Sahin_2019_J.Biomol.Struct.Dyn__1

Acethylcholinesterase (AChE) and butyrylcholinesterase (BChE) are crucial target enzymes for the Alzheimer's disease (AD). The excess activities of these enzymes may lead serious issues especially for neurodegenerative diseases. Since the current FDA approved drugs for the AD have some serious adverse effects, identification of novel scaffolds in small molecule therapeutics for this disease is a still hot topic both in academia and in pharmaceutical industry. For this aim, in the current work, we developed a computational pipeline method for predicting the binding affinities of studied compounds at the specific target sides. Since many approved therapeutic compounds involve indole or indole-derivative rings, in the current study we focused compounds including these fingerprints. Initially, 212520 compounds were retrieved from Specs SC small molecule library and after the conversion of IUPAC text file format, compounds that include "indol" keyword (5194 indole-based compounds) were used in binary QSAR-based models from MetaCore/MetaDrug platform from Clarivate Analytics to screen against a defined therapeutic activity. The molecules that have higher AD therapeutic activity values (>0.5) were then used in the 26 different toxicity-QSAR models. Combined disease and toxicity QSAR models resulted in 89 hits that have high AD therapeutic activity and no toxicity in 26 toxicity QSAR models. Selected 89 molecules were then screened against AChE targets using molecular docking and top-docking poses of compounds were then used in initially short (10 ns) molecular dynamics (MD) simulations. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding free energy calculations were then performed for 89 ligands and tightly bound 17 ligands based on average MM/GBSA scores were selected for long (100 ns) MD simulations. The same protocol was also applied for the known 4 AChE inhibitors. Selected hits were also docked to the binding pocket of BChE. Finally, based on MM/GBSA scores, as well as their corresponding docking scores and metabolite production profiles, 7 compounds were selected and their in vitro tests were performed. Out of 7 compounds, 6 of them showed muM-level inhibition for both AChE and BChE targets. Success rate of our developed method was found as 86%.