Immunoregulatory mechanism studies of ginseng leaves on lung cancer based on network pharmacology and molecular docking

Pharmacological effects and target analysis of Guipi wan in the treatment of cerebral ischemia-reperfusion injury

Guipi wan (GPW) is a traditional Chinese medicine commonly used in clinical practice, typically to treat neurological diseases such as neurasthenia and traumatic brain injury. It may have positive effects on cerebral ischemia‒reperfusion injury (cI/R). This study aimed to assess the effects of GPW in a mouse model of cI/R and find its possible targets. C57BL/6J mice were used to establish the cI/R model, and the laser speckle doppler was used to determine the success of the model. GPW was administered intragastrically for 7 days, brain tissue sections were stained with TTC, HE, and TUNEL, Western blot assay was performed to detect the effect of apoptosis-related proteins. Furthermore, we screened active ingredients from the TCM Database and constructed a compound‒target network using the Cytoscape 3.8.0 software. Moreover, we employed protein‒protein interaction and component‒target‒pathway network analyses to determine the potential components of GPW and its target genes, the key target was verified through molecular docking. Finally, we detected the influence of the downstream signaling pathway of the target through Western blot. The results showed that GPW decreased the cerebral infarction area, neurological function scores, and neuronal apoptosis in mice by regulating PI3K/AKT signaling pathway. Network analysis indicated that gamma-aminobutyric acid B receptor 1 (GABBR1) might be a potential target for the treatment of cI/R. Molecular docking indicated that 9 active components in GPW could bind to GABBR1 with desirable binding energy. This study represented the demonstratable effect of GPW in the treatment of cI/R injury and suggested GABBR1 as a potential target using network analysis.

Bioactive components and the molecular mechanism of Shengxian Decoction against lung adenocarcinoma based on network pharmacology and molecular docking

OBJECTIVE

The aim of this study was to identify the active components of Shengxian Decoction (SXT) and to elucidate the multi-component, multi-target, and multi-pathway regulatory mechanisms underlying the efficacy of SXT in treating lung adenocarcinoma (LUAD).

METHODS

The effects of SXT extract on proliferation, migration, and invasion capabilities of human LUAD cells were determined through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), wound healing, and Transwell assays. High-Performance Liquid Chromatography (HPLC) was employed to pinpoint the primary active constituents of SXT. The SXT-active component-target-pathway network and protein-protein interaction (PPI) network were constructed based on network pharmacology. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using DAVID. The clinical significance of key targets was assessed using several external databases, and molecular docking confirmed the binding affinities between key targets and SXT active components.

RESULTS

SXT significantly inhibited the proliferation, migration and invasion of human LUAD cells. HPLC identified and quantified seven active SXT components. Network pharmacology yielded 197 targets, 128 signaling pathways, and 448 GO terms. The PPI network and external validation underscored 13 key targets significantly associated with the influence of SXT on LUAD progression. Molecular docking demonstrated strong interactions between SXT active components and key targets.

CONCLUSION

SXT treats LUAD through a multifaceted approach involving various components, targets, and pathways. This research offers novel insights into the constituents and molecular mechanisms of SXT in LUAD therapy.

Network pharmacological and molecular docking study of the effect of Liu-Wei-Bu-Qi capsule on lung cancer

BACKGROUND

Although Liu-Wei-Bu-Qi capsule (LBC) inhibits tumor progression by improving the physical condition and immunity of patients with lung cancer (LC), its exact mechanism of action is unknown.

AIM

To through compound multi-dimensional network of chemical ingredient-target-disease-target- protein-protein interaction (PPI) network, the principle of action of Chinese medicine prescription was explained from molecular level.

METHODS

Network pharmacology and molecular docking simulations were used to analyze the relationship among the main components, targets, and signaling pathways of LBC in treatment of LC.

RESULTS

From the analysis, 360 LBC active ingredient-related targets and 908 LC-related targets were identified. PPI network analysis of the LBC and LC overlapping targets identified 16 hub genes. Kyoto Encyclopedia of Genes and Genomes analysis suggested that LBC can target the vascular endothelial growth factor signaling pathway, Toll-like receptor signaling pathway, prolactin signaling pathway, FoxO signaling pathway, PI3K-Akt signaling pathway and HIF-1 signaling pathway in the treatment of LC. Molecular docking simulations showed that quercetin had the best affinity for MAPK3, suggesting that quercetin in LBC may play an important role in the treatment of LC.

CONCLUSION

The results showed that the active ingredients in LBC can play a crucial role in the treatment of LC by regulating multiple signaling pathways. These results provide insights into further studies on the mechanism of action of LBC in the treatment of LC.

Identification of the potential regulatory interactions in rheumatoid arthritis through a comprehensive analysis of lncRNA-related ceRNA networks

OBJECTIVE

This study aimed at constructing a network of competing endogenous RNA (ceRNA) in the synovial tissues of rheumatoid arthritis (RA). It seeks to discern potential biomarkers and explore the long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) axes that are intricately linked to the pathophysiological mechanisms underpinning RA, and providing a scientific basis for the pathogenesis and treatment of RA.

METHODS

Microarray data pertaining to RA synovial tissue, GSE103578, GSE128813, and GSE83147, were acquired from the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo ). Conducted to discern both differentially expressed lncRNAs (DELncRNAs) and differentially expressed genes (DEGs). A ceRNA network was obtained through key lncRNAs, key miRNAs, and key genes. Further investigations involved co-expression analyses to uncover the lncRNA-miRNA-mRNA axes contributing to the pathogenesis of RA. To delineate the immune-relevant facets of this axis, we conducted an assessment of key genes, emphasizing those with the most substantial immunological correlations, employing the GeneCards database. Finally, gene set enrichment analysis (GSEA) was executed on the identified key lncRNAs to elucidate their functional implications in RA.

RESULTS

The 2 key lncRNAs, 7 key miRNAs and 6 key genes related to the pathogenesis of RA were obtained, as well as 2 key lncRNA-miRNA-mRNA axes (KRTAP5-AS1-hsa-miR-30b-5p-PNN, XIST-hsa-miR-511-3p/hsa-miR-1277-5p-F2RL1). GSEA of two key lncRNAs obtained biological processes and signaling pathways related to RA synovial lesions.

CONCLUSION

The findings of this investigation hold promise in furnishing a foundational framework and guiding future research endeavors aimed at comprehending the etiology and therapeutic interventions for RA.

Black Ginseng Extract Exerts Potentially Anti-Asthmatic Activity by Inhibiting the Protein Kinase Cθ-Mediated IL-4/STAT6 Signaling Pathway

Asthma is a chronic inflammatory lung disease that causes respiratory difficulties. Black ginseng extract (BGE) has preventative effects on respiratory inflammatory diseases such as asthma. However, the pharmacological mechanisms behind the anti-asthmatic activity of BGE remain unknown. To investigate the anti-asthmatic mechanism of BGE, phorbol 12-myristate 13-acetate plus ionomycin (PMA/Iono)-stimulated mouse EL4 cells and ovalbumin (OVA)-induced mice with allergic airway inflammation were used. Immune cells (eosinophils/macrophages), interleukin (IL)-4, -5, -13, and serum immunoglobulin E (IgE) levels were measured using an enzyme-linked immunosorbent assay. Inflammatory cell recruitment and mucus secretion in the lung tissue were estimated. Protein expression was analyzed via Western blotting, including that of inducible nitric oxide synthase (iNOS) and the activation of protein kinase C theta (PKCθ) and its downstream signaling molecules. BGE decreased T helper (Th)2 cytokines, serum IgE, mucus secretion, and iNOS expression in mice with allergic airway inflammation, thereby providing a protective effect. Moreover, BGE and its major ginsenosides inhibited the production of Th2 cytokines in PMA/Iono-stimulated EL4 cells. In EL4 cells, these outcomes were accompanied by the inactivation of PKCθ and its downstream transcription factors, such as nuclear factor of activated T cells (NFAT), nuclear factor kappa B (NF-κB), activator of transcription 6 (STAT6), and GATA binding protein 3 (GATA3), which are involved in allergic airway inflammation. BGE also inhibited the activation of PKCθ and the abovementioned transcriptional factors in the lung tissue of mice with allergic airway inflammation. These results highlight the potential of BGE as a useful therapeutic and preventative agent for allergic airway inflammatory diseases such as allergic asthma.

Exploring the mechanism of active components from ginseng to manage diabetes mellitus based on network pharmacology and molecular docking

A large body of literature has shown that ginseng had a role in diabetes mellitus management. Ginsenosides are the main active components of ginseng. But what ginsenosides can manage in diabetic are not systematic. The targets of these ginsenosides are still incomplete. Our aim was to identify which ginsenosides can manage diabetes mellitus through network pharmacology and molecular docking. To identify the targets of these ginsenosides. In this work, we retrieved and screened ginsenosides and corresponding diabetes mellitus targets across multiple databases. PPI networks of the genes were constructed using STRING, and the core targets were screened out through topological analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed by using the R language. Finally, molecular docking was performed after bioinformatics analysis for verification. Our research results showed that 28 ginsenosides in ginseng might be against diabetes mellitus by modulating related proteins such as VEGFA, Caspase 3, and TNF-α. Among the 28 ginsenosides, 20(R)-Protopanaxatriol, 20(R)-Protopanaxadiol, and Ginsenoside Rg1 might play a significant role. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis showed that the management of diabetes mellitus by ginsenosides may be related to the positive regulation of reactive oxygen metabolic processes, associated with the insulin signaling pathway, TNF signaling pathway, and AMPK signaling pathway. Molecular docking results and molecular dynamics simulation showed that most ginsenosides could stably bind to the core target, mainly hydrogen bonding and hydrophobic bond. This study suggests the management of ginseng on diabetes mellitus. We believe that our results can contribute to the systematic study of the mechanism of ginsenosides for the management of diabetes mellitus. At the same time, it can provide a theoretical basis for subsequent studies on the management of ginsenosides in diabetes mellitus.