Directed evolution is a powerful technique for generating tailor-made enzymes for a wide range of biocatalytic applications. Following the principles of natural evolution, iterative cycles of mutagenesis and screening or selection are applied to modify protein properties, enhance catalytic activities, or develop completely new protein catalysts for non-natural chemical transformations. This review briefly surveys the experimental methods used to generate genetic diversity and screen or select for improved enzyme variants. Emphasis is placed on a key challenge, namely how to generate novel catalytic activities that expand the scope of natural reactions. Two particularly effective strategies, exploiting catalytic promiscuity and rational design, are illustrated by representative examples of successfully evolved enzymes. Opportunities for extending these approaches to more complex biocatalytic systems are also considered.

Temperature influences the reaction kinetics and evolvability of all enzymes. To understand how evolution shapes the thermodynamic drivers of catalysis, we optimized the modest activity of a computationally designed enzyme for an elementary proton-transfer reaction by nearly 4 orders of magnitude over 9 rounds of mutagenesis and screening. As theorized for primordial enzymes, the catalytic effects of the original design were almost entirely enthalpic in origin, as were the rate enhancements achieved by laboratory evolution. However, the large reductions in ΔH ⧧ were partially offset by a decrease in TΔS ⧧ and unexpectedly accompanied by a negative activation heat capacity, signaling strong adaptation to the operating temperature. These findings echo reports of temperature-dependent activation parameters for highly evolved natural enzymes and are relevant to explanations of enzymatic catalysis and adaptation to changing thermal environments.

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 10 5 -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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