Reactant pairs and reaction organization patterns produced by a new rule-based approach

Abstract

ObjectivesImprovements in bioinformatics applications for the enzyme identification of biochemical reactions, enzyme classifications, mining for specific inhibitors and pathfinding require the accurate computational detection of reaction similarity. We provide a set of substrate-product pairs, clustered by reactions that share similar chemical transformation patterns, for which accuracy was calculated, comparing this set with manually curated data sets.Data descriptionThe data were analyzed by a new method that naturally split each reaction into compound pairs and loner compounds, which we called architectures (Vazquez-Hernandez et al. in BMC Syst Biol 12:63, 2018). The data include a set of 7491 curated reactions from the KEGG-Ligand data set. The data are presented in two formats, a string format and a tree structure, both of which reflect the splitting process and the final architectures of each reaction. We are also reporting sets of reactions that show similar splitting patterns naturally grouped into clusters of tree structures. The compound pairs in each cluster were compared with the reactant pairs proposed by the KEGG-RCLASS data set, and a match precision value is also provided. These data were collected with the aim of providing research with a confident set of reactant pairs that is useful for selecting between alternative substrate-product pairs predicted by pathfinders.

Ridinilazole, a narrow spectrum antibiotic for treatment of Clostridioides difficile infection, enhances preservation of microbiota-dependent bile acids

“…After nonenzymatic functions were eliminated, the K numbers were further filtered to remove functions that have very low counts (median count <10 across all ridinilazole or vancomycin samples) and are thus unlikely to play a quantitative role in microbiota metabolism. The remaining enzymatic functions were then linked to KEGG reaction identifiers ( r numbers) and their primary substrate-product pairs as defined by KEGG’s RCLASS data ( 46 ). The substrate-product pairs were used to draw the network graphs for annotation, where the nodes and edges correspond to metabolites and reactions, respectively.…”