Similarity based enzymatic retrosynthesis

• Published in: Chemical science (Cambridge) 2022-05, Vol.13 (2), p.639-653
• Main Authors: Sankaranarayanan, Karthik, Heid, Esther, Coley, Connor W, Verma, Deeptak, Green, William H, Jensen, Klavs F
• Format: Article
• Language: English
• Subjects: Alcohols; Biodegradability; Biofuels; Butanediol; Chain branching; Chemistry; Enzymes; Evolution; Graph theory; Homology; Knowledge bases (artificial intelligence); Natural products; Search algorithms; Similarity; Statistical models; Transformations; Workflow
• ISSN: 2041-6520; 2041-6539
• DOI: 10.1039/d2sc01588a

Enzymes synthesize complex natural products effortlessly by catalyzing chemo-, regio-, and enantio-selective transformations. Further, biocatalytic processes are increasingly replacing conventional organic synthesis steps because they use mild solvents, avoid the use of metals, and reduce overall non-biodegradable waste. Here, we present a single-step retrosynthesis search algorithm to facilitate enzymatic synthesis of natural product analogs. First, we develop a tool, RDEnzyme, capable of extracting and applying stereochemically consistent enzymatic reaction templates, i.e. , subgraph patterns that describe the changes in connectivity between a product molecule and its corresponding reactant(s). Using RDEnzyme, we demonstrate that molecular similarity is an effective metric to propose retrosynthetic disconnections based on analogy to precedent enzymatic reactions in UniProt/RHEA. Using ∼5500 reactions from RHEA as a knowledge base, the recorded reactants to the product are among the top 10 proposed suggestions in 71% of ∼700 test reactions. Second, we trained a statistical model capable of discriminating between reaction pairs belonging to homologous enzymes and evolutionarily distant enzymes using ∼30 000 reaction pairs from SwissProt as a knowledge base. This model is capable of understanding patterns in enzyme promiscuity to evaluate the likelihood of experimental evolution success. By recursively applying the similarity-based single-step retrosynthesis and evolution prediction workflow, we successfully plan the enzymatic synthesis routes for both active pharmaceutical ingredients ( e.g. Islatravir, Molnupiravir) and commodity chemicals ( e.g. 1,4-butanediol, branched-chain higher alcohols/biofuels), in a retrospective fashion. Through the development and demonstration of the single-step enzymatic retrosynthesis strategy using natural transformations, our approach provides a first step towards solving the challenging problem of incorporating both enzyme- and organic-chemistry based transformations into a computer aided synthesis planning workflow. Using a large database of enzymatic transformations, similarity based enzymatic retrosynthesis search algorithm takes a holistic approach to enzymatic synthesis planning to yield a diverse set of single-step suggestions.