Combined ligand and structure-based virtual screening approaches for identification of novel AChE inhibitors

Abstract

The excessive activity of acetylcholinesterase enzyme (AChE) causes different neuronal problems, especiallydementia and neuronal cell deaths. Food and Drug Administration (FDA) approved drugs donepezil, rivastigmine,tacrine and galantamine are AChE inhibitors and in the treatment of Alzheimer’s disease (AD) these drugs are currentlyprescribed. However, these inhibitors have various adverse side effects. Therefore, there is a great need for the novelselective AChE inhibitors with fewer adverse side effects for the effective treatment. In this study, combined ligand-basedand structure-based virtual screening approaches were used to identify new hit compounds from small molecules libraryof National Cancer Institute (NCI) containing approximately 265,000 small molecules. In the present study, we developeda computational pipeline method to predict the binding affinities of the studied compounds at the specific target sites.For this purpose, a text mining study was carried out initially and compounds containing the keyword “indol” wereconsidered. The therapeutic activity values against AD were screened using the binary quantitative structure activityrelationship (QSAR) models. We then performed docking, molecular dynamics (MD) simulations and free energy analysisto clarify the interactions between selected ligands and enzyme. Thus, in this study we identified new promising hitcompounds from a large database that may be used to inhibit the enzyme activity of AChE.