Multiscale computational evaluation of marine fungal metabolites containing iminohydantoin-like scaffolds as anti-Alzheimer drug candidates.

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder associated with amyloid-beta accumulation, neuroinflammation, and synaptic dysfunction, making beta-secretase 1 (BACE1) a promising therapeutic target. In the current investigation, we used an integrated computational approach, including virtual screening, machine learning, quantum-chemical analysis, molecular dynamics simulations, ADMET profiling, and network pharmacology, to identify marine fungal metabolites with potential BACE1-binding activity. A virtual chemical library consisting of 4,683 marine-derived compounds was virtually screened against the BACE1 catalytic subdomain to select 100 top compounds with docking energy ranging from -11.9 to -10.2 kcal/mol. The pharmacokinetic study showed promising CNS characteristics. CatBoost was identified as the most reliable model (r² = 0.243 ± 0.049), predicting pIC50 values of 7.51-7.95 for shortlisted marine fungal metabolites, suggesting potential BACE1 inhibitory activity. Density functional theory computations revealed good ligand reactivity and stability. Molecular dynamics simulation validated the stable ligand-protein interactions, and MM/GBSA analysis selected CMNPD7259 (ΔG_bind = -68.45 kcal/mol) as the most promising molecule. Network pharmacology further associated the metabolites with pathways involved in inflammation, apoptosis, immunological control, and neuronal function. Overall, the results indicate that metabolites from marine fungi are intriguing candidates for developing safer, more efficacious treatments for AD.