Theoretical Considerations and Computational Analysis of the Complexity in Polyketide Synthesis Pathways

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The emergence of antimicrobial resistance and the growing concern to produce new drugs have influenced an increase in the amount of research directed towards the engineering of novel polyketides. The polyketide carbon backbone is synthesized by a set of enzymes known as polyketide synthases (PKSs). These catalyze the formation of a linear chain and its subsequent cyclization and thus control the variables in the synthesis, and a change in the organization of the PKS leads to the synthesis of a different polyketide structure. Although only 10,000 polyketide structures have been discovered to date, the theoretical analysis of the mechanism for the formation of the chain performed suggests that over a billion possible linear structures can be synthesized. The complexity in the number of structures led to the implementation of this system in <em>Biochemical Network Integrated Computational Explorer <\em>(BNICE), a computational framework that is being developed for the study of cellular reaction networks. This formulation allowed the analysis of the evolution of diversity in the synthesis mechanism and the construction of the pathway architecture of polyketide biosynthesis. However, the original framework utilized graph theory to represent reactions as a series of matrix operations, an approach that did not distinguish between stereochemical isomers. Since enzymes are known for their stereoselective catalysis, the framework was expanded to differentiate stereoisomers as distinct structures and for the specification of the stereochemistry obtained through a reaction. Consequently, the framework can be used to identify all the possible polyketide structures that can theoretically be produced as well as the corresponding PKS organization required to synthesize each of the structures. The feasibility of the implementation of polyketide synthesis in <em>Escherichia coli<\em> as a heterologous host was assessed through the use of metabolic flux analysis in a genome-scale model of <em>E. coli<\em>, showing that there is a complex interplay between cellular energetics, oxygen uptake rates and polyketide production yield. Consequently, this framework can be used to assess the cellular feasibility for the synthesis of novel polyketides, thereby guiding metabolic engineering actions to produce a potential therapeutic agent

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  • 06/25/2018
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