Human rhinovirus 3C protease (HRV 3CP) has a high specificity against the substrate of LEVLFQ↓G at P1' site, which plays an important role in biotechnology and academia as a fusion tag removal tool. However, a non-ignorable limitation is that an extra residue of Gly would remain at the N terminus of the recombinant target protein after cleavage with HRV 3CP, thus potentially causing protein mis-functionality or immunogenicity. Here, we developed a combinatorial strategy by integrating structure-guided library design and high-throughput screening of eYESS approach for HRV 3CP engineering to expand its P1' specificity. Finally, a C3 variant was obtained, exhibiting a broad substrate P1' specificity to recognize 20 different amino acids with the highest activity against LEVLFQ↓M (k/K = 3.72 ± 0.04 mM∙s). Further biochemical and NGS-mediated substrate profiling analysis showed that C3 variant still kept its substrate stringency at P1 site and good residue tolerance at P2' site, but with an expanded P1' specificity. Structural simulation of C3 indicated a reconstructed S1' binding pocket as well as new interactions with the substrates. Overall, our studies here prompt not only the practical applications and understanding of substrate recognition mechanisms of HRV 3CP, also provide new tools for other enzyme engineering.