School of Pharmacy, Shaanxi University of Traditional Chinese Medicine, Xianyang, Shaanxi 712046, China.
Department of Mathematics and Physics, Pharmacy School, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
Biomed Res Int. 2020 Nov 4;2020:1704960. doi: 10.1155/2020/1704960. eCollection 2020.
To use network pharmacology and molecular docking technology in predicting the main active ingredients and targets of Qushi Huayu Decoction (QHD) treatment in Nonalcoholic Fatty Liver Disease (NAFLD) and explore the potential mechanisms of its multi-component-multi-target-multi-pathway.
The main chemical components of QHD were searched using traditional Chinese medicine system pharmacology technology platform (TCMSP) and PubChem database. The main chemical components of the prescription were ADMET screened by the ACD/Labs software. The main active ingredient was screened by 60% oral bioavailability, and 60% of "bad" ingredients were removed from the drug-like group. Swiss Target Prediction, the SEA, and HitPick systems were sequentially used to search for the target of each active ingredient, and a network map of the QHD's target of the active ingredient was constructed. Genome annotation database platforms (GeneCards, OMIM, and DisGeNET) were used to predict action targets related to fatty liver disease. "Drug-Disease-Target" network diagram could be visualized with the help of Cytoscape (3.7.1) software. UniProt and STRING database platforms were used to build a protein interaction network. The KEGG signal pathway and DAVID platform were analyzed for biological process enrichment.
A total of 128 active ingredients and 275 corresponding targets in QHD were discovered through screening. 55 key target targets and 27 important signaling pathways were screened, such as the cancer pathway, P13K-AKT signaling pathway, PPAR signaling pathway, and other related signaling pathways.
The present study revealed the material basis of QHD and discussed the pharmacological mechanism of QHD in fatty liver, thus providing a scientific basis for the clinical application and experimental research of QHD in the future.
运用网络药理学和分子对接技术预测祛湿化瘀汤（QHD）治疗非酒精性脂肪性肝病（NAFLD）的主要活性成分和靶点，探讨其多成分-多靶点-多途径的潜在作用机制。
利用中药系统药理学技术平台（TCMSP）和 PubChem 数据库检索 QHD 的主要化学成分，ACD/Labs 软件对处方的主要化学成分进行 ADMET 筛选，采用 60%口服生物利用度筛选主要活性成分，并将“差”成分从药物样组中去除。依次使用 Swiss Target Prediction、SEA 和 HitPick 系统搜索各活性成分的靶点，构建 QHD 活性成分的靶点网络图谱。利用基因组注释数据库平台（GeneCards、OMIM 和 DisGeNET）预测与脂肪肝相关的作用靶点。借助 Cytoscape（3.7.1）软件可视化“药物-疾病-靶点”网络图。利用 UniProt 和 STRING 数据库平台构建蛋白质相互作用网络。采用 KEGG 信号通路和 DAVID 平台进行生物过程富集分析。
通过筛选，发现 QHD 中共有 128 种活性成分和 275 个对应靶点。筛选出 55 个关键靶标和 27 个重要信号通路，如癌症通路、P13K-AKT 信号通路、PPAR 信号通路等相关信号通路。
本研究揭示了 QHD 的物质基础，探讨了 QHD 治疗脂肪肝的药理机制，为 QHD 未来的临床应用和实验研究提供了科学依据。
