computational design and evaluation of novel rivastigmine analogues targeting hache in alzheimer ’s disease

Introduction: alzheimer’s disease (ad) is a progressive neurodegenerative disorder marked by memory loss and cognitive decline. one therapeutic strategy involves inhibiting acetylcholinesterase (ache), the enzyme responsible for acetylcholine degradation in synaptic clefts. ache inhibitors enhance cholinergic neurotransmission, thereby alleviating cognitive symptoms associated with ad. this study aimed to identify and evaluate novel ache inhibitors structurally related to rivastigmine using computational techniques, including virtual screening and molecular docking, to discover potential lead compounds for ad therapy. materials and methods: the crystal structure of ache (pdb id: 6m0e) was obtained from the protein data bank. ligands with over 95% structural similarity to rivastigmine, based on the tanimoto coefficient, were retrieved from pubchem. the ligands were energy-minimized and screened virtually using pyrx. molecular docking was performed with autodock 4.2, and docking results were analyzed in terms of binding energy, inhibition constant (ki), and interaction profiles to assess inhibitory potential.results: among the screened compounds, ligand 13 exhibited the most favorable binding affinity, with a binding energy of –5.07 kcal/mol and an inhibition constant of 192.84 µm. interaction analysis revealed that ligand 13 formed three hydrogen bonds with key residues ser215 and arg177 in the ache active site, suggesting stronger binding than rivastigmine.conclusion: ligand 13 emerged as a promising ache inhibitor candidate for ad treatment. further studies involving pharmacokinetic, toxicity, and experimental validation are necessary to confirm its therapeutic potential.