Insilico assisted investigation on quinazolinone–thiophene scaffolds as potential human insulin-degrading enzyme inhibitors

This study explores eighteen quinazolinone–thiophene scaffolds as potential inhibitors of the human insulin-degrading enzyme (IDE) using in silico approaches. Density functional theory optimization revealed that solvent effects slightly improve electronic stability and reactivity without major structural changes. Molecular docking showed strong binding affinities, with compound 9 exhibiting the best score (−8.43 kcal/mol), showing potential greater binding affinity than the reference drug, ML345 (5-fluoro-2-[2-(4-morpholinyl)-5-(4-morpholinylsulfonyl)phenyl]-1,2-benzisothiazol-3(2H)-one). Key interactions included hydrogen bonding, π–H, and electrostatic interactions with active site residues. Molecular dynamics simulations revealed the potential the stability of the ligand–enzyme complex. However, ADMET analysis indicated that compound 9 has less favorable pharmacokinetic and toxicity profiles compared to the reference. Regression analysis revealed weak correlations between electronic descriptors and docking scores, suggesting multivariate influence. Therefore, the compounds show promise but require further optimization for drug development.