4D-QSAR Molecular Modeling and Analysis of Flavonoid Derivatives as Acetylcholinesterase Inhibitors

Flavonoids are potential strikingly natural compounds with antioxidant activity and acetylcholinesterase (AChE) inhibitory activity for treating Alzheimer's disease (AD). In present study, in line with our interests in flavonoid derivatives as AChE inhibitors, a four-dimensional quantitative structure-activity relationship (4D-QSAR) molecular model was proposed. The data required to perform 4D-QSAR analysis includes 52 compounds reported in the literature, usually analogs, and their measured biological activities in a common assay. The model was generated by a complete set of 4D-QSAR program which was written by our group. The best model was found after trying multiple experiments. It had a good predictive ability with the cross-validation correlation coefficient Q(2) =0.77, the internal validation correlation coefficient R-2 =0.954, and the external validation correlation coefficient R-pred(2) = 0.715. The molecular docking analysis was also carried out to understand exceedingly the interactions between flavonoids and the AChE targets, which was in good agreement with the 4D-QSAR model. Based on the information provided by the 4D-QSAR model and molecular docking analysis, the idea for optimizing the structures of flavonoids as AChE inhibitors was put forward which maybe provide theoretical guidance for the research and development of new AChE inhibitors.

Automated summary

The study proposed a four-dimensional quantitative structure-activity relationship (4D-QSAR) molecular model for flavonoid derivatives as acetylcholinesterase (AChE) inhibitors. The model showed a good predictive ability based on data analysis of 52 compounds and their biological activities, with promising results for the research and development of new AChE inhibitors.