Unravelling the anti-Alzheimer potential of Annona muricata fruit through network pharmacology, molecular docking, DFT, molecular dynamics simulations, and MM/PBSA analysis

Background Alzheimer’s disease is characterized by progressive neuronal degeneration that culminates in cognitive impairment. Botanicals represent attractive therapeutic candidates owing to their wide margin of safety and their capacity to act through multiple mechanisms. Materials and Methods We deployed an integrated computational framework, combining ADME filtering, target-network mapping, binding-affinity prediction, molecular dynamics simulations, binding free-energy calculations, and quantum-chemical analysis to investigate the potential anti-Alzheimer relevance of Annona muricata fruit constituents. Results Network pharmacology identified 56 targets shared between 37 screened compounds and Alzheimer’s disease, among which APP, TNF, IL6, and AKT1 emerged as the principal hub genes. Among the AD-associated targets, α-synyclein (SNCA) was prioritized for detailed structural analysis based on its docking interactions with the screened constituents. Molecular docking identified T9, T17, and T19 as the constituents showing the most favourable predicted interactions with SNCA, with binding energies of −7.20, −7.001, and −7.25 kcal/mol, respectively. MD simulations indicated stable predicted protein-ligand interactions over the simulated trajectories, while MM/PBSA calculations yielded binding free energies of −12.63 ± 0.37, −12.57 ± 0.01, and −7.89 ± 0.27 kcal/mol for T9, T17, and T19, respectively. density functional theory analysis provided additional information about the chemical reactivity of these 3 compounds. Discussion The integrated computational results suggest that selected A. muricata constituents interact with molecular targets and pathways implicated in neuroinflammation and apoptosis pathways in Alzheimer’s disease. The structural stability and favourable electronic properties of T9 and T17 highlight their potential as lead scaffolds against SNCA-associated neurodegeneration. Conclusion Collectively, these computational insights nominate the phytoconstituents T9 and T17 as promising lead candidates for Alzheimer’s disease intervention, although prospective cell-based and animal studies remain necessary to confirm their bioactivity.