Mining Medicinally Relevant Bioreduction Substrates Inspired by Ligand-Based Drug Design

Abstract

Exploring the scope of biocatalytic transformations in the absence of enzyme structures without extensive experimentation is a challenging task. To expand the limited substrate capacity of carrotmediated bioreduction and hunt for new medicinally relevant ketones with minimum cost of labor and time, we deployed a practical method inspired by ligand-based drug design. Through analyzing collected literature data and building pharmacophore and reactivity prediction models, we screened a self-built virtual library of >8000 ketones bearing the most frequently used N,O,S-heterocycles and functional groups in drug discovery. Representative examples were validated, expanding the bioreduction substrate scope. The public availability of our models alongside the straightforward screening workflow makes it time-, labor-, and cost-saving to evaluate unknown bioreduction substrates for medicinal chemistry applications, especially for a large set of structurally differentiated ketones. Our studies also showcase the novelty of utilizing medicinal chemistry principles to solve a general biocatalysis problem.