Research of new acetylcholinesterase inhibitors based on QSAR and molecular docking studies of benzene-based carbamate derivatives

In the current study, we carried out a quantitative structure–activity relationship study of a series of thirty benzene-based carbamate derivatives reported as potential acetylcholinesterase inhibitors (AChEIs) using multiple linear regression method. For modeling, the series of molecules was split into training set and test set. Twenty-four molecules were used as training set to build the quantitative model and the remaining (test set) were used to evaluate the built model performances in terms of the predictive power. The quality of the model was found to be statistically satisfying (R2 = 0.811; R2adj = 0.759; MSE = 0.020; Q2CV = 0.689; Q2CV (rand) = −0.406; R2rand = 0.114). Furthermore, our model exhibited an excellent predictive capability (R2test = 0.824). What is more, the applicability domain has been defined for the built model using Williams plot. Based on the developed model, a series of newer carbamate derivatives were designed and their ADMET properties were predicted using pKCSM online software. Furthermore, molecular docking studies were performed to assess the binding affinities between the designed compounds and AChE enzyme. All designed compounds showed good binding affinities toward the targeted enzyme.