Design of Acetylcholinesterase Inhibitors as Promising Anti-Alzheimer's Agents Based on QSAR, Molecular Docking, and Molecular Dynamics Studies of Liquiritigenin Derivatives

Cholinesterase inhibitors are promising drugs for the symptomatic treatment of Alzheimer's disease. In the current study, we explored the quantitative structure activity relationship (QSAR) of a series of Liquiritigenin derivatives recently assessed for their anti-acetylcholinesterase activity. The multiple linear regression was applied to establish a QSAR model relating the biological activities of the studied compounds to their molecular descriptors. The QSAR model quality was evaluated by adopting Golbraikh and Tropsha's criteria. The obtained results highlight the fact that the developed model is perfectly valid (MSE=0.038; R-2=0.789; R-adj(2)=0.747; Q(CV)(2)=0.670; F=18.751) and exhibit high predictive power (R-test(2)=0.760). Besides, Balaban Index (J), total energy (E-T), dipole moment (& mu;) and electrophilicity index (& omega;) were identified to be the most relevant descriptors governing the anti-acetylcholinesterase activity. By analyzing these molecular features, new Liquiritigenin derivatives with enhanced anti-acetylcholinesterase activity were designed. Moreover, both molecular docking and molecular dynamics were performed to support the obtained results. In addition, the pharmacokinetics properties corresponding to the designed molecules were estimated. As a result, the compounds D10 and D13 were found to possess good pharmacokinetics properties and predicted to form stable complexes with the acetylcholinesterase protein, supporting their use as anti-Alzheimer drug candidates.

Automated summary

Cholinesterase inhibitors show promise in symptomatic treatment of Alzheimer's disease. A quantitative structure activity relationship (QSAR) model was developed to relate the anti-acetylcholinesterase activity of Liquiritigenin derivatives to their molecular descriptors. The model demonstrated high predictive power and identified specific molecular features governing the activity. New derivatives were designed based on these findings, and further analysis through molecular docking and dynamics supported their potential as anti-Alzheimer drug candidates.