Computational Assignment of the EC Numbers for Genomic-Scale Analysis of Enzymatic Reactions

Abstract

The EC (Enzyme Commission) numbers represent a hierarchical classification of enzymatic reactions, but they are also commonly utilized as identifiers of enzymes or enzyme genes in the analysis of complete genomes. This duality of the EC numbers makes it possible to link the genomic repertoire of enzyme genes to the chemical repertoire of metabolic pathways, the process called metabolic reconstruction. Unfortunately, there are numerous reactions known to be present in various pathways, but they will never get EC numbers because the EC number assignment requires published articles on full characterization of enzymes. Here we report a computerized method to automatically assign the EC numbers up to the sub-subclasses, i.e., without the fourth serial number for substrate specificity, given pairs of substrates and products. The method is based on a new classification scheme of enzymatic reactions, named the RC (reaction classification) number. Each reaction in the current dataset of the EC numbers is first decomposed into reactant pairs. Each pair is then structurally aligned to identify the reaction center, the matched region, and the difference region. The RC number represents the conversion patterns of atom types in these three regions. We examined the correspondence between computationally assigned RC numbers and manually assigned EC numbers by the jackknife cross-validation test and found that the EC sub-subclasses could be assigned with the accuracy of about 90%. Furthermore, we examined the correlation with genomic information as represented by the KEGG ortholog clusters (OC) and confirmed that the RC numbers are correlated not only with elementary reaction mechanisms but also with protein families.

Systems chemical biology

“…Bioinformatics techniques use Enzyme Commission (EC) numbers to predict the metabolites a given sequence can catalyze [26][27][28] , and structure-and sequence-based methods to locate homologous ligand binding sites 29 . Cheminformatics techniques such as virtual screening seek to identify novel compounds for a given target 19,30 , can classify metabolic 31 and organic 32 reactions, and predict the EC number given a metabolic reaction 33 . Beyond common goals, cheminformatics and bioinformatics also share common computational techniques: clustering and machine learning based on regression, support vector machine (SVM), neural network, Bayesian networks, hidden Markov models, and decision trees, for example.…”

Overview of KEGG applications to omics-related research

“…Specific pathways can be specified to search for the reaction paths, so that the organisms containing specific compounds can be retrieved, for example. Another tool is the reaction prediction tool called e-zyme, 6) which takes at least one pair of compounds and returns all possible reactions involving them. These results are all linked with PATHWAY such that a listing of all pathways involving given compound structures can be retrieved.…”

Atom Mapping with Constraint Programming

“…Atom maps convey the complete information necessary to disentangle the mechanism, i.e., the bond re-arrangement, of a chemical reaction because they unambiguously identify the bonds that differ between educt and product molecules. The changing parts of the molecules are described by a so called imaginary transition state (ITS) [1,2] that allows, for instance, a classification of chemical reactions [3][4][5]. Atom maps are a necessary requisite for computational studies of an organism's metabolism.…”