Dataset Information

Identifying the Mechanism of Polygoni Cuspidati Rhizoma et Radix in Treating Acute Liver Failure Based on Network Pharmacology and Molecular Docking.

ABSTRACT:

Materials and methods

The potential bioactive compounds of PCRR and their targets were collected from TCMSP, TCMID, and BATMAN-TCM databases with absorption, distribution, metabolism, and excretion protocols (oral bioavailability ≥30% and drug-likeness ≥0.18). The ALF-related target genes were identified using the GeneCards and OMIM databases. A protein-protein interaction (PPI) network among these targets was constructed using the Cytoscape software to obtain the core targets. The genes associated with ALF were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify the signaling pathways related to the therapeutic effect of PCRR in ALF.

Results

In total, 10 bioactive compounds of PCRR and 200 targets related to them were obtained, and 2913 ALF-related target genes were identified. PPI network analysis pinpointed 15 core targets, namely, TP53, AKT1, JUN, HSP90AA1, MAPK1, RELA, TNF, ESR1, IL6, MYC, MAPK14, FOS, RB1, CDKN1A, and EGFR. GO enrichment and KEGG pathway analyses revealed that the therapeutic mechanisms of PCRR in ALF are related to cell metabolism, oxidative stress, inflammation, and hepatocyte apoptosis.

Conclusion

This is the first study to explore the therapeutic mechanisms of PCRR in ALF via network pharmacology and molecular docking. This study provides a research platform with candidate ALF-related targets of PRCC for the development of therapeutics against ALF.

SUBMITTER: Hong J

PROVIDER: S-EPMC9012611 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.