Computational identification of phytochemicals as glycogen synthase kinase 3 beta (GSK3β) inhibitors for therapeutic applications in chronic diseases.

Glycogen synthase kinase-3 beta (GSK-3β) is a serine/threonine kinase implicated in various diseases such as Alzheimer's, diabetes, and cancer, making it a pivotal therapeutic target. This study uniquely integrates a curated phytochemical library with comprehensive ADMET filtering and 200 ns molecular dynamics (MD) simulations to identify stable GSK-3β inhibitors, offering deeper mechanistic and dynamic insights than previous docking-based studies. ADMET profiling shortlisted 49 compounds, with uzarigenin, jatrophone, chrysin, and podolide exhibiting superior binding affinities compared to Tideglusib (-8.53 kcal/mol). Among these, jatrophone displayed the highest binding affinity (9.00 kcal/mol), followed by uzarigenin (8.63 kcal/mol) and podolide (8.60 kcal/mol), indicating stronger interactions with GSK-3β. Molecular dynamics simulations confirmed stability for uzarigenin and podolide over 200 nanoseconds, supported by RMSD, SASA, and Rg analyses. Principal component and covariance analyses revealed strong residue interactions in these complexes. KEGG pathway analysis highlighted the role of GSK-3β inhibitors in Alzheimer's disease, Wnt signaling, and cancer pathways. This study identifies phytochemicals with potential therapeutic applications for neurodegenerative, cancer, and metabolic diseases, warranting further experimental validation.

© 2025. The Author(s).