Discovery of a novel acetylcholinesterase inhibitor by structure-based virtual screening techniques.

Acetylcholinesterase (AChE) is considered to be one of the most important targets for the treatment of Alzheimer's disease (AD). Previously our group has reported a series of tacrine-based hybrids as potent AChE inhibitors (AChEI). To discover more novel scaffolds, molecular docking and dynamics stimulation were applied to acquire the binding models of AChE with the most prominent compounds from our work. A structure-based pharmacophore model plus shape constraints was generated from the binding models and it was then employed to virtually screen commercial databases, giving a focused hit list of candidates. Subsequently, we scored the hit compounds by their molecular binding energies, which were calculated by MM/PBSA method. Fifteen compounds were selected and purchased for testing their anti-AChE effects, while seven of them showed inhibitory effects with IC(50) values ranging from 1.5 to 9.8 μM. The drug-like properties of these compounds, including LogD, AlogP, molecular volume and Lipinski rule of five, were also calculated. Compounds 12 and 16 (IC(50)=2.5 and 1.5 μM, respectively) exhibited potent activity and acceptable drug-like properties, thus might serve as leads for further modification. The data suggest that the presented model might be a valid approach for identification and development of new AChEIs.