Analyzing Biochemical Pathways Using Neural Networks and Genetic Algorithms
Johann Gasteiger A C , Martin Reitz A , Yongquan Han A and Oliver Sacher BA Computer-Chemie-Centrum, University of Erlangen-Nuremberg, 91052 Erlangen, Germany.
B Molecular Networks GmbH, Naegelsbachstr. 25, 91052 Erlangen, Germany.
C Corresponding author. Email: johann.gasteiger@chemie.uni-erlangen.de
Australian Journal of Chemistry 59(12) 854-858 https://doi.org/10.1071/CH06140
Submitted: 2 May 2006 Accepted: 11 July 2006 Published: 20 December 2006
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.
Acknowledgments
The work reported here was funded by the BMBF projects no. 08 C 5850 0, 08 C 5879, 031U112D, 031U212D, 031U112A, and 031U212A.
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A www.biocyc.org
B Available from Molecular Networks GmbH. www.mol-net.com
C Can be tested online. www2.chemie.uni-erlangen.de/software/corina/free_struct.html
D www.brenda.uni-koeln.de
E www.expasy.org/tools/pathways
F www.mol-net.com/databases/biopath.html
G www2.chemie.uni-erlangen.de/services/biopath/index.html