Development of 2D and 3D QSAR models of pyrazole derivatives as acetylcholine esterase inhibitors

Abstract

The drugs that are most useful in all stages of Alzheimer?s disease (AD) are acetylcholinesterase (AChE) inhibitors. The objectives of this work are to generate various QSAR models and to select robust predictive models from corresponding models. Studies were then focused on finding a range of pyrazole-like AChE inhibitors by 2D and 3D QSAR analysis. Genetic algorithm-based multiple linear regression (GA-MLR) provided the statistically robust 2D-QSAR model that depicted the significance of molecular volume and number of multiple bonds along with the presence/absence of specific atom-centred fragments and topological distance between 2D pharmacophoric features. Furthermore, these results were correlated well with the electrostatic and steric contour maps retrieved from the 3D-QSAR (i.e., alignment-dependent molecular field analysis). The 2D QSAR analysis developed a highly statistical and reliable model which was compared with the mechanistic interpretation of 3D structures and their electrostatic and steric field contributions leading to a predictive 3D QSAR model. The molecule-protein interactions elicited by molecular docking corroborated with the field interactions as revealed by 2D-QSAR. Thus, the developed computational models and simulation analyses in the current work provide valuable information for the future design of pyrazole and spiropyrazoline analogs as potent AChE inhibitors.