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

Spiropyrazolin Acetylcholinesterase Inhibitors for Alzheimer's Disease Treatment

الملخص

This work used computational methods of 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). Molecular docking results revealed that the new M1 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 2. 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 M1 and molecule 2 with acetylcholinesterase complexes at 100 ns. Both compounds showed good stability regarding RMSD, Rg, RMSF, and SASA values. Compound M1 shows remarkable stability in the active site of AChE compared to compound 2. 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 M1.