Similarity perception of reactions catalyzed by oxidoreductases and hydrolases using different classification methods

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 substrate of each enzymatic reaction were calculated to describe the characteristics of each reaction. The 311 reactions catalyzed by hydrolases (EC 3.b.c.d) and the 651 reactions catalyzed by oxidoreductases (EC 1.b.c.d) were classified by Kohonen's self-organizing neural network (KohNN), by a support vector machine (SVM), and by hierarchical clustering analysis (HCA). For the 311 reactions catalyzed by hydrolases, the classification accuracy of 95.8% by a KohNN and 97.7% by an SVM was achieved. For the 651 reactions catalyzed by oxidoreductases, the classification accuracy was 93.4% and 96.3% by a KohNN and a SVM, respectively. The similarities of reactions reflected by the physicochemical effects of reacting bonds were compared with the traditional Enzyme Commission (EC) classification system. The results of a KohNN and a SVM are similar to those of the EC classification system method. However, the perception of similarity of reactions by a KohNN and a SVM shows finer details of the enzymatic reactions and thus could provide a good basis for the comparison of enzymes.