Network pharmacology and molecular docking to explore Polygoni Cuspidati Rhizoma et Radix treatment for acute lung injury

BACKGROUNDPolygoni Cuspidati Rhizoma et Radix (PCRR), a well-known traditional Chinese medicine (TCM), inhibits inflammation associated with various human diseases. However, the anti-inflammatory effects of PCRR in acute lung injury (ALI) and the underlying mechanisms of action remain unclear.AIMTo determine the ingredients related to PCRR for treatment of ALI using multiple databases to obtain potential targets for fishing.METHODSRecognized and candidate active compounds for PCRR were obtained from Traditional Chinese Medicine Systems Pharmacology, STITCH, and PubMed databases. Target ALI databases were built using the Therapeutic Target, DrugBank, DisGeNET, Online Mendelian Inheritance in Man, and Genetic Association databases. Network pharmacology includes network construction, target prediction, topological feature analysis, and enrichment analysis. Bioinformatics resources from the Database for Annotation, Visualization and Integrated Discovery were utilized for gene ontology biological process and Kyoto Encyclopedia of Genes and Genomes network pathway enrichment analysis, and molecular docking techniques were adopted to verify the combination of major active ingredients and core targets.RESULTSThirteen bioactive compounds corresponding to the 433 PCRR targets were identified. In addition, 128 genes were closely associated with ALI, 60 of which overlapped with PCRR targets and were considered therapeutically relevant. Functional enrichment analysis suggested that PCRR exerted its pharmacological effects in ALI by modulating multiple pathways, including the cell cycle, cell apoptosis, drug metabolism, inflammation, and immune modulation. Molecular docking results revealed a strong associative relationship between the active ingredient and core target.CONCLUSIONPCRR alleviates ALI symptoms via molecular mechanisms predicted by network pharmacology. This study proposes a strategy to elucidate the mechanisms of TCM at the network pharmacology level.