(340bs) Enzymatic Synthesis of Chemical Compounds.. | AIChE

(340bs) Enzymatic Synthesis of Chemical Compounds..


Sankaranarayanan, K. - Presenter, Massachusetts Institute of Technology
Khosla*, C., Stanford University
Jensen, K., Massachusetts Institute of Technology
Research Interests

Enzymatic syntheses often result in extraordinary efficiencies due to the stereo-, regio-, and enantio- selectivity afforded by enzymes. Further, they frequently yield greener processes compared to their chemocatalytic counterparts. Here, I will present (1) an illustrative example of an experimental platform to synthesize a complex natural product using enzymes (2) a computational tool that facilitates use of enzymes in synthetic applications.

The Lipid A family of glycolipids, found in the outer membranes of all Gram-negative bacteria, exhibits considerable structural diversity in both lipid and glycan moieties. The lack of facile methods to prepare analogues of these natural products represents a major roadblock in understanding the relationship between their structure and immunomodulatory activities. Here we present a modular, cell-free multienzymatic platform to access these structure−activity relationships. By individually purifying 19 Escherichia coli proteins and reconstituting them in vitro in the presence of acetyl-CoA, UDP-N- acetylglucosamine, NADPH, and ATP, we have developed a system capable of synthesizing Lipid IVA, the first bioactive intermediate in the Lipid A pathway. Our reconstituted multienzyme system revealed considerable promiscuity for orthologs with distinct substrate specificity, as illustrated by swapping enzymes from distantly related cyanobacterial and Pseudomonas species. Analysis of the agonistic and antagonistic activities of the resulting products against the THP-1 human monocytic cell line revealed hitherto unrecognized trends, while opening the door to harnessing the potent biological activities of these complex glycolipid natural products.

Encouraged by the experimental synthesis of Lipid A analogs, we developed a computational enzymatic synthesis planner to facilitate the use of enzymes in synthetic applications. To address this challenge, we (1) demonstrated that molecular similarity is an effective metric to propose retrosynthetic disconnections based on analogy to precedent enzymatic reactions in UniProt/ RHEA (2) trained a neural network capable of understanding the substrate promiscuity of enzymes and evaluating the likelihood of experimental success. We successfully planned enzymatic synthesis routes for both active pharmaceutical ingredients (e.g. Islatravir, Molnupiravir) and commodity chemicals (e.g. 1,4-butanediol, 1,3-propanediol, branched-chain higher alcohols/biofuels), in a retrospective fashion. Our approach provides an important first step towards solving the challenging problem of incorporating both enzymatic- and organic chemistry- based transformations into a computer aided synthesis planning workflow.


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