Computational biology and chemistry · 2025
A comprehensive computational and experimental study of novel imidazole linked thiadiazole based amide derivatives as cholinesterase duel-target inhibitor for the treatment of Alzheimer's disease.
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Khan Yousaf, Naeem Mujeeb Ul, Arooj Komal, Naseem Mahrukh, Adnan Robina, Azmatullah
Аннотация
The thiadiazole scaffold has gained prominence in modern drug discovery due to its remarkable structural adaptability. Its unique framework enables interactions with a wide spectrum of biological targets, making it a valuable pharmacophore for therapeutic development. Reflecting its growing clinical importance, efficient synthetic access to thiadiazole derivatives has become a focal point for medicinal chemists seeking to exploit its multifunctional activity. In our study, we synthesized a streamlined and high-throughput synthetic protocol to generate a novel library of imidazole linked thiadiazole analogues. All newly imidazole linked thiadiazole analogues were spectroscopically characterized by 1HNMR and 13CNMR spectroscopy and high-resolution electron impact mass spectrometry (HRMS). Biological screening across a panel of key metabolic enzymes revealed potent inhibitory action against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Remarkably, a majority of tested compounds outperformed standard inhibitors donepezil exhibited compounds 1, 2, 4 and 8 showing lower IC50 values of 5.32 ± 0.87 µM (AChE), 6.09 ± 0.97 µM (BuChE), 7.40 ± 0.76 µM (AChE), 6.97 ± 0.56 µM (BuChE), 7.56 ± 0.54 µM (AChE), 7.03 ± 0.39 µM (BuChE), and 5.13 ± 0.28 µM (AChE), 5.33 ± 0.61 µM (BuChE) respectively. Detailed structure-activity relationship (SAR) analyses revealed that strategic substitution patterns modulate inhibitory efficacy and selectivity. Complementing these findings, molecular docking study illuminated key interactions within the catalytic pockets of (AChE) and (BuChE), identifying critical amino acid residues mediating ligand engagement. Hence, our integrated synthetic, biochemical, and computational approach identifies compounds 1, 2, 4 and 8 as a promising lead compound that possess favorable pharmacological attributes for further preclinical development in metabolic disease interventions.