Abstract
As there are increased levels and activity of butyrylcholiesterase (BChE) in the late stage of Alzheimer's disease (AD), development of selective BChE inhibitors is of vital importance. In this study, a workflow combining computational technologies and biological assays were implemented to identify selective BChE inhibitors with new chemical scaffolds. In particular, a pharmacophore model served as a 3D search query to screen three compound collections containing 3.0 million compounds. Molecular docking and cluster analysis were performed to increase the efficiency and accuracy of virtual screening. Finally, 15 compounds were retained for biological investigation. Results revealed that compounds 8 and 18 could potently and highly selectively inhibit BChE activities (IC50 values < 10 μM on human BChE, selectivity index BChE > 30). These active compounds with novel scaffolds provided us with a good starting point to further design potent and selective BChE inhibitors, which may be beneficial for the treatment of AD.