Identification of Enzyme Genes Using Chemical Structure Alignments of Substrate–Product Pairs

Abstract

Although there are several databases that contain data on many metabolites and reactions in biochemical pathways, there is still a big gap in the numbers between experimentally identified enzymes and metabolites. It is supposed that many catalytic enzyme genes are still unknown. Although there are previous studies that estimate the number of candidate enzyme genes, these studies required some additional information aside from the structures of metabolites such as gene expression and order in the genome. In this study, we developed a novel method to identify a candidate enzyme gene of a reaction using the chemical structures of the substrate-product pair (reactant pair). The proposed method is based on a search for similar reactant pairs in a reference database and offers ortholog groups that possibly mediate the given reaction. We applied the proposed method to two experimentally validated reactions. As a result, we confirmed that the histidine transaminase was correctly identified. Although our method could not directly identify the asparagine oxo-acid transaminase, we successfully found the paralog gene most similar to the correct enzyme gene. We also applied our method to infer candidate enzyme genes in the mesaconate pathway. The advantage of our method lies in the prediction of possible genes for orphan enzyme reactions where any associated gene sequences are not determined yet. We believe that this approach will facilitate experimental identification of genes for orphan enzymes.

Data integration aids understanding of butterfly–host plant networks

“…6a). We used the E-zyme webserver (see Methods) to search for known enzymatic reactions having the same chemical transformation patterns as the query reaction3233. Only one of the four reactions (Fig.…”

“…The first step is the problem of enzymatic reaction-likeness, i.e., whether a pair of metabolic compounds can be the substrate and product of a single enzymatic reaction30. The second step is the prediction of the actual enzymes responsible for the putative enzymatic reactions33. To accomplish the first step, we used known chemical transformation patterns encoded as SMIRKS strings49 to search for pairs of metabolic compounds potentially possessing the same chemical transformation pattern.…”

“…To accomplish the first step, we used known chemical transformation patterns encoded as SMIRKS strings49 to search for pairs of metabolic compounds potentially possessing the same chemical transformation pattern. For the second step, we used the E-zyme32 and E-zyme233 webservers. E-zyme predicts putative enzyme classifications (referred to as Enzyme Commission numbers) with generated values reflecting the similarity between the given transformation patterns and known patterns.…”

KCF-Convoy: efficient Python package to convert KEGG Chemical Function and Substructure fingerprints

“…The eight metabolites were subjected to the E-zyme2 program (Moriya et al, 2016), which predicts candidate enzyme orthologs that can catalyze a reaction given as a query substrate-product pair. The prediction results showed that a Brassica oleracea (wild cabbage) cytochrome (CYP) enzyme (EC 1.14.14.1) could catalyze the interconversion of two of the metabolites (C00027106 and C00036583).…”

Assigning enzyme sequences to orphan and novel reactions using knowledge of substrate reactive sites

“…In addition, these methods are not suitable for the annotation of de novo reactions since current pathway prediction tools only provide information about enzyme catalytic biotransformations and not about their sequences. These shortcomings motivated the development of alternative computational methods based on the structural similarity of reactants and products for identifying candidate protein sequences for orphan enzymatic reactions (30,33,(36)(37)(38)(39)(40). The idea behind these approaches was to assess the similarity of two enzymatic reactions via the similarity of their reaction fingerprints, i.e., the mathematical descriptors of the structural and topological properties of the participating metabolites (41), which could eliminate the problems associated with non-matching or unassigned protein sequences.…”