Computational Prediction of Spiropyrazoline Derivatives as Potential Acetylcholinesterase Inhibitors for Alzheimer's Disease Treatment.

Objective: Acetylcholinesterase (AChE) is a crucial enzyme in the nervous system that catalyzes the degradation of acetylcholine, a neurotransmitter. Its primary role is to regulate the transmission of nerve signals by breaking down acetylcholine after it has conveyed its message to the target cell. Methods: This study employed computational methods, including 3D-QSAR, molecular docking, ADMET, and molecular dynamics simulations, to analyze the relationship between chemical structure and acetylcholinesterase inhibition mechanism by spiropyrazoline derivatives COMFA and COMSIA predicted the inhibitory activities of the proposed spiropyrazoline derivatives against acetylcholinesterase, where the best models are (COMSIA/S + E + H) (Q2 = 0.517, R2 = 0.904, R2 test = 0.931). Results and Discussion: Molecular docking results revealed that the new (I) complex interacts with critical residues in the major circuits of the AChE main chain, with residues TRP286, TRP86, TYR341, TYR72, TYR124, and TYR337 more than compound (II). This residue plays an essential role in the stability of the complex. A molecular dynamics simulation explored the binding stability and conformational interaction changes of (I) and molecule (II) with acetylcholinesterase complexes at 100 ns. Both compounds showed good stability regarding RMSD, Rg, RMSF, and SASA values. Compound (I) shows remarkable stability in the active site of AChE compared to compound (II). In addition, Lipinski's rule for predicting pharmacokinetics with ADMET is satisfactory. The retrosynthetic approach was used to develop an efficient and convenient synthetic route for preparing the target molecule (I). Conclusions: The present study offers theoretical insights into the development, prediction, and design of new compounds that specifically target acetylcholinesterase. [ABSTRACT FROM AUTHOR]