Connecting chemical and protein sequence space to predict biocatalytic reactions.

Abstract

The application of biocatalysis in synthesis has the potential to offer streamlined routes towards target molecules¹, tunable catalyst-controlled selectivity², as well as processes with improved sustainability³. Despite these advantages, biocatalysis is often a high-risk strategy to implement, as identifying an enzyme capable of performing chemistry on a specific intermediate required for a synthesis can be a roadblock that requires extensive screening of enzymes and protein engineering to overcome⁴. Strategies for predicting which enzyme and small molecule are compatible have been hindered by the lack of well-studied biocatalytic reaction datasets⁵. The underexploration of connections between chemical and protein sequence space constrains navigation between these two landscapes. Here we report a two-phase effort relying on high-throughput experimentation to populate connections between productive substrate and enzyme pairs and the subsequent development of a tool, CATNIP, for predicting compatible α-ketoglutarate (α-KG)/Fe(II)-dependent enzymes for a given substrate or, conversely, for ranking potential substrates for a given α-KG/Fe(II)-dependent enzyme sequence. We anticipate that our approach can be readily expanded to further enzyme and transformation classes and will derisk the investigation and application of biocatalytic methods.