ArticleBMC bioinformatics2010
Predicting the network of substrate-enzyme-product triads by combining compound similarity and functional domain composition.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
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- HIV infection alters the human epigenetic landscape.Gene therapy · 2019Article
- SumSec: Accurate Prediction of Sumoylation Sites Using Predicted Secondary Structure.Molecules (Basel, Switzerland) · 2018Article
- Tissue Expression Difference between mRNAs and lncRNAs.International journal of molecular sciences · 2018Article
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- Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways.PloS one · 2017Article
- Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds.Molecular genetics and genomics : MGG · 2016Article
- Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.BioMed research international · 2016Article
- Classifying ten types of major cancers based on reverse phase protein array profiles.PloS one · 2015Article
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- Gene ontology and KEGG enrichment analyses of genes related to age-related macular degeneration.BioMed research international · 2014Article
- Prediction of effective drug combinations by chemical interaction, protein interaction and target enrichment of KEGG pathways.BioMed research international · 2013Article
- Prediction of substrate-enzyme-product interaction based on molecular descriptors and physicochemical properties.BioMed research international · 2013Article
- Study of drug function based on similarity of pathway fingerprint.Protein & cell · 2012Article
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- Identification of amino acid propensities that are strong determinants of linear B-cell epitope using neural networks.PloS one · 2012Article
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Authors and funding
5 authors.
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Abstract
backgroundMetabolic pathway is a highly regulated network consisting of many metabolic reactions involving substrates, enzymes, and products, where substrates can be transformed into products with particular catalytic enzymes. Since experimental determination of the network of substrate-enzyme-product triad (whether the substrate can be transformed into the product with a given enzyme) is both time-consuming and expensive, it would be very useful to develop a computational approach for predicting the network of substrate-enzyme-product triads.
resultsA mathematical model for predicting the network of substrate-enzyme-product triads was developed. Meanwhile, a benchmark dataset was constructed that contains 744,192 substrate-enzyme-product triads, of which 14,592 are networking triads, and 729,600 are non-networking triads; i.e., the number of the negative triads was about 50 times the number of the positive triads. The molecular graph was introduced to calculate the similarity between the substrate compounds and between the product compounds, while the functional domain composition was introduced to calculate the similarity between enzyme molecules. The nearest neighbour algorithm was utilized as a prediction engine, in which a novel metric was introduced to measure the "nearness" between triads. To train and test the prediction engine, one tenth of the positive triads and one tenth of the negative triads were randomly picked from the benchmark dataset as the testing samples, while the remaining were used to train the prediction model. It was observed that the overall success rate in predicting the network for the testing samples was 98.71%, with 95.41% success rate for the 1,460 testing networking triads and 98.77% for the 72,960 testing non-networking triads.
conclusionsIt is quite promising and encouraged to use the molecular graph to calculate the similarity between compounds and use the functional domain composition to calculate the similarity between enzymes for studying the substrate-enzyme-product network system. The software is available upon request.
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