🧫 Experiment Protocol
ExploratoryAlzheimer's diseaseComputational network analysisproposed
A computational network pharmacology approach was employed to identify shared molecular targets between curcumin, Glycyrrhiza glabra, and Alzheimer's disease pathways. This bioinformatics analysis revealed 40 common targets associated with AD pathogenesis that could be modulated by both compounds. The network analysis provided insights into the molecular mechanisms underlying the synergistic effects observed in the animal studies, with particular enrichment in NF-κB and IL-17 signaling pathways. This computational prediction was subsequently validated through experimental verification in the mouse model, demonstrating the reliability of the network pharmacology approach for understanding multi-compound therapeutic mechanisms.
PRIMARY OUTCOME
Identification of shared molecular targets
EXPECTED OUTCOMES
Discovery of common therapeutic targets and pathways for synergistic drug action
SUCCESS CRITERIA
Identification of significant target overlap and pathway enrichment, validated by experimental results
PROTOCOL
Network pharmacology analysis to identify overlapping targets between curcumin, G. glabra, and AD-related pathways, followed by pathway enrichment analysis and experimental validation