Mechanism of Astragalus membranaceus in treatment for vascular dementia based on network pharmacology and molecular docking

Abstract

Objective To investigate the mechanism of Astragalus membranaceus (AM) in the treatment of vascular dementia (VD) by network pharmacology and molecular docking. Methods The active components of AM were collected from TCMSP database, and the targets of active components were predicted in TargetNet database according to the SMILES. The VD targets were collected by GeneCards database, and the common targets of active components and VD was calculated to obtain the potential targets of AM in the treatment of VD. The active components-target network was constructed by Cytoscape 3.9.1 software. The potential targets of AM in the treatment of VD were imported into STRING database to construct protein-protein interaction (PPI) network, which was analyzed to obtain core targets. The core targets were imported into DAVID database to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The molecular docking was performed to assess the affinity of main active components of AM and the corresponding VD core targets via AutoDock software. Results A total of 20 active components of AM were collected, including jaranol, isorhamnetin, isoflavanone, kaempferol and quercetin, and a total of 102 predicted targets were obtained. A total of 3 556 VD targets were screened, 71 common targets of AM and VD were calculated, and 36 core targets were obtained by PPI analysis, including SLC6A4, ESR1, PTGS2, ABCB1 and AR. A total of 187 GO items and 32 KEGG pathways were enriched, mainly focusing on neurological function, hormone signal and angiogenesis. Molecular docking showed good affinity between the main active components of AM and VD core targets. Conclusion AM treats VD mainly by regulating neurological function, hormone signal and angiogenesis.

Keywords

• network pharmacology
• molecular docking
• astragalus membranaceus
• vascular dementia
• molecular mechanism