This study investigated the potential of m-TOR inhibitor drugs (sirolimus, everolimus, and tacrolimus) in combating both hepatocellular carcinoma (HCC) and hepatitis C virus (HCV) replication. After treating HepG2 and PBMCs with the mammalian target of Rapamycin (m-TOR) inhibitors drugs; sirolimus, everolimus, and tacrolimus at different concentrations (1, 5, and 10 µM/µl), cell proliferation was assessed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Antioxidant activities (total antioxidant, glutathione S-transferase, and glutathione reductase), Fas-ligand level, tumor necrosis factor-α (TNF-α) level, caspase-3, -8, and -9 activities, and cell cycle analysis were measured. quantitative Real-time PCR, colony forming assay, molecular docking studies after infection of PBMCs with 1 ml (1.5 × 106 HCV) serum then incubated with m-TOR inhibitor drugs at their respective IC50 concentrations. In HepG2 cells, treatment with these inhibitors resulted in suppressed cell viability, increased dead cell accumulation, and enhanced apoptotic signaling through elevated Fas-ligand and caspase activities. Additionally, cell cycle analysis revealed arrest in G0/G1 and G2/M phases, further hindering HCC progression. Furthermore, m-TOR inhibitor drugs significantly reduced HCV viral load and colony formation in infected PBMCs. This antiviral effect was accompanied by decreased TNF-α activity, suggesting potential modulation of the inflammatory response associated with HCV infection. Molecular docking studies provided theoretical support for these findings, with Sovaldi demonstrating the highest binding affinity towards key HCV targets compared to other m-TOR inhibitors. This suggests its potential as a potent HCV inhibitor, while also highlighting the potential of exploring m-TOR inhibitors for future HCV treatment development. Overall, this study provides encouraging evidence for the potential of m-TOR inhibitor drugs as promising therapeutic agents for both HCC and HCV, warranting further investigation and optimization for clinical applications.