Network pharmacology study on the mechanism of Qiangzhifang in the treatment of panic disorder

网络药理学研究强之芳治疗惊恐障碍的机制

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Abstract

BACKGROUND: Panic disorder (PD) is a kind of mental illness characterized by the symptom of recurring panic attacks. Qiangzhifang (QZF) is a novel decoction developed by Professor Zhaojun Yan based on a unique system of syndrome differentiation and clinical experience. It has achieved remarkable results after long-term clinical practice, but its mechanism of action is still unclear. This study aims to use network pharmacology and molecular docking to explore the mechanism of QZF in the treatment of PD. METHODS: We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), a literature search, and Encyclopedia of Traditional Chinese Medicine (ETCM) to find active ingredients and targets of QZF. We searched for PD targets in GeneCards, Online Mendelian Inheritance in Man (OMIM), the Comparative Toxicogenomics Database (CTD), and DrugBank. We established a PD target database, constructed a protein-protein interaction (PPI) network, and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis in order to screen possible pathways of action and analyze the mechanism. RESULTS: This study identified 84 effective components of QZF, 691 potential targets, 357 PD targets, and 97 intersectional targets. Enrichment analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) showed that QZF was associated with 118 biological processes (BPs), 18 cellular components (CCs), 35 molecular functions (MFs) [false discovery rate (FDR) <0.01], and 62 pathways (FDR <0.01). QZF mainly acts on its targets AKT1, FOS, and APP through active ingredients such as quercetin, β-sitosterol, 4-(4'-hydroxybenzyloxy)benzyl methyl ether, harmine, 1,7-dimethoxyxanthone, and 1-hydroxy-3,7-dimethoxyxanthone to regulate serotonin, gamma-aminobutyric acid (GABA), cyclic adenosine monophosphate (cAMP), and other signal pathways to treat PD. CONCLUSIONS: Through network pharmacology and molecular docking technology, we predicted the possible mechanism of QZF in the treatment of PD, revealed the interaction targets and potential value of QZF, and provided a basis for its clinical application.

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