Mechanism underlying effect of Chaihu Shugan San on major depressive disorder: a network pharmacology-based study.

OBJECTIVE: To investigate the mechanism underpinning the effect of Chaihu Shugan San ( CHSGS) on major depressive disorder (MDD). METHODS: We searched the compound components of from seven herbal ingredients of CHSGS from TCMSP, SymMap, ETCM, NPASS databases, and the chemical structure of the compound from PubChem, and collected the compound targets from TCMSP and TargetNet databases, and MDD-related targets from DiseaseGene Network. We established protein-protein interaction in the STRING database. Through gene mapping, topology analysis and enrichment analysis, the core targets and pathways of CHSGS for MDD, and the involved biological processes (BP), cell components (CC), and molecular functions (MF) were predicted. RESULTS: We collected a total of 1135 CHSGS compounds. After screening by ADME standards and the five rules of Ribinski, we obtained 99 different chemical components with different chemical structures, and related targets of 183 different CHSGS compounds. In the DiseaseGene Network, a total of 740 relevant targets for MDD were collected. Through gene mapping and topological analysis, 62 related targets of CHSGS for MDD, 24 targets with topological Chinese herbal medicine were obtained. Through enrichment analysis, 10 relevant pathways and 3 core pathways were obtained with the involvement of 127 BP, 27 CC, and 43 MF. CONCLUSION: There are multiple targets and signaling pathways are involved in the action of CHSGS in the treatment of MDD.

Network pharmacology assessment of Qingkailing injection treatment of cholestatic hepatitis.

OBJECTIVE: To investigate the targets and mechanisms of action of Qingkailing injection (，QKL) in the treatment of cholestatic hepatitis. METHODS: A network pharmacology method was implemented using drug and disease databases to target QKL and cholestasis hepatitis, respectively. The functional protein association network STRING database was used to construct a protein-protein interaction network using R language and the Bioconductor toolkit. The org.Hs.eg.db and clusterProfiler packages were used for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, which explored biological functions and pathways of potential targets. Targets were then visualized using Cytoscape 3.6.0 software. RESULTS: We screened 121 compounds in QKL and identified 112 targets for the treatment of cholestatic hepatitis. QKL played a role in the treatment of cholestatic hepatitis through 305 biology process terms, 15 cellular component and 29 molecular function terms. The mechanism of QKL action was mainly related to tumor necrosis factor, mitogen-activated protein kinase, and PI3K-Akt signaling pathways. CONCLUSION: The treatment of cholestatic hepatitis by QKL involved multiple targets, biological functions, and signaling pathways that are closely associated with the disease.

Network Pharmacology and Bioinformatics Approach Reveals the Therapeutic Mechanism of Action of Baicalein in Hepatocellular Carcinoma.

Liver cancer is the fourth leading cause of cancer death worldwide, and hepatocellular carcinoma (HCC) accounts for the greatest proportion of these deaths. Baicalein, a flavonoid isolated from the root of Scutellariae radix, is considered a potential candidate to treat HCC. However, the underlying molecular mechanisms remain poorly understood. In the present study, a network pharmacological approach was combined with microarray data (GSE95504) acquired from the Gene Expression Omnibus database to reveal the therapeutic mechanisms of action of baicalein at a systemic level. We identified 38 baicalein targets and 76 differently expressed genes (DEGs) following treatment with baicalein, including 55 upregulated and 21 downregulated genes. The DEGs were significantly enriched in the biological functions of apoptosis, endoplasmic reticulum stress, and PERK-mediated unfolded protein response. Protein-protein interaction (PPI) network construction and topological screening revealed a core module of PPIs including two baicalein targets, TP53 and CDK1, and two downregulated DEGs, HSPA1A and HSPA1B. Expression and survival data for these genes in the module derived from Gene Expression Profiling Interactive Analysis (GEPIA) were subjected to Kaplan-Meier analysis of overall survival and disease-free survival. Overexpression of CDK1, BRCA1, TUBB, HSPA1A, HSPA1B, and HSPA4 was associated with significantly worse overall survival, while overexpression of CDK1, CLU7, BRCA1, and TUBB was associated with significantly worse disease-free survival. These data suggest that baicalein exerts therapeutic effects against HCC via a PPI network involving TP53, CDK1, HSPA1A, and HSPA1B.