogui Pill originated from the work “Jingyue Quanshu” authored by Zhang Zhongjing, a renowned clinician during the Ming Dynasty, and has been widely employed in clinical practice due to its outstanding effect, specifically, to improve clinical symptoms on liver cancer. In recent years, many studies–27 On the other hand, key protein targets tended to have interactions among different key modules. For example, PTGS2, JUN, SELE were all involved in TNF signaling pathway. LPS can trigger the release of inflammatory mediators like PTGS2. Zuo et al demonstrated that Cr (VI) induced PTGS2 expression via an NFκB/c-Jun/AP-1-dependent pathway. Therefore, these key targets have significant correlations within important cancer-related cellular processes. In addition, the analysis of molecular docking showed that the top 5 active ingredients of Zuogui Pill commonly had good binding energy with 10 key targets, results based on combining machine learning and network pharmacology were further verified for detecting key targets. It was suggested that sesamin and quercetin may give full play to the treatment of liver cancer.According to the GO and KEGG enrichment analysis, it was found that key targets played different roles in expressing biological functions. Over 50% of key targets, such as PTGS2, FOS, were involved in Hepatitis B, MAPK signaling pathways, which were closely associated with liver cancer. Furthermore, PRKCA, JUN enriched in most of TOP 10 KEGG pathways, such as IL-17, MAPK, PI3K-Akt signaling pathways. PI3K-Akt and MAPK pathways make a significant impact on regulating the cell cycle, proliferation, apoptosis, and metabolism. Therefore, symptom-gene associations may help to uncover the molecular mechanism for Chinese formula. To elucidate the potential mechanism of Zuogui Pill in treating liver cancer from the perspective of improving symptoms, we mapped the associated symptoms of Zuogui Pill to phenotype terms of liver cancer. It was found that the clinical symptoms treated by Zuogui Pill are similar to the phenotypes of liver cancer. Based on the symptom-gene-herb-signaling pathway associations, particularly, PTGS2 exhibit correlations with fever, the clinical manifestation of liver cancer, thereby suggesting that the administration of Shu Di Huang, a key constituent of Zuogui Pill, may effectively mitigate fever by modulating PTGS2 on IL-17 signaling pathway. Likewise, it was displayed that Shan Yao may improve loss of appetite by regulating FOS via MAPK signaling pathway. Zuogui Pill can improve different clinical symptoms in treating liver cancer, by regulating multiply targets like PTGS2 and FOS, participating in MAPK, IL-17 and TNF signaling pathways.In real-world TCM clinical setting, symptoms provide key information for personalized herb treatment.Nevertheless, some limitations were inevitable in our study. 14 of 345 potential protein targets from ingredients of Zuogui Pill have been omitted, because they had not been found in the present databases related to liver cancer. It was necessary to be included into the further validation for exploring the complicated molecular mechanism of Zuogui Pill, maybe it would help to promote clinical applications in discovering new biological compound.In summary, based on bioinformatics methods, we identified key drug targets of Zuogui Pill and revealed herb-target-symptom network correlations to explore the underlying therapeutic mechanism in the treatment of liver cancer. The results confirmed Zuogui Pill can mitigate clinical symptoms on liver cancer via synthetic mechanism of multi-component, multi-target and multi-pathway, our finding would provide promising evidence for further experimental verification of these hub targets.Data curation: Ruiling Li.Methodology: Xiang Gao, Li Ma.Software: Biao Guang.Visualization: Biao Guang, Ruiling Li.Writing – original draft: Biao Guang, Xiangrong Chen, Li Ma.Writing – review & editing: Li Ma.


Rosenroot (Rhodiola rosea) is a traditional Chinese herbal medicine. It has been used to treat patients with coronary artery disease (CAD). Salidroside is the main active constituent of rosenroot. This study was designed to explore the mechanism of salidroside in treating CAD and its role in angiogenesis in CAD systematically.In this study, potential targets related to salidroside and CAD were obtained from public databases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Disease Ontology (DO) and CellMarker enrichment analyses were performed. The binding of salidroside to angiogenesis-related targets was assessed by PyMOL and Ligplot. Furthermore, the effects of salidroside on collateral circulation were evaluated by correlation analysis of these angiogenesis-related targets with the coronary flow index (CFI), and the influence of salidroside on human umbilical vein endothelial cell (HUVEC) proliferation and migration was assessed.FGF1 , KDR  and HIF1A  were correlated with the coronary flow index (CFI), and salidroside docked well with them. Finally, cell experiments confirmed that salidroside promoted the proliferation and migration of HUVECs.Eighty-three targets intersected between targets of salidroside and CAD. GO and KEGG analyses indicated that salidroside mainly treated CAD through angiogenesis and anti-inflammatory action. There were 12 angiogenesis-related targets of salidroside in coronary heart disease, among which This study revealed the potential molecular mechanism of salidroside on angiogenesis in CAD and provided new ideas for the clinical application of salidroside in the treatment of CAD.The online version contains supplementary material available at 10.1186/s12906-023-04027-3. Coronary artery disease (CAD), also known as coronary atherosclerotic heart disease, is a principal cause of cardiovascular death globally, and the mortality rates of CAD are increasing annually . PercutaRhodiola rosea) is a traditional Chinese herbal medicine and has significant medicinal and health benefits [Rosenroot  was used to find the chemical structure of salidroside. The TCMSP database (https://tcmsp-e.com/) was used to evaluate the pharmacokinetic properties of salidroside, such as oral bioavailability (OB), Caco-2 permeability (Caco-2), and blood–brain barrier (BBB).Using “salidroside” as the search term, the PubChem database (http://www.tcmip.cn/ETCM/), similarity ensemble approach  and STITCH (http://stitch.embl.de/) databases were used. Concurrently, dataset GSE85871 was obtained from the Gene Expression Omnibus  database. This dataset contains RNA sequencing (RNA-seq) data from MCF-7 cells treated with 102 different herbs, including salidroside, to help investigate the potential pharmacological mechanisms and molecular targets of the various herbs [To identify the potential targets for salidroside, the Encyclopedia of Traditional Chinese Medicine  with a score > 0.2, DrugBank (https://www.drugbank.com/), GeneCards (https://www.genecards.org/) with score > 20, The Human Phenotype Ontology , NCBI-gene (https://www.ncbi.nlm.nih.gov/gene/), Online Mendelian Inheritance in Man  and PharmGKB (https://www.pharmgkb.org/) databases using “coronary artery disease”,” coronary heart disease”,” Ischemic heart disease”,” coronary disease” and “coronary occlusion” as search terms. All database results were combined to obtain the CAD-related disease targets.To obtain potential targets associated with CAD, we searched for DisGeNET (https://metascape.org) is a powerful online bioinformatics analysis tool that integrates Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) [Homo sapiens”. GO, KEGG and protein–protein interaction (PPI) network analyses were performed. Meanwhile, key modules were identified by the default algorithm of Metascape. Terms with adjusted P values < 0.05 were collected. Finally, the results were visualized using the ggplot2 package in R software and Cytoscape.Metascape (s (KEGG) –16, The s (KEGG) . The inthttp://xteam.xbio.top/CellMarker/) contains 13,605 cell markers of 467 cell types in 158 human tissues/subtissues and 9148 cell markers of 389 cell types in 81 mouse tissues/subtissues. Marker genes expressed in tissues and cells can be found through the CellMarker database [Salidroside-related targets and targets for the treatment of CAD were further used for CellMarker and DO Analysis. The CellMarker database  , 20 withTo identify the angiogenesis-related genes in salidroside treatment of CAD by crossing the angiogenesis-related genes with the targets of salidroside treatment of CAD. Further, Pearson correlation analysis was performed using the RMA normalized matrix of GSE7638 to evaluate the association between these genes and coronary flow index (CFI) .http://www.rcsb.org/pdb/) [The protein structures of genes related to angiogenesis in salidroside treatment of CAD were downloaded from the Protein Data Bank (rg/pdb/) . The watrg/pdb/) . Pymol2.Human umbilical vascular endothelial cells  were seeded in 96-well plates  at 3000 per well. On Day 2, the medium was exchanged for serum-free medium for 10 h. Then, the control group was cultured with complete medium, and the salidroside group was cultured with complete medium containing 30 μM salidroside. After 24 h, cell proliferation rates were subsequently assessed using the cell counting kit-8  according to the manufacturer’s instructions. The optical density (OD) values at 450 nm and 570 nm were measured. The OD value at 450 nm was subtracted from the OD value at 600 nm to obtain the corrected OD value of each well.A total of 300000 cells/well were plated into a 6-well plate  and incubated to reach confluence. The monolayer was scratched using a 20 μl tip and washed with phosphate buffered saline to remove detached cells. The cells were cultured in serum-free medium supplemented with or without salidroside (30 μM). An inverted microscope  was used to observe the healing of the scratches 24 h later, and the results were treated with ImageJ.P < 0.05 was considered statistically significant.All experiments were independently repeated 3 times. Statistical analysis was carried out using the GraphPad Prism 7.0 statistical software package, and The 2D structure of salidroside was downloaded from PubChem  and KDR  but negatively correlated with HIF1A . The detailed results are shown in Fig. Twenty-five gene sets related to angiogenesis were found in misgdb, containing a total of 463 genes (Supplementary Table P < 0.01, Fig. To verify the effect of salidroside on HUVECs, CCK-8 and wound healing assays were performed. Our results indicated that 30 μM salidroside significantly increased the capacity to proliferate and migrate HUVECs compared with the control group (The pathophysiological mechanisms of CAD are complex. It is well known that CAD is a chronic inflammatory disease. Several proinflammatory cytokines, such as IL-6, IL-18, TNF-α and C-reactive protein, have been reported to be independently associated with the risk of coronary heart disease , 25. In The enrichment analysis of salidroside in the treatment of CAD suggests that salidroside can regulate inflammatory biological processes, such as leukocyte apoptotic process, leukocyte migration, and inflammatory response in the treatment of CAD, which is consistent with the pharmacological mechanism of salidroside . SalidroMore intriguingly, many biological processes and signaling pathways related to angiogenesis were enriched in the enrichment analysis. Angiogenesis is the formation of new blood vessels. In the process of angiogenesis, endothelial cells proliferate, migrate and assemble to form tubular structures and then recruit smooth muscle cells and parietal cells to form mature blood vessels , 32. HigVEGF, HIF1A and KDR were correlated with coronary artery collateral circulation. In addition, cell experiments also confirmed that salidroside can promote the proliferation and migration of HUVECs. In conclusion, we believe that salidroside plays an important role in angiogenesis and collateral circulation in CAD. Due to the limited efficacy of proangiogenic therapy, salidroside as a complementary therapy may play a synergistic role in promoting angiogenesis in CAD.Actually, salidroside has been shown to promote angiogenesis significantly. It has been.reported that salidroside can increase the expression of VEGF and NO, thus promoting the angiogenesis mediated by bone marrow-derived endothelial progenitor cells . SalidroOur study also has some limitations. First, we only tested the effect of salidroside on the proliferation and migration of HUVECs, even though some literatures also adopted the same method , 42. HowOverall, in this study, the pharmacological mechanism of salidroside in CAD was investigated using network pharmacology and experimental methods. Salidroside may improves angiogenesis and collateral circulation in patients with CAD by regulating VEGF, HIF1A and KDR and other angiogenesis-related factors. However, the final mechanism needs to be further verified by subsequent experiments.Additional file 1:Supplementary Table 1. Targets of salidroside, CAD, and salidroside in the treatment of CAD.Additional file 2:Supplementary Table 2. Enrichment analysis of salidroside-related targets and targets for treatment of CAD.Additional file 3:Supplementary Table 3. Twenty-five gene sets and genes related to angiogenesis in MSigDB.