Identification of promiscuous ene-reductase activity by mining structural databases using active site constellations

Abstract

The exploitation of catalytic promiscuity and the application of de novo design have recently opened the access to novel, non-natural enzymatic activities. Here we describe a structural bioinformatic method for predicting catalytic activities of enzymes based on three-dimensional constellations of functional groups in active sites (‘catalophores’). As a proof-of-concept we identify two enzymes with predicted promiscuous ene-reductase activity (reduction of activated C–C double bonds) and compare them with known ene-reductases, that is, members of the Old Yellow Enzyme family. Despite completely different amino acid sequences, overall structures and protein folds, high-resolution crystal structures reveal equivalent binding modes of typical Old Yellow Enzyme substrates and ligands. Biochemical and biocatalytic data show that the two enzymes indeed possess ene-reductase activity and reveal an inverted stereopreference compared with Old Yellow Enzymes for some substrates. This method could thus be a tool for the identification of viable starting points for the development and engineering of novel biocatalysts. Enzymes are very efficient reaction catalysts, though taking advantage of this synthetically is hampered by their notorious specificity. Here, the authors identify important arrangements of active site residues and use structural bioinformatics to successfully predict enzyme activity.