Virtual screening of acetylcholinesterase inhibitors through pharmacophore-based 3D-QSAR modeling, ADMET, molecular docking, and MD simulation studies

Alzheimer’s disease (AD) is a leading cause of dementia in elderly patients. The pathophysiology of AD includes various pathways, such as the degradation of acetylcholine, amyloid-beta deposition, neurofibrillary tangle formation, and neuroinflammation. Many studies showed that targeting acetylcholinesterase enzyme (AChE) to improve acetylcholine can be an effective option to treat AD. In the current work, we employed a 3D QSAR-based approach to generate a pharmacophore to screen a chemical library of compounds that may inhibit AChE. Data from experimental studies were collected and used for the generation of pharmacophores. More than 1 million compounds were screened, and further drug-like properties were determined via in-silico ADMET studies. Techniques like molecular docking and molecular dynamics simulation were performed to analyze the binding of novel AChE inhibitors. A novel AChE inhibitor ligand-1 was identified as best with a docking score of -13.560 kcal/mol with RMSD of 1.71 Å during a 100 ns MD run. Further biological studies can give an insight into the potential of ligand-1 as a therapeutic agent for AD.