Objective Living organisms utilize enzyme-catalyzed reactions to synthesize a large array of complex molecules and macromolecules. Enzyme catalyzed processes are characterized by mild conditions, fast reaction rates, highly stereospecific interactions, and minimal byproduct formation. Visualization and control of these living processes will enable researchers to ‘engineer’ metabolic systems; for example the creation of renewable carbon resources or novel pharmaceuticals. The complexity of biological systems dictates that a computational framework be used for the identification of chemicals novel to biological systems and the rational design of the biosynthetic routes that lead to these novel chemicals. The focus of this group is to build a systematic framework for the discovery and evaluation of novel pathways that could lead to novel chemicals. Approach Enzymes are
commonly classified by catalytic function. A computer uses the framework
to interpret this classification system as a set of rules for functional
group transformations of enzyme-catalyzed reactions. Manipulating this
framework enables the researcher to see where and how a novel species
may be generated from a given substrate (e.g. A new cancer drug from sucrose).
Graph theory draws together the math, statistical, chemical and other
concepts necessary to evaluate pathways into a comprehensive picture which
may be used to effectively perceive the whole network. Results The biosynthetic ability of the shikimate pathway was explored and the results show not only the reconstruction of the natural pathway, but new pathways leading to chemicals novel to biological systems.
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[Polymer Recovery] | [Catalysis] | [Mechanistic Modeling] | [Novel Biochemical Transformations]
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