The process of developing novel compounds/drugs is arduous, time-intensive, and financially burdensome, characterized by a notably low success rate and relatively high attrition rates. To alleviate these challenges, compound/drug repositioning strategies are employed to predict potential therapeutic effects for DrugBank-approved compounds across various diseases. In this study, we devised a computational and enzyme inhibitory mechanistic approach to identify promising compounds from the pool of DrugBank-approved substances targeting Diabetes Mellitus (DM). Molecular docking analyses were employed to validate the binding interaction patterns and conformations of the screened compounds within the active site of α-glucosidase. Notably, Asp352 and Glu277 participated in interactions within the α-glucosidase-ligand complexes, mediated by conventional hydrogen bonding and van der Waals forces, respectively. The stability of the docked complexes (α-glucosidase-compounds) was scrutinized through Molecular Dynamics (MD) simulations. Subsequent in vitro analyses assessed the therapeutic potential of the repositioned compounds against α-glucosidase. Kinetic studies revealed that "Forodesine" exhibited a lower IC