Functional Mapping of Key Residues in Reductive Aminases Enabled by a High-Throughput Assay.

Enzymatic reductive amination allows direct and stereoselective access to 1°, 2°, and 3° chiral amines under environmentally friendly reaction conditions. Enzyme discovery and engineering campaigns for this important transformation are crucial for industrial applications but currently rely on tedious and time-consuming screening of large libraries using expensive LC/LC-MS systems. Such engineering campaigns have also focused on optimizing a single aminase candidate per defined synthetic target. In this work, we have developed a versatile high-throughput (HTP) spectrophotometric/colorimetric assay for rapid and reliable quantitative monitoring of the aminase activity of recombinant aminase-expressing cells or unpurified cell extracts. The assay couples aminase product formation to an amine oxidase-HRP reporter system, yielding a colored dye/signal that can be monitored at 492/498 nm. We demonstrate its application to quantitatively monitor reductive amination reactions catalyzed by reductive aminases (RedAms), amine dehydrogenases (AmDHs), and amino acid dehydrogenases (AADHs). The assay enabled the HTP screening of 56 site saturation libraries in two RedAms, revealing 10 positions, including N113, D135, D188, Y196, W227, T234, Q257, A262, S270, and D297 in RedAm as important residues for RedAms' catalytic function/substrate specificity. Extending our screening to four substrate combinations enabled the identification of positions R53, T115, Y154, L189, M195, Y196, W227, and Q257 in RedAm (and equivalent positions: R35, T99, Y139, L174, M180, Y181, W211, and Q241 in RedAm) that yielded mutants with improved activity of up to 7-fold compared to the wild-type enzyme in at least three of the four transformations. We propose that these residues act as potential "universal" hotspots for engineering substrate specificity in these enzymes across diverse substrates. Our work lays an important foundation for mapping sequence-activity relationships in RedAms at the enzyme family level to pave the way for more predictable, faster, and cost-effective engineering of RedAms for applications.