Chaturvedi, NehaBhattacharya, SushantaAsati, VivekChtita, SamirKaya, SavaşAlmehizia, Abdulrahman A.Dubey, Raghvendra2025-05-042025-05-0420251570-1808https://doi.org/10.2174/0115701808350303241230081711https://hdl.handle.net/20.500.12418/34989Introduction: A new set of 1,2,4-triazine combined 1, 2, 3-triazole hybrids were designed computationally for predicting anti-diabetic potential. All the derivatives taken for study exhibited excellent anti-diabetic potential with significant IC50 values. Methods: The present research includes the development of pharmacophore models, 3D QSAR, virtual screening, molecular docking, and evaluation of models based on certain criteria. The DHRRR_1 showed the best pharmacophore model with a survival score of 5.9937. The 3D QSAR analysis developed a model with the values of R2 = 0.9714 and Q2 = 0.7202. The binding pose and affinity of the most potent compound, 10c, in the active site of α-glucosidase was investigated using in-silico molecular docking analysis. Results: It was observed that compound 10c demonstrated promising binding affinity with a score of -8.078 kcal/mol and exhibited binding interaction with the essential amino acids ASN301 and LEU227. There were five compounds (1-5) that showed significant binding affinity towards the target comprising active amino acids (ASH202, ASP333 and VAL335). The molecular dynamic study showed the stability of ligand-protein binding interactions. Conclusion: The results of the present investigation can accelerate the optimization and reformation of the latest anti-diabetic agents that target the α-glucosidase. © 2025 Bentham Science Publishers.en10.2174/0115701808350303241230081711info:eu-repo/semantics/closedAccessAnti-diabeticatom-based QSARdockingpharmacophoretriazoleArticle2-s2.0-105001715454Q3