Several existing drugs are currently being tested worldwide to treat COVID-19 patients . Recent data indicate that SARS-CoV-2 is rapidly evolving into more transmissible variants . It is therefore highly possible that SARS-CoV-2 can accumulate adaptive mutations modulating drug susceptibility and hampering viral antigenicity . Thus, it is vital to predict potential non-synonymous mutation sites and predict the evolution of protein structural modifications leading to drug tolerance . As two FDA-approved anti-hepatitis C virus (HCV) drugs, boceprevir, and telaprevir, have been shown to effectively inhibit SARS-CoV-2 by targeting the main protease (Mpro), here we used a high-throughput interface-based protein design strategy to identify mutational hotspots and potential signatures of adaptation in these drug binding sites of Mpro . Several mutants exhibited reduced binding affinity to these drugs, out of which hotspot residues having a strong tendency to undergo positive selection were identified . The data further indicated that these anti-HCV drugs have larger footprints in the mutational landscape of Mpro and hence encompass the highest potential for positive selection and adaptation . These findings are crucial in understanding the potential structural modifications in the drug binding sites of Mpro and thus highlight the adaptation signatures . Furthermore, the data could provide systemic strategies for robust antiviral design and discovery against COVID-19 in the future.