Discovery of new acetylcholinesterase and butyrylcholinesterase inhibitors through structure-based virtual screening†
Abstract
Small molecule cholinesterase (ChE) inhibitors represent one of the most effective therapeutic strategies for the treatment of Alzheimer's disease (AD). However, only three of these drugs have entered the market. Understanding of the structures of successful ChE inhibitors is still very limited; therefore, it is an urgent task to identify new scaffolds for the design of ChE inhibitors. In the present study, we report an effective computer-aided workflow using a hierarchical structure-based virtual screening to identify new ChE inhibitors. 3D shape-based similarity screening combined with structure-based pharmacophore models was applied to obtain efficiently narrow potential hits from large compound collections, such as Chemdiv. Molecular docking was then used to further restrict the screening results. Five new ChE inhibitors, namely C629-0196, G070-1566, G115-0283, G801-0274, and F048-0694, were identified from the biological validation of 24 potential hits from the virtual screening. These compounds provide interesting templates for the design of new ChE inhibitors. Among the compounds, G801-0274 exhibited the lowest nanomolar range IC50 (0.031 ± 0.006 μM) and the highest selectivity (ratio = 66.13) against BuChE. Another compound, C629-0196, showed a low micromolar range IC50 (1.28 ± 0.83 μM) against AChE; however, it had no activity against BuChE. Most importantly, these two compounds provide good starting points for the discovery of highly selective ChE inhibitors.
- This article is part of the themed collections: Drug design and discovery, Molecular modelling and Computational chemistry