%0 Journal Article
%T Computational Screening of Chalcone Derivatives as Novel Acetylcholinesterase Inhibitors for Alzheimer’s Disease
%A Mohammed Merzouki
%A Oussama Khibech
%A Elmehdi Fraj
%A Hicham Elmsellem
%A Ahmed Chetouani
%A Boufelja Bouammali
%A Allal Challioui
%J Journal of Biochemical Technology
%@ 0974-2328
%D 2026
%V 17
%N 1
%R 10.51847/PTHVL9LMg0
%P 129-136
%X The identification of novel acetylcholinesterase inhibitors remains a key strategy for the treatment of Alzheimer’s disease. In this study, a series of chalcone derivatives was evaluated using an integrated in silico approach combining ADMET prediction, BOILED-Egg analysis, and molecular docking. The pharmacokinetic assessment revealed favorable drug-likeness profiles, along with good predicted gastrointestinal absorption for most compounds. In addition, the BOILED-Egg model suggested potential blood–brain barrier permeability, an essential feature for central nervous system activity. Molecular docking studies performed against acetylcholinesterase (PDB ID: 1C2B) demonstrated that chalcone phenylhydrazone (−7.736 kcal/mol), cyclohexenyl chalcone (−7.704 kcal/mol), and benzalacetophenone (−7.259 kcal/mol) exhibited stronger binding affinities than the reference inhibitor donepezil (−6.738 kcal/mol). These findings indicate that chalcone derivatives may serve as promising scaffolds for the development of new acetylcholinesterase inhibitors. Overall, this study highlights the relevance of combining computational tools to accelerate the identification of potential therapeutic candidates for Alzheimer’s disease, supporting future experimental validation and clinical research efforts.
%U https://jbiochemtech.com/article/computational-screening-of-chalcone-derivatives-as-novel-acetylcholinesterase-inhibitors-for-alzheim-egyg8rahjfncvp0