Alzheimer's disease (AD) is a neurodegenerative disorder with gradual cognitive deterioration and complex pathophysiological mechanisms include amyloid-β aggregation, tau hyperphosphorylation, cholinergic dysfunction, and altered proteostasis. Finding multi-target ligands that can simultaneously modulate several pathogenic proteins is becoming more and more popular due to the complex nature of AD. Six plant-derived phytochemicals—Withanolide A, Ginkgolide B, Epigallocatechin gallate, Huperzine A, Baicalein, and Fisetin—were thoroughly screened in silico and their interactions with the four main AD-associated proteins—β-secretase 1 (BACE1), γ-secretase, tau protein, and acetylcholinesterase (AChE)—were examined in this study. High-resolution protein–ligand complexes were used for docking investigations, and binding preferences were then captured by interaction fingerprinting and energy-based comparisons. Our findings show that different phytochemicals have different but similar binding landscapes, with some exhibiting stable binding orientations and good docking scores across a variety of targets. While Baicalein and Fisetin showed consistent interactions with BACE1, Epigallocatechin gallate and Withanolide A showed the best multi-target potential, especially against AChE and γ-secretase. Comparative interaction heatmaps revealed hydrophobic interactions and conserved hydrogen bonds among catalytic residues, indicating that certain phytochemicals take advantage of structural weaknesses that AD proteins frequently share. Additionally, selectivity profiling demonstrated how particular drugs can distinguish between structural and enzymatic targets, providing information on both target-specific suppression and broad-spectrum modulation. The potential of phytochemicals derived from plants as scaffolding for multi-target AD treatments is highlighted by this integrated investigation. Through the integration of docking-based energetics, per-residue interaction mapping, and comparative binding landscape visualization, our research offers a methodical computational framework that connects the fields of neurodegenerative drug discovery and natural product chemistry. These results demonstrate the translational potential of phytochemical libraries in tackling the complexity of Alzheimer's disease, even though more refinement by MM-GBSA, molecular dynamics simulations, and in vitro validation is necessary.
K et al. (Tue,) studied this question.