Overexpression of the antioxidant enzyme glutathione peroxidase-1 (GPx1) is associated with different cancer types. Inhibitors of GPx1, including mercaptosuccinic acid and pentathiepins derivatives, have been proposed previously and investigated as potent drugs to combat cancer. However, these compounds often lack specificity and demonstrate off-target effects, which necessitates the need for more targeted, non-toxic, and effective GPx1 inhibitors. This study utilized molecular docking and dynamic simulations based computational pipeline to repurpose drugs, approved by The Food and Drug Administration [1], as potent GPx1 inhibitors from a library containing 1615 synthetic compounds. The drug suitability and stability of the selected compounds were further investigated using ADMET, bioactivity probability, Molecular Mechanics-Generalized Born Surface Area (MM-GBSA), and Molecular Mechanics-Poisson-Boltzmann Surface Area (MM-PBSA) analyses. Initially, 13 compounds were virtually screened based on the Triangle Matcher algorithm, docking modules, and GBVI/WSA dG scoring function. Of these 13 screened compounds, three compounds, including dronedarone, nilotinib, and thonzonium, were rigorously selected based on their ADMET profiles, physicochemical properties, drug suitability, and stability and were subjected to Molecular Dynamic (MD) simulations. MD simulations further validated the stability of the dronedarone, nilotinib, and thonzonium complexes with GPx1 and provided further insights into the mechanism of their interaction. The in-silico approaches used herein revealed thonzonium, dronedarone, and nilotinib as potent GPx1 inhibitors.