Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism

Background: Understanding of secondary metabolic pathway in plant is essential for finding druggable candidate enzymes. However, there are many enzymes whose functions are not yet discovered in organism-specific metabolic pathways. Towards identifying the functions of those enzymes, assignment of EC numbers to the enzymatic reactions they catalyze plays a key role, since EC numbers represent the categorization of enzymes on one hand, and the categorization of enzymatic reactions on the other hand. Results: We propose reaction graph kernels for automatically assigning EC numbers to unknown enzymatic reactions in a metabolic network. Reaction graph kernels compute similarity between two chemical reactions considering the similarity of chemical compounds in reaction and their relationships. In computational experiments based on the KEGG/REACTION database, our method successfully predicted the first three digits of the EC number with 83% accuracy. We also exhaustively predicted missing EC...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, Koji Tsuda
• Keywords: BMCBI 2010, Ec Numbers, Enzymatic Reactions, Reaction Graph