Computer-assisted multistep chemoenzymatic retrosynthesis using a chemical synthesis planner

Area of Science:

• Chemical Synthesis
• Biocatalysis
• Computational Chemistry

Background:

• Chemoenzymatic synthesis combines organic and enzyme chemistry for efficient small molecule synthesis.
• Enzyme-catalyzed transformations offer sustainable and selective advantages in chemical manufacturing.
• Developing computational tools is crucial for planning complex chemoenzymatic routes.

Purpose of the Study:

• To develop a multistep retrosynthesis search algorithm for chemoenzymatic synthesis.
• To facilitate the planning of synthetic routes for pharmaceuticals, commodity chemicals, and specialty chemicals.
• To identify potential enzyme-catalyzed transformations within synthetic pathways.

Main Methods:

• Employed the ASKCOS synthesis planner for multistep synthesis design.
• Utilized a curated database of biocatalytic reaction rules from RetroBioCat.
• Integrated enzyme catalysis identification into the retrosynthesis search algorithm.

Main Results:

• Successfully planned chemoenzymatic routes for various compounds including Sitagliptin, Rivastigmine, Ephedrine, acrylamide, glycolic acid, S-Metalochlor, and Vanillin.
• Identified enzymatic transformations that reduce the overall number of synthetic steps.
• Recovered published synthetic routes and proposed novel alternative pathways.

Conclusions:

• The developed algorithm provides a robust strategy for chemoenzymatic synthesis planning.
• It effectively identifies candidate transformations suitable for enzyme catalysis.
• This approach enhances the efficiency and sustainability of chemical manufacturing.