BibTex format
@article{Yamaguchi:2026,
author = {Yamaguchi, H and Isalan, M},
journal = {Scientific Reports},
title = {Loop engineering and activity improvement of TEV protease by a phagemid-based selection system},
year = {2026}
}
Citation
RIS format (EndNote, RefMan)
TY - JOUR
AB - Loop engineering of enzymes remains challenging due to high flexibility and conformational complexity, posing a bottleneck for deep-learning-based design. Here, we constructed mutant libraries for three loops of TEV protease to assess combining directed evolution with deep learning. Using an M13 phagemid-based selection system, the three libraries were screened, resulting in a Loop 1 variant (HyperTEV60/L1) that significantly enhanced the Miichaelis constant (Km) of the HyperTEV60 scaffold, a highly active mutant identified byProteinMPNN. Structural modeling suggested that a single-residue deletion and substitution in Loop 1 expands the substrate binding pocket, accounting for the improved Km. Although the catalytic efficiency kcat/Km of HyperTEV60/L1 was only marginally higher than HyperTEV60, due to a kcat decrease, our results reveal that the phagemid-based selection system tended to find variants optimizing Km. This study demonstrates that combining deep- learning-based global optimization with localized directed evolution maximizes the probability of discovering distinct, high-performance enzyme variants.
AU - Yamaguchi,H
AU - Isalan,M
PY - 2026///
SN - 2045-2322
TI - Loop engineering and activity improvement of TEV protease by a phagemid-based selection system
T2 - Scientific Reports
ER -
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