Analyzing Biochemical Pathways Using Neural Networks and Genetic Algorithms
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Abstract
The analysis of biochemical pathways has recently gained much interest as these are the processes that keep us alive. A deeper understanding of biochemical reactions must analyze them at atomic resolution. In order to achieve that we have developed a reaction database with the information on the well known Biochemical Pathways wall chart. Based on that, 3D models of the substrates and intermediates of biochemical reactions can be built. It is shown how this information can be used for searching for inhibitors of enzyme catalyzed reactions by superimposition of 3D structures with a genetic algorithm. Physicochemical properties of the bonds directly involved in the reaction event allow a classification of these enzyme catalyzed reactions by self-organizing neural networks. This classification is compared with the enzyme code (EC) classification.
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