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The roles of local interactions in the laboratory evolution of a highly active, computationally designed retroaldolase (RA) are examined. Partial Order Optimum Likelihood (POOL) is used to identify catalytically important amino acid interactions in several RA95 enzyme variants. The series RA95.5, RA95.5–5, RA95.5–8, and RA95.5–8F, representing progress along an evolutionary trajectory with increasing activity, is examined. Computed measures of coupling between charged states of residues show that, as evolution proceeds and higher activities are achieved, electrostatic coupling between the biochemically active amino acids and other residues is increased. In silico residue scanning suggests multiple coupling partners for the catalytic lysine K83. The effects of two predicted partners, Y51 and E85, are tested using site‐directed mutagenesis and kinetic analysis of the variants Y51F and E85Q. The Y51F variants show decreases ink_catrelative to wild type, with the greatest losses observed for the more evolved constructs; they also exhibit significant decreases ink_cat/K_Macross the series. Only modest decreases ink_cat/K_Mare observed for the E85Q variants with little effect onk_cat. Computed metrics of the degree of coupling between protonation states rise significantly as evolution proceeds and catalytic turnover rate increases. Specifically, the charge state of the catalytic lysine K83 becomes more strongly coupled to those of other amino acids as the enzyme evolves to a better catalyst.

Regulation of enzymatic activity is vital to living organisms. Here, we report the development and the genetic optimization of an artificial zymogen requiring the action of a natural protease to upregulate its latent asymmetric transfer hydrogenase activity.