Design of Novel Thiazole-based Schiff Analogs as α-Amylase Inhibitors Using 3D-QSAR, ADME-Tox, Molecular Docking, Molecular Dynamics, Biological Efficacy, and Retrosynthesis

Graphical Abstract

The study develops new analogs of the Schiff thiazole that inhibit the enzyme α-amylase using a number of methods. These include 3D-QSAR (CoMSIA_DH modeling), molecular docking, ADMET properties, molecular dynamics simulations, biological efficacy, and retrosynthesis. These techniques enable the development of anti-diabetic ligands with good binding affinities, favorable pharmacokinetic profiles, and respect for Lipinski's rule.

Abstract

This study enabled us to develop new analogs of the Schiff thiazole base with high inhibitory activity against the α-amylase enzyme as effective anti-diabetic drug candidates. To this end, we used virtual screening methods such as 3D-QSAR, molecular docking, ADMET properties, molecular dynamics simulation, biological efficacy, and retrosynthesis on selected Schiff thiazole base derivatives. The results of 3D-QSAR modeling showed that the CoMSIA_DH model has excellent predictive ability (Q² = 0.71, R²_train = 0.978, R²_test = 0.987, and SEE = 0.072). Using the template (17), we designed three new ligands with high inhibitory activities against the α-amylase enzyme. ADMET predictions for designed molecules met Lipinski's rule and pharmacokinetic profiles. The new Ligands were anchored in α-amylase's active site, showing good binding affinities. The molecular docking results and binding stability of the selected ligands to the receptor were confirmed through molecular dynamics simulations. The CaverDock program was utilized to identify the tunnels through which ligands are most likely to migrate from the active site to the receptor surface, thereby determining the biological efficacy of the target compounds. The study found compound B1 to be the most effective, and using retrosynthesis, a pathway for the synthesis of these therapeutic prospects was identified.