Background: Metabolic Disorder Type 2 Diabetes mellitus (T2DM) is a chronic disease that involves hyperglycemia due to insulin resistance and impaired insulin secretion. α-glucosidase inhibition has been proven to be a therapeutic approach for controlling postprandial hyperglycemia and is a well-established treatment for T2DM. 1,3,4-thiadiazole is a promising pharmacophore among heterocyclic scaffolds due to its broad range of biological activities, including α-glucosidase inhibition.
Purpose: The present study was designed to identify and optimize novel 1,3,4-thiadiazole derivatives as α-glucosidase inhibitors using an integrated computer-aided drug design (CADD) approach that includes pharmacophore modeling, 3D-QSAR, molecular docking, optimization of R-groups, and ADMET prediction.
Methods: A total of 34 reported 1,3,4-thiadiazole derivatives were analyzed to build an optimal pharmacophore model (AADHR₃) as well as atom-based (R² = 0.799, Q² = 0.822) and Gaussian field-based 3D-QSAR models (R² = 0.967, Q² = 0.682). The structurally optimized lead compounds were then identified by molecular docking, R-group optimization, and ADMET prediction.
Results: The analysis of the contour map showed that bulky hydrophobic groups in the R₁ position and electron-withdrawing groups in the R₂ position were beneficial for enhancing α-glucosidase inhibitory activity. The docking score of five compounds was comparable or better than that of acarbose (−6.260 kcal/mol), with the best score being compound 25 (−6.686 kcal/mol). The designed derivatives (DM1 (−7.625 kcal/mol), DM2 (−7.418 kcal/mol), and DM3 (−7.284 kcal/mol)) showed better binding abilities and favorable interactions with Arg281, Asp282, Asp404, Asp518, Asp616, His674, and Phe525, in addition to promising ADMET properties.
Conclusion: Pharmacophore analysis, 3D-QSAR, molecular docking, SAR, and ADMET studies indicated that the 1,3,4-thiadiazole scaffold could be a promising template for designing potent α-glucosidase inhibitors. The optimized derivatives, especially DM1–DM3, are good lead candidates for further development into therapeutic drugs for T2DM.
Debarshi Mondal, Priya Devi, Shalini Sharma et al.· Journal of Pharmaceutical Te...· 0 citations
Background: Chronic diabetic complications develop through the important role of aldose reductase (AR), a key enzyme in the polyol pathway. Clearly, it is important to identify potent AR inhibitors with better PK properties for treatment of diabetes-associated complications.
Purpose: The purpose of this study was to discover novel 1,3,4-thiadiazole derivatives as aldose reductase inhibitors using an integrated computational drug discovery approach.
Methods: The dataset consisted of 30 reported 1,3,4-thiadiazole derivatives, which were analysed by the pharmacophore modelling, atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR), molecular docking, structure-activity relationship (SAR) analysis, R-group enumeration, virtual screening and ADMET prediction methods. Using the best pharmacophore model (AHHRR_1), a validated 3D-QSAR model was developed, and 1,419 new derivatives were designed. These compounds were then further optimised for binding interactions and pharmacokinetic parameters with the top-ranked ones, including the designed derivative PD01.
Results: The optimised pharmacophore and 3D-QSAR models were able to recognise the crucial structural elements that are essential for AR inhibition. Activity increased with the hydrophobic and electron-withdrawing groups, while the bulky polar groups were responsible for decreased activity. Docking studies showed that compounds 04 (-10.178 kcal/mol), 01 (-10.081 kcal/mol), 02 (-10.050 kcal/mol), 10 (-9.977 kcal/mol), and 11 (-9.672 kcal/mol) exhibited stronger binding than Epalrestat (-8.182 kcal/mol). The highest docking score was obtained for PD01 (-10.605 kcal/mol), which had strong hydrogen-bond, hydrophobic, π-π stacking, π-cation and halogen-bond interactions. The ADMET analysis showed good drug-likeness and good oral absorption.
Conclusion: The integrated computational workflow has concluded that PD01 is the most promising lead candidate with excellent binding affinity, a favourable interaction pattern and desirable ADMET properties. The results suggest that the scaffold 1,3,4-thiadiazole is a promising structural template for designing new generation aldose reductase inhibitors for diabetic complications.
Priya Devi, Debarshi Mondal, Shalini Sharma et al.· Journal of Pharmaceutical Te...· 0 citations
