Literature DB >> 28783336

Optimization of Enzyme Mechanism along the Evolutionary Trajectory of a Computationally Designed (Retro-)Aldolase.

Cathleen Zeymer1, Reinhard Zschoche1, Donald Hilvert1.   

Abstract

De novo biocatalysts have been successfully generated by computational design and subsequent experimental optimization. Here, we examined the evolutionary history of the computationally designed (retro-)aldolase RA95. The modest activity of the starting enzyme was previously improved 105-fold over many rounds of mutagenesis and screening to afford a proficient biocatalyst for enantioselective cleavage and synthesis of β-hydroxyketones. Using a set of representative RA95 variants, we probed individual steps in the multistep reaction pathway to determine which processes limit steady-state turnover and how mutations that accumulated along the evolutionary trajectory influenced the kinetic mechanism. We found that the overall rate-limiting step for aldol cleavage shifted from C-C bond scission (or an earlier step in the pathway) for the computational design to product release for the evolved enzymes. Specifically, interconversion of Schiff base and enamine intermediates, formed covalently between acetone and the catalytic lysine residue, was found to be the slowest step for the most active variants. A complex hydrogen bond network of four active site residues, which was installed in the late stages of laboratory evolution, apparently enhances lysine reactivity and facilitates efficient proton shuffling. This catalytic tetrad accounts for the tremendous rate acceleration observed for all steps of the mechanism, most notably Schiff base formation and hydrolysis. Comparison of our results with kinetic and structural studies on natural aldolases provides valuable feedback for computational enzyme design and laboratory evolution approaches alike.

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Year:  2017        PMID: 28783336     DOI: 10.1021/jacs.7b05796

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  14 in total

1.  Directed Evolution's Influence on Rapid Density Fluctuations Illustrates How Protein Dynamics Can Become Coupled to Chemistry.

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2.  Optimization of the Turnover in Artificial Enzymes via Directed Evolution Results in the Coupling of Protein Dynamics to Chemistry.

Authors:  Joseph W Schafer; Ioanna Zoi; Dimitri Antoniou; Steven D Schwartz
Journal:  J Am Chem Soc       Date:  2019-06-24       Impact factor: 15.419

Review 3.  A mechanistic view of enzyme evolution.

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4.  Screening and characterization of a diverse panel of metagenomic imine reductases for biocatalytic reductive amination.

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Journal:  Nat Chem       Date:  2020-12-30       Impact factor: 24.427

5.  Directed Evolution Mimics Allosteric Activation by Stepwise Tuning of the Conformational Ensemble.

Authors:  Andrew R Buller; Paul van Roye; Jackson K B Cahn; Remkes A Scheele; Michael Herger; Frances H Arnold
Journal:  J Am Chem Soc       Date:  2018-05-17       Impact factor: 15.419

6.  Evolution of Enzyme Function and the Development of Catalytic Efficiency: Triosephosphate Isomerase, Jeremy R. Knowles, and W. John Albery.

Authors:  John A Gerlt
Journal:  Biochemistry       Date:  2021-05-20       Impact factor: 3.321

7.  Role of Conformational Dynamics in the Evolution of Retro-Aldolase Activity.

Authors:  Adrian Romero-Rivera; Marc Garcia-Borràs; Sílvia Osuna
Journal:  ACS Catal       Date:  2017-11-03       Impact factor: 13.084

8.  Complete Switch of Reaction Specificity of an Aldolase by Directed Evolution In Vitro: Synthesis of Generic Aliphatic Aldol Products.

Authors:  Sebastian Junker; Raquel Roldan; Henk-Jan Joosten; Pere Clapés; Wolf-Dieter Fessner
Journal:  Angew Chem Int Ed Engl       Date:  2018-07-04       Impact factor: 15.336

9.  Protein Flexibility and Stiffness Enable Efficient Enzymatic Catalysis.

Authors:  John P Richard
Journal:  J Am Chem Soc       Date:  2019-02-14       Impact factor: 15.419

10.  Analysis of electrostatic coupling throughout the laboratory evolution of a designed retroaldolase.

Authors:  Timothy A Coulther; Moritz Pott; Cathleen Zeymer; Donald Hilvert; Mary Jo Ondrechen
Journal:  Protein Sci       Date:  2021-05-24       Impact factor: 6.725

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