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Investigations of Enzyme-Catalyzed Reactions Based on Physicochemical Descriptors Applied to Hydrolases

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Oliver Sacher^†, Martin Reitz^‡ and Johann Gasteiger*^†^‡

Molecular Networks GmbH, Henkestrasse 91, D-91052 Erlangen, Germany, and Universität Erlangen-Nürnberg, Computer-Chemie-Centrum and Institute of Organic Chemistry, Nägelsbachstrasse 25, D-91052 Erlangen, Germany

J. Chem. Inf. Model., 2009, 49 (6), pp 1525–1534

DOI: 10.1021/ci800277f

Publication Date (Web): May 15, 2009

* To whom correspondence should be addressed. Tel: +49-9131-815668. Fax: +49-9131-815669. E-mail: gasteiger@molecular-networks.com. website: http://www.molecular-networks.com., †

Molecular Networks GmbH.

, ‡

Universität Erlangen-Nürnberg.

Section:

Enzymes

Abstract

The EC number system for the classification of enzymes uses different criteria such as reaction pattern, the nature of the substrate, the type of transferred groups or the type of acceptor group. These criteria are used with different emphasis for the various enzyme classes and thus do not contribute much to an understanding of the mechanisms of enzyme catalyzed reactions. To explore the reasons for bonds being broken in enzyme catalyzed metabolic reactions, we calculated physicochemical effects for the bonds reacting in the substrate of these enzymatic reactions. These descriptors allow the definition of similarities within these reactions and thus can serve as a method for the classification of enzyme reactions. To foster an understanding of the investigations performed here, we compare the similarities found on the basis of the physicochemical effects with the EC number classification. To allow a reasonable comparison we selected enzymatic reactions where the EC number system is largely built on criteria based on the reaction mechanism. This is true for hydrolysis reactions, falling into the domain of the EC class 3 (EC 3.b.c.d). The comparison is made by a Kohonen neural network based on an unsupervised learning algorithm. For these hydrolysis reactions, the similarity analysis on physicochemical effects produces results that are, by and large, similar to the EC number. However, this similarity analysis reveals finer details of the enzymatic reactions and thus can provide a better basis for the mechanistic comparison of enzymes.

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This article has been cited by 1 ACS Journal articles (1 most recent appear below).

Similarity Perception of Reactions Catalyzed by Oxidoreductases and Hydrolases Using Different Classification Methods
Xiaoying Hu, Aixia Yan, Tianwei Tan, Oliver Sacher and Johann Gasteiger
Journal of Chemical Information and Modeling2010 50 (6), 1089-1100
- Similarity Perception of Reactions Catalyzed by Oxidoreductases and Hydrolases Using Different Classification Methods
  Xiaoying Hu, Aixia Yan, Tianwei Tan, Oliver Sacher and Johann Gasteiger
  Journal of Chemical Information and Modeling2010 50 (6), 1089-1100
  In this work, the perception of similarity of reactions catalyzed by hydrolases and oxidoreductases on the basis of the overall breaking and making of bonds of reactions is investigated. Six physicochemical properties for the reacting bond in the ...
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