In silico drug discovery of Acetylcholinesterase and Butyrylcholinesterase enzymes inhibitors based on Quantitative Structure-Activity Relationship (QSAR) and drug-likeness evaluation

Abstract

Abstract In the last years, in order to achieve a better treatment of Alzheimer s disease (AD), much focus has been put on the development of cholinesterase (Acetylcholinesterase and Butyrylcholinesterase) inhibitor drugs. Thus, the aim of this study is to discover promising active compounds for Acetylcholinesterase and Butyrylcholinesterase enzymes inhibitors based on QSAR model and drug-likeness evaluation. In this study, a series of DL0410 and its 50 derivatives are accounted for the set up of two QSAR models. This allows an exploration of the main molecular descriptors that control the inhibitory activity of specific compounds towards cholinesterase enzymes: Acetylcholinesterase (AChE) and Butyrylcholinesterase (BuChE). Simultanerously, the models can help to predict the inhibitory activity of new compounds within its applicability domain. A Multiple Linear Regression (MLR) analysis is carried out to derive QSAR models. The results indicate that the QSAR models of Acetylcholinesterase and Butyrylcholinesterase inhibitory activity are robust and have a very good prediction capacity, testified by values of R2 equal to 0.935 and 0.895, respectively. The analysis carried out by adopting the QSAR models succeed in screening 15 potential compounds with higher biological activity. Subsequently, the investigated compounds has been subjected to the drug-likeness evaluation and reactivity study. The results show that most of the compounds do not present any bioavailability problem when administered orally. The results also allow determining the compounds that have not clearance problems, those that are the most stable and the most reactive among those tested. These findings indicate that the newly designed candidate drugs have promising potential toward AChE and BuChE enzyme inhibition and should be experimentally investigated.