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Network Pharmacology-Based Prediction and Pharmacological Validation of Effects of Astragali Radix on Acetaminophen-Induced Liver Injury.

ABSTRACT: Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology-based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR-ALI crossover proteins, corresponding to 49 genes, were filtered into a protein-protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, MYC, MAPK8, and CXCL8 were highly associated with apoptosis in ALI. Then in vitro and in vivo experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of MYC (c-Myc), MAPK8 (JNK1), and CXCL8 (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.

SUBMITTER: Peng Y

PROVIDER: S-EPMC9289209 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Traumatic brain injury (TBI) is a critical public health and socioeconomic problem worldwide. The herb pair Astragali Radix (AR)-Radix Angelica Sinensis (RAS) is a common prescribed herbal formula or is added to other Chinese medicine prescriptions for traumatic brain injury (TBI) treatment. However, the underlying mechanisms are unclear. In this study, we aimed to explore the active ingredients and action targets of AR-RAS based on the combined methods of network pharmacology prediction and experimental verification. Furthermore, the corresponding potential mechanisms of "multicomponents, multitargets, and multipathways" were disclosed. Methods. A network pharmacology approach including ADME (absorption, distribution, metabolism, and excretion) filter analysis, target prediction, known therapeutic targets collection, Gene Ontology (GO), pathway enrichment analysis, and network construction was used in this study. Further verification experiments were performed to reveal the therapeutic effects of AR-RAS in a rat model of TBI. Results. The comprehensive systematic approach was to successfully identify 14 bioactive ingredients in AR-RAS, while 33 potential targets hit by these ingredients related to TBI. Based on GO annotation analysis, multiple biological processes were significantly regulated by AR-RAS. In addition, 89 novel signaling pathways (P<0.05) underlying the effects of AR-RAS for TBI treatment were identified by DAVID. The neurotrophin signaling pathway was suggested as the major related pathway targeted by AR-RAS to improve axonal growth. The animal experiment confirmed that AR-RAS significantly induced tissue recovery and improved neurological deficits on the 14th day (P<0.01). Treatment with AR-RAS markedly reduced the protein and mRNA expression level of NogoA in the hippocampus of TBI rats. Conclusion. Our work illuminates the "multicompounds, multitargets, and multipathways" curative action of AR-RAS in the treatment of TBI by network pharmacology. The animal experiment verifies the effects of AR-RAS on neurological function improvement and axonal outgrowth via downregulation of NogoA expression, providing a theoretical basis for further research on treatment of TBI.

Project description:According to current research, the primary active ingredients of Radix Astragali (RA), such as saponins, flavonoids, and polysaccharides, play an important role in anti-inflammatory effects. However, the exact molecular mechanism underlying the action was not elucidated to date. Our research attempted to determine the active components in RA and to investigate the interaction between the active components and targets involved in the anti-inflammation activity by network pharmacology and molecular docking. The active components and targets of RA were screened out by TCMSP. Thereafter, through the "anti-inflammation effect" and "inflammation" as the keywords, disease targets were obtained from the GeneCards database. The PPI network was constructed with Cytoscape 3.8.0 software to screen core targets. The GO function and KEGG analysis were enriched and analyzed through the Metascape platform, obtaining the 3-dimensional view of the core targets from the PDB database, and then, performing molecular docking in AutoDock Vina, a heatmap was constructed using the binding free energies in GraphPad Prism 8. The Discovery Studio software was used for docking analysis, and eventually, the docking results were visualized. We also explored the targets and signaling pathways of Astragaloside IV acting on anti-inflammatory effects via constructing compound-disease-target-pathway network. 18 active components and 45 targets of RA were screened out. The main anti-inflammatory active components of RA were quercetin, Astragaloside IV, kaempferol, 7-O-methylisomucronulatol, and formononetin, and the strongly interacting core proteins were TNF, IL6, IL1B, TLR4, CXCL8, CCL2, IL10, VEGFA, and MMP9. The signal pathways mainly involved include Lipid and atherosclerosis, IL-17 signaling pathway, Chagas disease, leishmaniasis, and TNF signaling pathway. Moreover, molecular docking showed that the 2 most active compounds, Astragaloside IV and kaempferol, could efficiently bind with the targets TNF, TLR4, and IL10. Astragaloside IV may play a part in anti-inflammatory effects through pathways such as HIF-1 signaling pathway, Inflammatory bowel disease and Hepatitis B ect. RA exhibits the characteristic of multicomponent and multitarget synergistic effects in exerting anti-inflammatory effects and the effective component of RA is Astragaloside IV, targeting TNF, TLR4, and IL10.

Project description:Background:Astragali Radix (AR) is widely-used for improving liver fibrosis, but, the mechanism of action has not been systematically explained. This study aims to investigate the mechanism of AR intervention in liver fibrosis based on comprehensive metabolomics combined with network pharmacology approach. Materials and methods:UPLC-Q-TOF/MS based metabolomics technique was used to explore the specific metabolites and possible pathways of AR affecting the pathological process of liver fibrosis. Network pharmacology analysis was introduced to explore the key targets of AR regarding the mechanisms on liver fibrosis. Results:AR significantly reduced the levels of ALT, AST and AKP in serum, and improved pathological characteristics. Metabolomics analysis showed that the therapeutic effect of AR was mainly related to the regulation of nine metabolites, including sphingosine, 6-keto-prostaglandin F1a, LysoPC (O-18:0), 3-dehydrosphinganine, 5,6-epoxy-8,11,14-eicosatrienoic acid, leukotriene C4, taurochenodesoxycholic acid, LysoPC (18:1 (9Z)) and 2-acetyl-1-alkyl-sn-glycero-3-phosphocholine. Pathway analysis indicated that the treatment of AR on liver fibrosis was related to arachidonic acid metabolism, ether lipid metabolism, sphingolipid metabolism, glycerophospholipid metabolism and primary bile acid biosynthesis. Validation of the key targets by network pharmacology analysis of potential metabolic markers showed that AR significantly down-regulated the expression of CYP1B1 and up-regulated the expression of CYP1A2 and PCYT1A. Conclusion:Metabolomics combined with network pharmacology was used for the first time to clarify that the treatment of AR on liver fibrosis, which is related to the regulation of arachidonic acid metabolism and ether lipid metabolism by modulating the expression of CYP1A2, CYP1B1 and PCYT1A. And the integrated approach can provide new strategies and ideas for the study of molecular mechanisms of traditional Chinese medicines in the treatment of liver fibrosis.

Project description:BackgroundAstragali Radix-Curcumae Rhizoma (ARCR), a classic drug pair, has been widely used for the treatment of gastric intraepithelial neoplasia (GIN) in China. However, the underlying mechanisms of this drug pair are still unknown. Thus, elucidating the molecular mechanism of ARCR for treating GIN is imperative.MethodsThe active components and targets of ARCR were determined from the TCMSP database, and the differentially expressed genes related to GIN were identified from the GSE130823 dataset. The protein-protein interaction (PPI) network and ARCR-active component-target-pathway network were constructed by STRING 11.0 and Cytoscape 3.7.2, respectively. In addition, a receiver operating characteristic curve (ROC) was conducted to verify the key targets, and enrichment analyses were performed using R software. Molecular docking was carried out to test the binding capacity between core active components and key targets.Results31 active components were obtained from ARCR, among which 22 were hit by the 51 targets associated with GIN. Gene Ontology (GO) functional enrichment analysis showed that biological process (BP), molecular function (MF), and cellular component (CC) were most significantly enriched in response to a drug, catecholamine binding, and apical part of the cell, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated ARCR against GIN through regulation of neuroactive ligand-receptor interaction, nitrogen metabolism, calcium signaling pathway, chemical carcinogenesis-receptor activation, drug metabolism, gap junction, and cancers. In the PPI network, 15 potential targets were identified, of which nine key targets were proven to have higher diagnostic values in ROC. Molecular docking revealed a good binding affinity of active components (quercetin, bisdemethoxycurcumin, and kaempferol) with the corresponding targets (CYP3A4, CYP1A1, HMOX1, DRD2, DPP4, ADRA2A, ADRA2C, NR1I2, and LGALS4).ConclusionThis study revealed the active components and molecular mechanism by which ARCR treatment is effective against GIN through regulating multipathway, such as neuroactive ligand-receptor interaction, nitrogen metabolism, and calcium signaling pathway.

Project description:BackgroundKeyin pill (KP), a patented medicine in China, is used to treat psoriasis. However, KP has been reported to have liver toxicity, but its toxic substance basis and underlying mechanisms remain unclear. Therefore, this study aimed to explore the pharmacological mechanisms and components of KP-induced liver injury through animal experiments, UPLC-QTOF/MS combined with network pharmacology.MethodsFirstly, based on the immune stress mouse model, liver function parameters and hematoxylin-eosin (H&E) staining were detected to investigate KP-induced liver injury. The UPLC-QTOF/MS method was used to identify the components of KP. CTD database and literature mining were further applied to screen nonliver protective components. Subsequently, the nonliver protective components and their corresponding targets and targets of hepatotoxicity were analyzed by the method of network pharmacology. Finally, key targets from networked pharmacology were examined by the enzyme-linked immunosorbent assay (ELISA) and molecular docking.ResultsOur results indicated that KP had hepatotoxicity in male Kunming mice, which could favor hepatocyte necrosis and infiltration of inflammatory cells. A total of 70 nonliver protective compounds were identified and screened. The results of network pharmacology illustrated that methoxsalen, obacunone, limonin, and dictamnine might be the main compounds that caused liver damage. The potential hepatotoxicity mechanisms of KP might be through the IL17 and apoptosis pathways to regulate IL6, TNFα, CASP3, and CASP8 targets, thereby causing inflammation, excessive release of factors, and hepatocyte necrosis. The results of the ELISA experiments indicated that KP could increase the release of IL6 and TNFα inflammatory factors in liver tissues. Molecular docking suggested that methoxsalen, obacunone, limonin, and dictamnine had moderate binding ability with CASP3 and CASP8.ConclusionIn this study, the material basis and potential pharmacological mechanisms of KP-induced liver injury were preliminarily explored. Our research provides the initial theoretical basis for reducing the toxicity of KP.

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Network Pharmacology-Based Prediction and Pharmacological Validation of Effects of Astragali Radix on Acetaminophen-Induced Liver Injury.

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