Integrated Pharmacophore-Guided Atom-Based 3D-QSAR, Molecular Docking, Virtual Screening, and ADMET Analysis for the Identification of Novel 1,3,4-Thiadiazole-Based Aldose Reductase Inhibitors
| dc.contributor.author | Priya Devi | |
| dc.contributor.author | Debarshi Mondal | |
| dc.contributor.author | Shalini Sharma | |
| dc.contributor.author | Harmel Singh Chahal | |
| dc.date.accessioned | 2026-10-07T10:32:17Z | |
| dc.date.available | 2026-10-07T10:32:17Z | |
| dc.date.issued | 2026-08-13 | |
| dc.description.abstract | 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. | |
| dc.identifier.issn | 2321-2217 | |
| dc.identifier.issn | 2321-2225 | |
| dc.identifier.other | https://doi.org/10.15415/jptrm.2025.132007 | |
| dc.identifier.uri | https://dspace.chitkara.edu.in/handle/123456789/728 | |
| dc.language.iso | en | |
| dc.publisher | Chitkara University Publications | |
| dc.subject | Aldose reductase inhibitors | |
| dc.subject | 1 | |
| dc.subject | 3 | |
| dc.subject | 4-thiadiazole | |
| dc.subject | Pharmacophore modelling | |
| dc.subject | 3D-QSAR | |
| dc.subject | Molecular docking | |
| dc.title | Integrated Pharmacophore-Guided Atom-Based 3D-QSAR, Molecular Docking, Virtual Screening, and ADMET Analysis for the Identification of Novel 1,3,4-Thiadiazole-Based Aldose Reductase Inhibitors | |
| dc.type | Article |