Dataset Information

Potential Mechanism of Dingji Fumai Decoction Against Atrial Fibrillation Based on Network Pharmacology, Molecular Docking, and Experimental Verification Integration Strategy.

ABSTRACT: Background: Dingji Fumai Decoction (DFD), a traditional herbal mixture, has been widely used to treat arrhythmia in clinical practice in China. However, the exploration of the active components and underlying mechanism of DFD in treating atrial fibrillation (AF) is still scarce. Methods: Compounds of DFD were collected from TCMSP, ETCM, and literature. The targets of active compounds were explored using SwissTargetPrediction. Meanwhile, targets of AF were collected from DrugBank, TTD, MalaCards, TCMSP, DisGeNET, and OMIM. Then, the H-C-T-D and PPI networks were constructed using STRING and analyzed using CytoNCA. Meanwhile, VarElect was utilized to detect the correlation between targets and diseases. Next, Metascape was employed for systematic analysis of the mechanism of potential targets and protein complexes in treating AF. AutoDock Vina, Pymol, and Discovery Studio were applied for molecular docking. Finally, the main findings were validated through molecular biology experiments. Results: A total of 168 active compounds and 1,093 targets of DFD were collected, and there were 89 shared targets between DFD and AF. H-C-T-D network showed the relationships among DFD, active compounds, targets, and AF. Three functional protein complexes of DFD were extracted from the PPI network. Further systematic analysis revealed that the regulation of cardiac oxidative stress, cardiac inflammation, and cardiac ion channels were the potential mechanism of DFD in treating AF. Addtionally, molecular docking verified the interactions between active compounds and targets. Finally, we found that DFD significantly increased the level of SIRT1 and reduced the levels of ACE, VCAM-1, and IL-6. Conclusions: DFD could be utilized in treating AF through a complicated mechanism, including interactions between related active compounds and targets, promoting the explanation and understanding of the molecular biological mechanism of DFD in the treatment of AF.

SUBMITTER: Liang Y

PROVIDER: S-EPMC8631917 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Objective: We aim at investigating the molecular mechanisms through which the Qingfei Jiedu decoction (QFJDD) regulates PD-L1 expression in lung adenocarcinoma (LUAD). Methods: Bioactive compounds and targets of QFJDD were screened from TCMSP, BATMAN-TCM, and literature. Then, GeneCard, OMIM, PharmGKB, Therapeutic Target, and DrugBank databases were used to identify LUAD-related genes. The protein-protein interaction (PPI) network was constructed using overlapping targets of bioactive compounds in LUAD with the Cytoscape software and STRING database. The potential functions and pathways in which the hub genes were enriched by GO, KEGG, and DAVID pathway analyses. Molecular docking of bioactive compounds and key genes was executed via AutoDock Vina. Qualitative and quantitative analyses of QFJDD were performed using UPLC-Q-TOF-MS and UPLC. Expressions of key genes were determined by qRT-PCR, immunoreactivity score (IRS) of PD-L1 was assessed by immunohistochemistry (IHC), while the CD8+PD-1+T% derived from spleen tissues of Lewis lung cancer (LLC) bearing-mice was calculated using flow cytometry (FCM). Results: A total of 53 bioactive compounds and 288 targets of QFJDD as well as 8151 LUAD associated genes were obtained. Further, six bioactive compounds, including quercetin, luteolin, kaempferol, wogonin, baicalein, and acacetin, and 22 hub genes were identified. The GO analysis showed that the hub genes were mainly enriched in DNA or RNA transcription. KEGG and DAVID pathway analyses revealed that 20 hub genes were primarily enriched in virus, cancer, immune, endocrine, and cardiovascular pathways. The EGFR, JUN, RELA, HIF1A, NFKBIA, AKT1, MAPK1, and MAPK14 hub genes were identified as key genes in PD-L1 expression and PD-1 checkpoint pathway. Moreover, ideal affinity and regions were identified between core compounds and key genes. Notably, QFJDD downregulated EGFR, JUN, RELA, HIF1A, NFKBIA, and CD274 expressions (p < 0.05), while it upregulated AKT1 and MAPK1 (p < 0.05) levels in A549 cells. The PD-L1 IRS of LLC tissue in the QFJDD high dose (Hd) group was lower than model group (p < 0.01). CD8+PD-1+T% was higher in the QFJDD Hd group than in normal and model groups (p < 0.05). Conclusion: QFJDD downregulates PD-L1 expression and increases CD8+PD-1+T% via regulating HIF-1, EGFR, JUN and NFκB signaling pathways. Therefore, QFJDD is a potential treatment option for LUAD.

Project description:BackgroundAsthma is a chronic airway inflammatory disease characterized by airway inflammation, mucus hypersecretion, airway hyper-reactivity. Sanzi Yangqin Decoction (SZYQD) is widely prescribed for asthma treatment. Its anti-asthma activities have been reported in animal model, but the exact mechanism and targets of SZYQD in asthma treatment have not been fully elucidated.MethodsA network pharmacological approach was used to predict the active components, targets, and signalling pathways of SZYQD in asthma, including potential target prediction, protein‒protein interaction (PPI) network construction and analysis, and Gene Ont (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The active ingredients were identified from the SZYQD, and were molecular docked according to the results of network pharmacology. A mouse model of asthma induced by ovalbumin (OVA) and lipopolysaccharide (LPS) was constructed to evaluate the therapeutic effect of SZYQD. Furthermore, the effects of SZYQD and its active ingredients were tested in vitro for regulating inflammation and MUC5AC expression (two main pathophysiologic abnormalities of asthma) in macrophages and airway epithelial cells by using Real-time PCR and western blotting.ResultsA total of 28 active ingredients and 111 HUB genes were screened in the relevant databases, including three key ingredients (luteolin, β-carotene, and Sinapine) and nine core target genes (JUN, CTNNB1, IL10, TP53, AKT1, STAT3, TNF, IL6 and EGFR). KEGG and GO analysis indicated that the potential anti-asthmatic mechanisms of SZYQD were related to PI3K-Akt signalling pathway and response to lipopolysaccharide, etc. In the in vivo asthmatic model, our findings demonstrated that SZYQD exerted a protective effect against asthmatic mice induced by OVA and LPS through the inhibition of inflammation and mucus overproduction. Consistently, cell experiments showed that the SZYQD extract or the key active ingredients luteolin significantly decreased lipopolysaccharide (LPS)-induced IL-6 expression and activation of the NF-κB pathway in macrophages. In addition, SZYQD extract or luteolin inhibited activation of the AKT pathway and expression of MUC5AC induced by EGF in airway epithelial cells.ConclusionThe anti-asthmatic mechanism of SZYQD might be associated with inhibiting inflammation and airway mucus hypersecretion by regulating the NF-κB and AKT signalling pathways as predicted by network pharmacology, which provides more evidence for the application of SZYQD in asthma treatment.

Project description:Neuroinflammation plays an important role in the onset and progression of neurodegenerative diseases. The multicomponent and multitarget approach may provide a practical strategy to address the complex pathological mechanisms of neuroinflammation. This study aimed to develop synergistic herbal compound formulas to attenuate neuroinflammation using integrated network pharmacology, molecular docking, and experimental bioassays. Eight phytochemicals with anti-neuroinflammatory potential were selected in the present study. A compound-gene target-signaling pathway network was constructed to illustrate the mechanisms of action of each phytochemical and the interactions among them at the molecular level. Molecular docking was performed to verify the binding affinity of each phytochemical and its key gene targets. An experimental study was conducted to identify synergistic interactions among the eight phytochemicals, and the associated molecular mechanisms were examined by immunoblotting based on the findings from the network pharmacology analysis. Two paired combinations, andrographolide and 6-shogaol (AN-SG) (IC50 = 2.85 μg/mL), and baicalein-6-shogaol (BA-SG) (IC50 = 3.28 μg/mL), were found to synergistically (combination index <1) inhibit the lipopolysaccharides (LPS)-induced nitric oxide production in microglia N11 cells. Network pharmacology analysis suggested that MAPK14, MAPK8, and NOS3 were the top three relevant gene targets for the three phytochemicals, and molecular docking demonstrated strong binding affinities of the phytochemicals to their coded proteins. Immunoblotting suggested that the AN-SG and BA-SG both showed prominent effects in inhibiting inducible nitric oxide synthase (iNOS) (p < 0.01 and p < 0.05, respectively) and MAPKp-p38 (both p < 0.05) compared with those induced by the LPS stimulation only. The AN-SG combination exhibited greater inhibitions of the protein expressions of iNOS (p < 0.05 vs. individual components), which may partly explain the mechanisms of the synergy observed. This study established a practical approach to developing novel herbal-compound formulations using integrated network pharmacology analysis, molecular docking, and experimental bioassays. The study provides a scientific basis and new insight into the two synergistic combinations against neuroinflammation.

Project description:ObjectiveThe mechanism of action of Sanhua Decoction (SHD) in the treatment of ischemic stroke (IS) was analyzed based on the network pharmacology technology, and the pharmacodynamics and key targets were verified using the rat middle cerebral artery occlusion (MCAO) model.MethodsThe GEO database was used to collect IS-related gene set S D , and DrugBank and TTD databases were used to obtain the therapeutic drug target set S T . IS disease gene set S I was collected from DisGeNET, GeneCards, and OMIM databases. These three different gene sets obtained from various sources were merged, duplicates were removed, and the resulting IS disease gene set S IS was imported into the STRING database to establish the protein-protein interaction (PPI) network. Two methods were used to screen the key targets of IS disease based on the PPI network analysis. The TCMSP database and PubChem were applied to retrieve the main chemical components of SHD, and the ACD/Labs software and the SwissADME online system were utilized for ADMET screening. HitPick, SEA, and SwissTarget Prediction online systems were used to predict the set of potential targets for SHD to treat IS. The predicted set of potential targets and the IS disease gene set were intersected. Subsequently, the set of potential targets for SHD treatment of IS was identified, the target information was confirmed through the UniProt database, and finally, the component-target data set for SHD treatment of IS was obtained. clusterProfiler was used for GO function annotation and KEGG pathway enrichment analysis on the target set of SHD active ingredients. A rat MCAO model was established to evaluate the pharmacodynamics of SHD in the treatment of IS, and Western blot analysis assessed the level of proteins in the related pathways.ResultsThis study obtained 1,009 IS disease gene sets. PPI network analysis identified 12 key targets: AGT, SAA1, KNG1, APP, GNB3, C3, CXCR4, CXCL12, CXCL8, CXCL1, F2, and EDN1. Database analyses retrieved 40 active ingredients and 47 target genes in SHD. The network proximity algorithm was used to optimize the six key components in SHD. KEGG enrichment showed that the signaling pathways related to IS were endocrine resistance, estrogen, TNF signal pathway, and AGEs/RAGE. Compound-disease-target regulatory network analysis showed that AKT1, IL-6, TNF-α, TP53, VEGFA, and APP were related to the treatment of IS with SHD. Animal experiments demonstrated that SHD significantly reduces the neurological function of rat defect symptoms (P < 0.05), the area of cerebral avascular necrosis, and neuronal necrosis while increasing the levels of IL-6 and APP proteins (P < 0.05) and reducing the levels of AKT1 and VEGFA proteins (P < 0.05).ConclusionThe effective components of SHD may regulate multiple signaling pathways through IL-6, APP, AKT1, and VEGFA to reduce brain damage and inflammatory damage and exert a neuroprotective role in the treatment of IS diseases. Thus, this study provides a feasible method to study the pharmacological mechanism of traditional Chinese medicine compound prescriptions and a theoretical basis for the development of SHD into a new drug for IS treatment.

Dataset Information

Potential Mechanism of Dingji Fumai Decoction Against Atrial Fibrillation Based on Network Pharmacology, Molecular Docking, and Experimental Verification Integration Strategy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets