Chem Biol Drug Des
School of Pharmacy, The University of Queensland, Brisbane, QLD, Australia.
Published: May 2021
Cholinesterase inhibitors remain the mainstay of Alzheimer's disease treatment, and the search for new inhibitors with better efficacy and side effect profiles is ongoing. Virtual screening (VS) is a powerful technique for searching large compound databases for potential hits. This study used a sequential VS workflow combining ligand-based VS, molecular docking and physicochemical filtering to screen for central nervous system (CNS) drug-like acetylcholinesterase inhibitors (AChEIs) amongst the 6.9 million compounds of the CoCoCo database. Eleven in silico hits were initially selected, resulting in the discovery of an AChEI with a K of 3.2 µM. In vitro kinetics and in silico molecular dynamics experiments informed the selection of an additional seven analogues. This led to the discovery of two further AChEIs, with K values of 2.9 µM and 0.65 µM. All three compounds exhibited reversible, mixed inhibition of acetylcholinesterase. Importantly, the in silico physicochemical filter facilitated the discovery of CNS drug-like compounds, such that all three inhibitors displayed high in vitro blood-brain barrier model permeability.
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http://dx.doi.org/10.1111/cbdd.13825 | DOI Listing |
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