Complete computational design of high-efficiency Kemp elimination enzymes

Until now, computationally designed enzymes exhibited low catalytic rates<sup>1-5</sup> and required intensive experimental optimization to reach activity levels observed in comparable natural enzymes<sup>5-9</sup>. These results exposed limitations in design methodology and suggested critical gaps in our understanding of the fundamentals of biocatalysis<sup>10,11</sup>. 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<sup>-1</sup> s<sup>-1</sup>. 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<sup>-1</sup> s<sup>-1</sup>) and rate (2.8 s<sup>-1</sup>), surpassing previous computational designs by two orders of magnitude<sup>1-5</sup>. Furthermore, designing a residue considered essential in all previous Kemp eliminase designs increases efficiency to more than 10<sup>5</sup> M<sup>-1</sup> s<sup>-1</sup> and rate to 30 s<sup>-1</sup>, achieving catalytic parameters comparable to natural enzymes and challenging fundamental biocatalytic assumptions. By overcoming limitations in design methodology<sup>11</sup>, our strategy enables programming stable, high-efficiency, new-to-nature enzymes through a minimal experimental effort.

Authors

Institutions

Publication Details

Journal
Nature
Published
2025-06-18
DOI
https://doi.org/10.1038/s41586-025-09136-2
Citations
24
Primary Topic
Enzyme Structure and Function
Type
article
Field-Weighted Citation Impact
12.43
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Complete computational design of high-efficiency Kemp elimination enzymes

Shelly Hamer-Rogotner, Shlomo Yakir Hoch, Orly Dym, Dina Listov et al.
24 citations
Nature
Enzyme Structure and Function
12.43
article

Complete computational design of high-efficiency Kemp elimination enzymes

Shelly Hamer-Rogotner, Shlomo Yakir Hoch, Orly Dym, Dina Listov, Sarel Jacob Fleishman, Gyula Hoffka, Eva Vos, Shina Caroline Lynn Kamerlin, Andrej Berg
article en
24 citations

Abstract

Until now, computationally designed enzymes exhibited low catalytic rates<sup>1-5</sup> and required intensive experimental optimization to reach activity levels observed in comparable natural enzymes<sup>5-9</sup>. These results exposed limitations in design methodology and suggested critical gaps in our understanding of the fundamentals of biocatalysis<sup>10,11</sup>. 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<sup>-1</sup> s<sup>-1</sup>. 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<sup>-1</sup> s<sup>-1</sup>) and rate (2.8 s<sup>-1</sup>), surpassing previous computational designs by two orders of magnitude<sup>1-5</sup>. Furthermore, designing a residue considered essential in all previous Kemp eliminase designs increases efficiency to more than 10<sup>5</sup> M<sup>-1</sup> s<sup>-1</sup> and rate to 30 s<sup>-1</sup>, achieving catalytic parameters comparable to natural enzymes and challenging fundamental biocatalytic assumptions. By overcoming limitations in design methodology<sup>11</sup>, our strategy enables programming stable, high-efficiency, new-to-nature enzymes through a minimal experimental effort.

NatureVol. 643(8074)
Uppsala University (SE), Georgia Institute of Technology (US), University of Debrecen (HU), Lund University (SE), Weizmann Institute of Science (IL)
Openalex Percentile: Top 1%
Enzyme Structure and Function
12.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.