Retrosynthetic design of metabolic pathways to chemicals not found in nature. Issue 14 (April 2019)

• Record Type: Journal Article
• Authors: Lin, Geng-Min; Warden-Rothman, Robert; Voigt, Christopher A.
• Is Part Of: Current opinion in systems biology. Issue 14(2019)
• Page Start: 82
• Page End: 107
• Publication Date: 2019-04
• Subjects: Synthetic biology -- Systems biology -- Artificial intelligence -- Machine learning; Systems biology -- Periodicals; 570
• DOI: 10.1016/j.coisb.2019.04.004
• Languages: English
• ISSNs: 2452-3100

Abstract

Abstract: Biology produces a universe of chemicals whose precision and complexity is the envy of chemists. Over the last 30 years, the expansive field of metabolic engineering has many successes in optimizing the overproduction of metabolites of industrial interest, including moving natural product pathways to production hosts ( e.g ., plants to yeast). However, there are stunningly few examples where enzymes are artificially combined to make a chemical that is not found somewhere in nature. Here, we review these efforts and discuss the challenges limiting the construction of such pathways. An analogy is made to the retrosynthesis problem solved in chemistry using algorithmic approaches, recently harnessing artificial intelligence, noting key differences in the needs of the optimization problem. When these issues are addressed, we see a future where chemistry and biology are intertwined in reaction networks that draw on the power of both to build currently unobtainable molecules across consumer, industrial, and defense applications.