Research of the mechanism of Huganning tablet in the treatment of nonalcoholic fatty liver disease based on network pharmacology and computer-aided drug design
10.16438/j.0513-4870.2022-1046
- VernacularTitle:基于网络药理学及计算机辅助药物设计研究护肝宁片治疗非酒精性脂肪性肝病的作用机制
- Author:
Cong CHEN
;
Xiang-hui ZHOU
;
Bing ZHANG
;
Yan-fen PENG
;
Xin-ping YANG
;
Qi-ming YU
;
Xiang-duan TAN
- Publication Type:Research Article
- Keywords:
Huganning tablet;
nonalcoholic fatty liver disease;
network pharmacology;
computer-aided drug design;
mechanism
- From:
Acta Pharmaceutica Sinica
2023;58(3):695-710
- CountryChina
- Language:Chinese
-
Abstract:
In this study, we explored the mechanism of Huganning tablet (HGNP) in the treatment of nonalcoholic fatty liver disease (NAFLD) based on network pharmacology and computer-aided drug design. Firstly, the potential ingredients and targets of HGNP were identified from TCMSP database, Swiss Target Prediction database, Chinese pharmacopoeia (2015) and literatures, and then the targets of HGNP intersected with NAFLD disease targets that obtained in GeneCards database to acquired potential targets. The bioconductor bioinformatics package of R software was used for gene ontology (GO) enrichment and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis. The network of “potential ingredient-key target-pathway” was formed in Cytoscape software to study the interactions between potential ingredients of HGNP, key targets, pathways and NAFLD. Based on the results of network pharmacology, the molecular docking analysis of the key targets and potential active ingredients in HGNP tablets with top degree in the network was conducted using Discovery Studio 2020 software, followed by molecular dynamics simulations, binding free energy calculation, drug-likeness properties analysis and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties prediction. In vitro, HepG2 cells were used to establish steatosis model, and the effects of five key compounds on hepatocyte steatosis were analyzed by oil red O staining and triglyceride (TG) content determination. The results showed that 141 ingredients and 151 potential targets were obtained. A total of 2 526 items and 151 pathways were identified by GO and KEGG enrichment analysis. The molecular docking suggested that five components, isorhamnetin, salvianolic acid B, emodin, resveratrol and rhein, exhibited strong binding ability with key targets [retinoic acid receptor RXR-alpha (RXRA), tumor necrosis factor (TNF), glycogen synthase kinase-3 beta (GSK3B), serine/threonine-protein kinase 1 (AKT1)]. It was further verified that isorhamnetin and salvianolic acid B bind to key targets with good structural stability and binding affinity based on molecular dynamics simulations and binding free energy calculations. The drug-likeness properties, pharmacokinetic properties and toxicity of five key compounds were more comprehensively analyzed through drug-likeness properties analysis and ADMET properties prediction. In vitro, all five compounds, isorhamnetin, salvianolic acid B, emodin, resveratrol, and rhein, improved hepatocyte steatosis of HepG2 cells, confirming the reliability of the present study. In conclusion, based on network pharmacology, computer-aided drug design and in vitro validation, this study investigated the mechanism of HGNP for the treatment of NAFLD at multiple levels and provided a basis for its clinical application.