4.8 Article

Computer-assisted multistep chemoenzymatic retrosynthesis using a chemical synthesis planner

Journal

CHEMICAL SCIENCE
Volume 14, Issue 23, Pages 6467-6475

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/d3sc01355c

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Chemoenzymatic synthesis methods combine organic and enzyme chemistry to efficiently synthesize small molecules. A multistep retrosynthesis search algorithm is presented in this study to facilitate the chemoenzymatic synthesis of various compounds. The algorithm uses a synthesis planner and a biocatalytic reaction database to identify enzyme-catalyzed reactions and plan synthetic routes for pharmaceutical, specialty, and commodity chemicals. The approach successfully plans chemoenzymatic routes for different compounds and proposes alternative pathways as well.
Chemoenzymatic synthesis methods use organic and enzyme chemistry to synthesize a desired small molecule. Complementing organic synthesis with enzyme-catalyzed selective transformations under mild conditions enables more sustainable and synthetically efficient chemical manufacturing. Here, we present a multistep retrosynthesis search algorithm to facilitate chemoenzymatic synthesis of pharmaceutical compounds, specialty chemicals, commodity chemicals, and monomers. First, we employ the synthesis planner ASKCOS to plan multistep syntheses starting from commercially available materials. Then, we identify transformations that can be catalyzed by enzymes using a small database of biocatalytic reaction rules previously curated for RetroBioCat, a computer-aided synthesis planning tool for biocatalytic cascades. Enzymatic suggestions captured by the approach include ones capable of reducing the number of synthetic steps. We successfully plan chemoenzymatic routes for active pharmaceutical ingredients or their intermediates (e.g., Sitagliptin, Rivastigmine, and Ephedrine), commodity chemicals (e.g., acrylamide and glycolic acid), and specialty chemicals (e.g., S-Metalochlor and Vanillin), in a retrospective fashion. In addition to recovering published routes, the algorithm proposes many sensible alternative pathways. Our approach provides a chemoenzymatic synthesis planning strategy by identifying synthetic transformations that could be candidates for enzyme catalysis.

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