A computational framework for the discovery of novel biotransformations
The large no. of chem. transformations involved in biochem. pathways and the even larger no. of enzymes that catalyze these transformations contribute to the complexity of biol. systems. Anal. of the available genome sequences, as well as results from prior and current biochem. research, suggest that while many of these transformations are common in most of the organisms, there are many organism-specific pathways, and many new enzymes and transformations remain to be discovered. We have focused on the development of a computational framework that identifies novel biotransformation pathways based on the rules of enzyme function and evaluates the alternative pathways with respect to their thermodn. feasibility. The framework is based on graph theoretic methodologies. Graph theory provides the foundation for applying mathematics and assocd. algorithms to represent biochem. As applied to biochem., this allows for the identification of sep. mols. down to the isomeric level and provides the fundamental framework for computer generation of reactions and pathways. Representing mols. as graphs, or an equiv. matrix representation, allows biochem. reaction to be carried out using matrix addn. To apply this approach to biochem. reactions, it is necessary to det. and specify the reaction matrixes, or operators, that capture the biochem. transformations of interest. Through repetitive application of the set of reaction matrixes representing the enzymic reactions of interest to the reactants and their progeny, reaction pathways are generated automatically. The reactions must be carried out in a logical fashion to ensure that all species undergo their allowable reactions. The reactants and the products are assembled into the form of a reaction and added to the growing list of reactions. An unreacted species is obtained from the list, and the algorithm is repeated. The output of the pathway generation algorithm is a set of mols. and paths connecting them based on likely enzyme-catalyzed transformations. The application of this framework to tryptophan biosythesis will be discussed. [on SciFinder (R)]
FIELD Section Title:
Chemical Engineering, CMBL,Northwestern University,Evanston,IL,USA. FIELD URL:
written in English.
Record created on 2007-01-11, modified on 2016-08-08