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Amine transaminases (ATAs) are powerful biocatalysts for the stereoselective synthesis of chiral amines. Machine learning provides a promising approach for protein engineering, but activity prediction models for ATAs remain elusive due to the difficulty of obtaining high-quality training data. Thus, we first created variants of the ATA from Ruegeria sp. (3FCR) with improved catalytic activity (up to 2000-fold) as well as reversed stereoselectivity by a structure-dependent rational design and collected a high-quality dataset in this process. Subsequently, we designed a modified one-hot code to describe steric and electronic effects of substrates and residues within ATAs. Finally, we built a gradient boosting regression tree predictor for catalytic activity and stereoselectivity, and applied this for the data-driven design of optimized variants which then showed improved activity (up to 3-fold compared to the best variants previously identified). We also demonstrated that the model can predict the catalytic activity for ATA variants of another origin by retraining with a small set of additional data.

The enzymatic transamination of ketones into (

International audience; The enzymatic transamination of ketones into (R)-amines represents an important route for accessing a range of pharmaceuticals or building blocks. Although many publications have dealt with enzyme discovery, protein engineering, and the application of (R)-selective amine transaminases [(R)-ATA] in biocatalysis, little is known about the actual in vivo role and how these enzymes have evolved from the ubiquitous a-amino acid transaminases (alpha-AATs). Here, we show the successful introduction of an (R)-transaminase activity in an alpha-amino acid aminotransferase with one to six amino acid substitutions in the enzyme's active site. Bioinformatic analysis combined with computational redesign of the D-amino acid aminotransferase (DATA) led to the identification of a sextuple variant having a specific activity of 326 milliunits mg(-1) in the conversion of (R)-phenylethylamine and pyruvate to acetophenone and b-alanine. This value is similar to those of natural (R)-ATAs, which typically are in the range of 250 milliunits mg(-1). These results demonstrate that (R)-ATAs can evolve from alpha-AAT as shown here for the DATA scaffold.