Ginger has been reported to potentially treat Alzheimer's disease (AD), but the specific compounds responsible for this biological function and their mechanisms are still unknown. In this study, a combination of network pharmacology, molecular docking, and dynamic simulation technology was used to screen active substances that regulate AD and explore their mechanisms. The TCMSP, GeneCards, OMIM, and DisGeNET databases were utilized to obtain 95 cross-targets related to ginger's active ingredients and AD as key targets. A functional enrichment analysis revealed that the pathways in which ginger's active substances may be involved in regulating AD include response to exogenous stimuli, response to oxidative stress, response to toxic substances, and lipid metabolism, among others. Furthermore, a drug-active ingredient-key target interaction network diagram was constructed, highlighting that 6-Gingerol is associated with 16 key targets. Additionally, a protein-protein interaction (PPI) network was mapped for the key targets, and HUB genes ( ALB , ACTB , GAPDH , CASP3 , and CAT ) were identified. Based on the results of network pharmacology and cell experiments, 6-Gingerol was selected as the active ingredient for further investigation. Molecular docking was performed between 6-Gingerol and its 16 key targets, and the top three proteins with the strongest binding affinities ( ACHE , MMP2 , and PTGS2 ) were chosen for molecular dynamics analysis together with the CASP3 protein as the HUB gene. The findings indicate that 6-Gingerol exhibits strong binding ability to these disease targets, suggesting its potential role in regulating AD at the molecular level, as well as in abnormal cholinesterase metabolism and cell apoptosis, among other related regulatory pathways. These results provide a solid theoretical foundation for future in vitro experiments using actual cells and animal experiments to further investigate the application of 6-Gingerol.
Keyphrases
- molecular docking
- protein protein
- molecular dynamics
- oxidative stress
- molecular dynamics simulations
- small molecule
- drinking water
- genome wide
- randomized controlled trial
- induced apoptosis
- network analysis
- gene expression
- cognitive decline
- dna damage
- transcription factor
- machine learning
- density functional theory
- bone marrow
- drug induced
- signaling pathway
- cell death
- cell cycle arrest
- dna methylation
- ischemia reperfusion injury
- single molecule
- deep learning
- mild cognitive impairment
- big data
- genome wide identification