While Yinma Jiedu Granules are frequently employed for Acute bronchitis treatment, research on their network pharmacology and molecular docking remains scarce. Utilizing network pharmacology and molecular docking techniques, this study forecasts potential targets and signaling routes for Yinma Jiedu Granules in managing Acute bronchitis. The active components and related targets of Yinma Jiedu Granules were obtained by TCMSP, GeneCards and UniProt. GeneCards, DrugBank and OMIM were used to obtain targets related to Acute bronchitis. By merging the STRING database, the network of protein interactions was created, and the PPI network linking Yinma Jiedu Granule and Acute bronchitis was established using the Cytoscape v3.8.2 software. GO bioinformatics analysis and KEGG pathway enrichment analysis on intersecting genes were conducted using the David database, and the bubble map and histogram were made using the micro-bioinformatics platform and RStudio software. The key targets were verified by molecular docking with the main active components by AutoDockTools 1.5.7, Pymol, BatchDocking and LigPlus software. Findings indicated that employing Oral Bioavailability and Drug Likeness for screening led to the acquisition of 117 active elements, 154 genes intersecting drug-disease, and 111 primary targets. The KEGG enrichment study forecasted that Yinma Jiedu Granules' therapy for Acute bronchitis primarily targeted advanced glycation end products, including receptor and TNF signaling pathways, IL-17 signaling pathways, among others. Molecular docking outcomes verified that Yinma Jiedu Granules' primary active elements, quercetin and luteolin, maintained a consistent binding affinity with key targets STAT3 and HSP90AA1.
Bipolar disorder (BD), which also refers to manic-depressive disease, often synchronously develops accompanying mental disorder, endocrine, and long-term awful physical conditions and has a poor prognosis, making bipolar disorder a significant public health problem and a global disease burden. The disorder is highly heritable and has been shown to be genetically linked. Identifying and screening major molecular markers for therapeutic targeting has become a global concern. This paper aims to use a bioinformatics approach to screen genes included in the pathogenesis of bipolar affective disorder and to analyze their signaling pathways. In this study, mRNA expression profiles in the orbitofrontal cortex (GSE5389) and dorsolateral brain tissue (GSE5388) obtained from the GEO public database on the National Center for Biological Information (NCBI) website were employed in order to detect and analyze differentially expressed genes (DEGs) in the normal and disease groups adopting the limma package with the R language, followed by an application of Metascape database for GO and KEGG signaling pathway analysis and WGCNA package for GSE5389 for weighted gene co-expression network analysis in order to acquire the relevant modules as well as crucial genes relation. It was shown that patients with bipolar disorder, genes included in the development of neuronal cell development, cell agglutination, immune signaling, and glial cell regeneration are dysregulated.
Objectives: By the ways of Network Pharmacology and Molecular Docking Technology,researching the potential targets and the mechanism of action of proanthocyanidins combined with Allicin against atherosclerosis(AS). Methods: Searching in the Genecards database, collect the targets of Proanthocyanidins, Allicin and AS and try to analyse the common targets of them. Import the common targets of Proanthocyanidins, Allicin and AS into the web platform called Venny2.1.0 and get the Venn diagram; then after importing the intersecting targets that we got into the STRING database to build up the PPI net, beautify the PPT net by the Cytoscape software which could lead to the target nets of “Medicine and Disease.” Import the targets of how the medicines is used to treat the AS which is analyzed before into the web platform Metascape to perform GO and KEGG enrichment of analysismedicines and diseases. Make use of vina, pymol, ligplot and GROMACS software to perform the Docking validation and Molecular dynamics studies about the affinities among the medicine ingredient targets and core AS targets. Results: The key targets of Proanthocyanidins combined with Allicin against the relevant proteins of AS include Jun proto-oncogene(JUN), epidermal growth factor receptor(EGFR), mitogen-activated protein kinase 3(MAPK3), tumor necrosis factor (TNF), interleukin 6(IL6) and vascular endothelial growth factor A (VEGFA), etc. According to the enrichment analyses of GO, we find 2 pathways: GO:0000302 response to reactive oxygen species and GO:0009725:response to hormone; According to the enrichment analyses of KEGG, we find that AS closely relates to cancer, Lipids and Fluid shear stress. Docking validation and Molecular dynamics studies show that Proanthocyanidins combined with Allicin are capable to stably combine with eNOS and TNF-α. Conclusion: Proanthocyanidins combined with Allicin can fight against AS by IL-6, TNF, VEGF and JUN and other core targets. Meanwhile, by the pathways of Cancers, Lipids and Fluid shear stress.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.