Until now, computationally designed enzymes exhibited low catalytic rates1–5 and required intensive experimental optimization to reach activity levels observed in comparable natural enzymes5–9. These results exposed limitations in design methodology and suggested critical gaps in our understanding of the fundamentals of biocatalysis10,11. We present a fully computational workflow for designing efficient enzymes in TIM-barrel folds using backbone fragments from natural proteins and without requiring optimization by mutant-library screening. Three Kemp eliminase designs exhibit efficiencies greater than 2,000 M−1 s−1. The most efficient shows more than 140 mutations from any natural protein, including a novel active site. It exhibits high stability (greater than 85 °C) and remarkable catalytic efficiency (12,700 M−1 s−1) and rate (2.8 s−1), surpassing previous computational designs by two orders of magnitude1–5. Furthermore, designing a residue considered essential in all previous Kemp eliminase designs increases efficiency to more than 105 M−1 s−1 and rate to 30 s−1, achieving catalytic parameters comparable to natural enzymes and challenging fundamental biocatalytic assumptions. By overcoming limitations in design methodology11, our strategy enables programming stable, high-efficiency, new-to-nature enzymes through a minimal experimental effort.
