Computational design of serine hydrolases

The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization at each step in the reaction to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies (<i>k</i><sub>cat</sub>/<i>K</i><sub>m</sub>) up to 2.2 × 10<sup>5</sup> M<sup>-1</sup> s<sup>-1</sup> and crystal structures that closely match the design models (Cα root mean square deviations <1 angstrom). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts remove with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.

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Publication Details

Journal
Science
Published
2025-02-13
DOI
https://doi.org/10.1126/science.adu2454
Citations
139
Primary Topic
Click Chemistry and Applications
Type
article
Field-Weighted Citation Impact
129.18
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article

Computational design of serine hydrolases

Indrek Kalvet, Woody Ahern, Yakov Kipnis, Asim K. Bera et al.
139 citations
Science
Click Chemistry and Applications
129.18
article

Computational design of serine hydrolases

Indrek Kalvet, Woody Ahern, Yakov Kipnis, Asim K. Bera, Kiera H. Sumida, Rohith Krishna, Samuel J. Pellock, Andrew C. Hunt, Kendall N. Houk, Alex Kang, David A. Baker, Cooper S. Jamieson, Christoffer Norn, Anna Lauko, Banumathi Sankaran, Ivan Anishchenko, David Juergens, Ji-Ung Jeung, Evans Brackenbrough, Ian R. Humphreys, Alex Shida
article en
139 citations

Abstract

The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization at each step in the reaction to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies (<i>k</i><sub>cat</sub>/<i>K</i><sub>m</sub>) up to 2.2 × 10<sup>5</sup> M<sup>-1</sup> s<sup>-1</sup> and crystal structures that closely match the design models (Cα root mean square deviations <1 angstrom). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts remove with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.

ScienceVol. 388(6744)
Howard Hughes Medical Institute (US), University of California, Los Angeles (US), University of Washington (US)
Openalex Percentile: Top 0%
Click Chemistry and Applications
129.18
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