Network Pharmacology-guided Identification and Molecular Validation of Multi-Target Phytoconstituents from Gmelina arborea against Alzheimer’s Disease

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, remains without a definitive cure due to its complex multifactorial pathogenesis. Conventional drug development strategies, targeting single pathway, have demonstrated limited success, necessitating a paradigm shift towards multi-target therapeutics. In this study, we systematically investigated the therapeutic potential of Gmelina arborea (GA), a medicinal plant used in traditional Indian medicine against dementia, using an integrated network pharmacology and molecular modeling approach. Phytoconstituents of GA (GAPC) were selected and screened for drug-likeness (DL), blood-brain barrier (BBB) permeability, and absorption, distribution, metabolism, excretion, and toxicology (ADMET) properties. Potential therapeutic targets of GAPC were predicted and cross-referenced with known AD-associated targets to construct a protein-protein interaction (PPI) network of common targets. Functional enrichment analysis revealed key aspects of gene ontology (GO) and pathways, including PI3K-Akt, MAPK, FoxO, Rap1, and Ras signaling pathways. Top ten core target genes (using topological analysis) were identified as AKT1, EGFR, ESR1, SRC, PTGS2, GSK3β, MMP9, PARP1, KDR, and ABCB1. Molecular docking, molecular dynamics (MD) simulations, molecular mechanics, the Generalized Born Surface Area (MM-GBSA), principal component analysis (PCA), and free energy landscape (FEL) analysis confirmed strong, stable binding interactions, especially for verbascoside and martynoside. This study provides compelling evidence that GA can be targeted for AD treatment following experimental validation and lays the foundation for further wet lab investigations. It also presents the first integrated in silico and network pharmacology analysis of GAPC's multi-target interactions in AD, offering mechanistic insights to guide future research.