Structure‐Based In Silico Assessment of Strategically Designed Quinazolinone Derivatives for Multi‐Target Alzheimer's Disease: From ADMET to Molecular Dynamics

ABSTRACT Identification of novel drugs for the neurodegenerative diseases such as Alzheimer's and Parkinson's are complex due to the involvement of more than one distinct cause and multiple disease mechanisms with multiple drug targets. Numerous target‐specific chemical or biologic drugs, proposed earlier, were either abandoned due to their limited potency to a single mechanistic target enzyme or failed in clinical trials due to adverse side‐effects and impaired blood–brain barrier (BBB) efficacy. This work focuses on a strategically designed database of quinazolinone derivatives and performed a detailed ADMET screening and sequential molecular docking toward the simultaneous inhibition of three therapeutic targets of Alzheimer's disease (AD) namely, acetylcholinesterase, butyrylcholinesterase, and β‐secretase. Molecular dynamics simulation (MD simulation) was conducted for 100 ns on the best‐docked poses of potential lead compound QNZ14 to analyze stability and interaction at the catalytic active site. The MD simulation trajectories, including RMSD, root mean square fluctuation (RMSF), and ligand–protein interaction were analyzed to interpret the stability. The effort has successfully identified a novel inhibitor of AD pathogenesis with “multi‐targeted efficacy”. This finding opens the door for further research into the lead compound as potential therapeutics for the efficient triple inhibition of the three crucial enzymes of amyloid‐based and cholinergic mechanisms for AD pathogenesis.