# Active site diversification of a non‐canonical amino acid decarboxylase by merging substrate multiplexed screening with computationally guided recombination

## TL;DR

Scientists improved an enzyme's ability to work with non-standard amino acids by combining smart screening and computational methods.

## Contribution

A new method combining substrate-multiplexed screening and computational recombination to diversify enzyme active sites efficiently.

## Key findings

- A screening method called SUMS helped identify active enzyme variants with altered specificity.
- A small screening effort (<200 measurements) trained a model to enrich active enzyme regions.
- One enzyme variant showed a 500-fold increase in catalytic efficiency compared to the wild-type.

## Abstract

Recombination of active site mutations is a powerful strategy to alter enzyme activity. The vastness of sequence space, however, often limits screening‐based engineering to single and double site libraries. Here, we explore focused recombination across five positions that enclose the active site of a tryptophan (Trp) decarboxylase. Our goal was to maximize the sequence diversity of enzymes that decarboxylate non‐canonical amino acids (ncAAs) with minimal screening effort. We used substrate‐multiplexed screening (SUMS) to distinguish recombinants that have impaired activity with all substrates from those that have altered specificity. In this way, we identified a larger fraction of active sequence space than could be found by single substrate screening alone. Wild‐type primer doping during library assembly enabled the enrichment of double and triple mutants while simultaneously scanning five positions. A small screening effort, <200 measurements, was sufficient to train a logistic regression model that enriched active regions of the recombination space. This iterative strategy to library design resulted in TDC variants with distinct promiscuity profiles, and one variant displayed a nearly 500‐fold increase in catalytic efficiency compared to wild‐type TDC. These results illustrate how SUMS can be combined with iterative, deep recombination to generate a panel of catalytically diverse active site architectures.