
==== Front
bioRxiv
BIORXIV
bioRxiv
2692-8205
Cold Spring Harbor Laboratory

10.1101/2024.08.29.610411
preprint
1
Article
Computational design of serine hydrolases
Lauko Anna http://orcid.org/0000-0001-5903-3518

Pellock Samuel J. http://orcid.org/0000-0002-7557-7985

Anischanka Ivan
Sumida Kiera H. http://orcid.org/0000-0003-2773-9676

Juergens David http://orcid.org/0000-0001-6425-8391

Ahern Woody http://orcid.org/0009-0006-1247-8847

Shida Alex
Hunt Andrew http://orcid.org/0000-0001-9620-593X

Kalvet Indrek http://orcid.org/0000-0002-6610-2857

Norn Christoffer http://orcid.org/0000-0002-1450-4651

Humphreys Ian R. http://orcid.org/0000-0002-3058-6714

Jamieson Cooper http://orcid.org/0000-0002-6076-6230

Kang Alex
Brackenbrough Evans http://orcid.org/0009-0004-1476-0219

Bera Asim K.
Sankaran Banumathi
Houk K. N.
Baker David http://orcid.org/0000-0003-3645-2044

30 8 2024
2024.08.29.610411https://creativecommons.org/licenses/by-nd/4.0/ This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License, which allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use.
http://biorxiv.org/lookup/doi/10.1101/2024.08.29.610411
nihpp-2024.08.29.610411.pdf
Abstract

Enzymes that proceed through multistep reaction mechanisms often utilize complex, polar active sites positioned with sub-angstrom precision to mediate distinct chemical steps, which makes their de novo construction extremely challenging. We sought to overcome this challenge using the classic catalytic triad and oxyanion hole of serine hydrolases as a model system. We used RFdiffusion 1 to generate proteins housing catalytic sites of increasing complexity and varying geometry, and a newly developed ensemble generation method called ChemNet to assess active site geometry and preorganization at each step of the reaction. Experimental characterization revealed novel serine hydrolases that catalyze ester hydrolysis with catalytic efficiencies ( k cat / K m ) up to 3.8 × 10 3 M -1 s -1 , closely match the design models (Cα RMSDs < 1 Å), and have folds distinct from natural serine hydrolases. In silico selection of designs based on active site preorganization across the reaction coordinate considerably increased success rates, enabling identification of new catalysts in screens of as few as 20 designs. Our de novo buildup approach provides insight into the geometric determinants of catalysis that complements what can be obtained from structural and mutational studies of native enzymes (in which catalytic group geometry and active site makeup cannot be so systematically varied), and provides a roadmap for the design of industrially relevant serine hydrolases and, more generally, for designing complex enzymes that catalyze multi-step transformations.
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