Lauko_2025_Science_388_eadu2454

Reference

Title : Computational design of serine hydrolases - Lauko_2025_Science_388_eadu2454
Author(s) : Lauko A , Pellock SJ , Sumida KH , Anishchenko I , Juergens D , Ahern W , Jeung J , Shida AF , Hunt A , Kalvet I , Norn C , Humphreys IR , Jamieson C , Krishna R , Kipnis Y , Kang A , Brackenbrough E , Bera AK , Sankaran B , Houk KN , Baker D
Ref : Science , 388 :eadu2454 , 2025
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 (k(cat)/K(m)) up to 2.2 x 10(5) M(-1) s(-1) and crystal structures that closely match the design models (Calpha 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.

PubMedSearch : Lauko_2025_Science_388_eadu2454
PubMedID: 39946508

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Citations formats

Lauko A, Pellock SJ, Sumida KH, Anishchenko I, Juergens D, Ahern W, Jeung J, Shida AF, Hunt A, Kalvet I, Norn C, Humphreys IR, Jamieson C, Krishna R, Kipnis Y, Kang A, Brackenbrough E, Bera AK, Sankaran B, Houk KN, Baker D (2025)
Computational design of serine hydrolases
Science 388 :eadu2454

Lauko A, Pellock SJ, Sumida KH, Anishchenko I, Juergens D, Ahern W, Jeung J, Shida AF, Hunt A, Kalvet I, Norn C, Humphreys IR, Jamieson C, Krishna R, Kipnis Y, Kang A, Brackenbrough E, Bera AK, Sankaran B, Houk KN, Baker D (2025)
Science 388 :eadu2454