Abstract

Nonalcoholic fatty liver disease (NAFLD) is a metabolic disease, the incidence of which increases annually. Shugan Xiaozhi (SGXZ) decoction, a composite traditional Chinese medicinal prescription, has been demonstrated to exert a therapeutic effect on NAFLD. In this study, the potential bioactive ingredients and mechanism of SGXZ decoction against NAFLD were explored via network pharmacology, molecular docking, and molecular dynamics simulation. Compounds in SGXZ decoction were identified and collected from the literature, and the corresponding targets were predicted through the Similarity Ensemble Approach database. Potential targets related to NAFLD were searched on DisGeNET and GeneCards databases. The compound-target-disease and protein-protein interaction (PPI) networks were constructed to recognize key compounds and targets. Functional enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed on the targets. Molecular docking was used to further screen the potent active compounds in SGXZ. Finally, molecular dynamics (MD) simulation was applied to verify and validate the binding between the most potent compound and targets. A total of 31 active compounds and 220 corresponding targets in SGXZ decoction were collected. Moreover, 1,544 targets of NAFLD were obtained, of which 78 targets intersected with the targets of SGXZ decoction. Key compounds and targets were recognized through the compound-target-disease and PPI network. Multiple biological pathways were annotated, including PI3K-Akt, MAPK, insulin resistance, HIF-1, and tryptophan metabolism. Molecular docking showed that gallic acid, chlorogenic acid and isochlorogenic acid A could combine with the key targets. Molecular dynamics simulations suggested that isochlorogenic acid A might potentially bind directly with RELA, IL-6, VEGFA, and MMP9 in the regulation of PI3K-Akt signaling pathway. This study investigated the active substances and key targets of SGXZ decoction in the regulation of multiple-pathways based on network pharmacology and computational approaches, providing a theoretical basis for further pharmacological research into the potential mechanism of SGXZ in NAFLD.

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