Structure-based design of small imine reductase panels for target substrates

Biocatalysis is important in the discovery, development and manufacture of pharmaceuticals. However, the identification of enzymes for target transformations of interest requires major screening efforts. Here we report a structure-based computational workflow to prioritize protein sequences by a score based on predicted activities on substrates, thereby reducing resource intensive laboratory-based biocatalyst screening. We selected imine reductases (IREDs) as a class of biocatalysts to illustrate the application of the computational workflow termed IREDFisher. Validation by using published data showed that IREDFisher can retrieve the best enzymes and increase the hit rate by identifying the top 20 ranked sequences. The power of IREDFisher is confirmed by computationally screening 1,400 sequences for chosen reductive amination reactions with different levels of complexity. Highly active IREDs were identified by only testing 20 samples in vitro. Our speed test shows it only takes 90 minutes to rank 85 sequences from user input and 30 minutes for the established IREDFisher database containing 591 IRED sequences. IREDFisher is available as a user-friendly web interface (https://enzymeevolver.com/IREDFisher). IREDFisher enables rapid discovery of IREDs for applications in synthesis and directed evolution studies, with minimal time and resource expenditure. Future use of the workflow with other enzyme families could be implemented following modification of the workflow scoring function.