Prediction of the mechanism of ampelopsin in improving acute lung injury based on network pharmacology and experimental verification

Published: 18 February 2025| Version 1 | DOI: 10.17632/8529f7gbn9.1
Contributors:
Chaohui Yan,
,

Description

Swiss Target Prediction, Traditional Chinese Medicine Systems Pharmacology (TCMSP), DisGeNET and GeneCards databases were used to predict the targets of APS to improve ALI. Potential targets were imported into the Metascape database to perform protein - protein interaction network (PPI), Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses respectively, then build "drugs - targets - disease - access network. Molecular docking with APS and key targets by PyMOL and AutoDock. Validation experiments were conducted using a lipopolysaccharide (LPS)-induced ALI mouse (KM mice) model, LPS-induced inflammatory A549cells, and molecular docking between active compounds of APS and potential targets.

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Institutions

  • GuangXi University of Chinese Medicine

Categories

Animal Research, Networking

Funders

  • Guangxi Municipal Natural Science Foundation
    Grant ID: 2020GXNSFDA238028
  • National Administration of Traditional Chinese Medicine (Chinese medicine preparation technology inheritance base
    Grant ID: [2022] #9

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