A combinatorially complete epistatic fitness landscape in an enzyme active site.

Protein engineering often targets binding pockets or active sites which are enriched in epistasis-nonadditive interactions between amino acid substitutions-and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable ß-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences-a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

Asymmetric Alkylation of Ketones Catalyzed by Engineered TrpB.

The ß-subunit of tryptophan synthase (TrpB) catalyzes a PLP-mediated ß-substitution reaction between indole and serine to form L-Trp. A succession of TrpB protein engineering campaigns to expand the enzyme's nucleophile substrate range has enabled the biocatalytic production of diverse non-canonical amino acids (ncAAs). Here, we show that ketone-derived enolates can serve as nucleophiles in the TrpB reaction to achieve the asymmetric alkylation of ketones, an outstanding challenge in synthetic chemistry. We engineered TrpB by directed evolution to catalyze the asymmetric alkylation of propiophenone and 2-fluoroacetophenone with a high degree of selectivity. In reactions with propiophenone, preference for the opposite product diastereomer emerges over the course of evolution, demonstrating that full control over the stereochemistry at the new chiral center can be achieved. The addition of this new reaction to the TrpB platform is a crucial first step toward the development of efficient methods to synthesize non-canonical prolines and other chirally dense nitrogen heterocycles.

Scalable continuous evolution for the generation of diverse enzyme variants encompassing promiscuous activities.

Enzyme orthologs sharing identical primary functions can have different promiscuous activities. While it is possible to mine this natural diversity to obtain useful biocatalysts, generating comparably rich ortholog diversity is difficult, as it is the product of deep evolutionary processes occurring in a multitude of separate species and populations. Here, we take a first step in recapitulating the depth and scale of natural ortholog evolution on laboratory timescales. Using a continuous directed evolution platform called OrthoRep, we rapidly evolve the Thermotoga maritima tryptophan synthase ß-subunit (TmTrpB) through multi-mutation pathways in many independent replicates, selecting only on TmTrpB's primary activity of synthesizing L-tryptophan from indole and L-serine. We find that the resulting sequence-diverse TmTrpB variants span a range of substrate profiles useful in industrial biocatalysis and suggest that the depth and scale of evolution that OrthoRep affords will be generally valuable in enzyme engineering and the evolution of biomolecular functions.