Exploring the mechanism of Ginkgo biloba L. leaves in the treatment of vascular dementia based on network pharmacology, molecular docking, and molecular dynamics simulation.

BACKGROUND

Ginkgo biloba L. leaves (GBLs) play a substantial role in the treatment of vascular dementia (VD); however, the underlying mechanisms of action are unclear.

OBJECTIVE

This study was conducted to investigate the mechanisms of action of GBLs in the treatment of VD through network pharmacology, molecular docking, and molecular dynamics simulations.

METHODS

The active ingredients and related targets of GBLs were screened using the traditional Chinese medicine systems pharmacology, Swiss Target Prediction and GeneCards databases, and the VD-related targets were screened using the OMIM, DrugBank, GeneCards, and DisGeNET databases, and the potential targets were identified using a Venn diagram. We used Cytoscape 3.8.0 software and the STRING platform to construct traditional Chinese medicine-active ingredient-potential target and protein-protein interaction networks, respectively. After gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis of potential targets using the DAVID platform, the binding affinity between key active ingredients and targets was analyzed by molecular docking, and finally, the top 3 proteins-ligand pairs with the best binding were simulated by molecular dynamics to verify the molecular docking results.

RESULTS

A total of 27 active ingredients of GBLs were screened and 274 potential targets involved in the treatment of VD were identified. Quercetin, luteolin, kaempferol, and ginkgolide B were the core ingredients for treatment, and AKT1, TNF, IL6, VEGFA, IL1B, TP53, CASP3, SRC, EGFR, JUN, and EGFR were the main targets of action. The main biological processes involved apoptosis, inflammatory response, cell migration, lipopolysaccharide response, hypoxia response, and aging. PI3K/Akt appeared to be a key signaling pathway for GBLs in the treatment of VD. Molecular docking displayed strong binding affinity between the active ingredients and the targets. Molecular dynamics simulation results further verified the stability of their interactions.

CONCLUSION SUBSECTIONS

This study revealed the potential molecular mechanisms involved in the treatment of VD by GBLs using multi-ingredient, multi-target, and multi-pathway interactions, providing a theoretical basis for the clinical treatment and lead drug development of VD.