Cancer remains a major global health challenge as the second-leading cause of human death worldwide. The traditional treatments for cancer beyond surgical resection include radiation and chemotherapy; however, these therapies can cause serious adverse side effects due to their high killing potency but low tumor selectivity. The FDA approved monoclonal antibodies (mAbs) that target TIGIT/PVR (T-cell immunoglobulin and ITIM domain/poliovirus receptor) which is an emerging immune checkpoint molecules has been developed; however, the clinical translation of immune checkpoint inhibitors based on antibodies is hampered due to immunogenicity, immunological-related side effects, and high costs, even though these mAbs show promising therapeutic efficacy in clinical trials. To overcome these bottlenecks, small-molecule inhibitors may offer advantages such as better oral bioavailability and tumor penetration compared to mAbs due to their smaller size. Here, we performed structure-based virtual screening of FDA-approved drug repertoires. The 100 screened candidates were further narrowed down to 10 compounds using molecular docking, with binding affinities ranging from -9.152 to -7.643 kcal/mol. These compounds were subsequently evaluated for their pharmacokinetic properties using ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis, which demonstrated favorable drug-like characteristics. The lead compounds will be further analyzed for conformational changes and binding stability against TIGIT through molecular dynamics (MD) simulations to ensure that no significant conformational changes occur in the protein structure. Collectively, this study represents the potential of computational methods and drug repurposing as effective strategies for drug discovery, facilitating the accelerated development of novel cancer treatments.