Rational modification of olive derived 4-ethylguaiacol into a BBB-permeable acetylcholinesterase inhibitor via molecular docking, DFT, and molecular dynamics: a computational approach to alzheimer's drug discovery.

Alzheimer's disease (AD) affects more than 55 million people worldwide, yet no disease-modifying therapy has been approved. Here, 23 phytochemicals from Olea europaea (olive) were evaluated using a multi-filter pipeline comprising ADME/drug-likeness screening, BBB permeability assessment, molecular docking, DFT analysis, and MD simulations. This is the first computational study of olive phytochemicals targeting AChE to use BBB permeability as an explicit screening filter, addressing the CNS penetrance gap that limits translation of prior in silico hits. ADME screening (through SwissADME) identified three Lipinski-compliant, BBB-permeable candidates. Among these, 4-ethylguaiacol exhibited the strongest AChE binding (-7.0 kcal/mol) and a favorable HOMO-LUMO energy gap (6.09 eV), indicating moderate chemical reactivity and stability. Structure-guided optimization of 4-ethylguaiacol using RDKit led to the design of AM-11; 4-ethyl-5-(1-hydroxycyclopropyl)-2-methoxyphenol, whose C-5 hydroxycyclopropyl group forms direct hydrogen bond with catalytic residue, Ser203. AM-11 showed improved binding affinity (-7.9 kcal/mol), stable RMSD throughout a 100 ns MD simulation, and a predicted LD₅₀ of 720 mg/kg (Class IV), a better acute toxicity profile than donepezil (505 mg/kg). These findings position AM-11 as a as a computational lead for a BBB-permeable AChE inhibitor scaffold requiring experimental validation, and the pipeline as a reproducible framework for phytochemical-based lead optimization in AD.