ArticleBiophysical journal2010
IGERS: inferring Gibbs energy changes of biochemical reactions from reaction similarities.
Article in Biophysical journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design.PLoS computational biology · 2021Article
- Systematic selection of chemical fingerprint features improves the Gibbs energy prediction of biochemical reactions.Bioinformatics (Oxford, England) · 2019Article
- Article
- Consistent estimation of Gibbs energy using component contributions.PLoS computational biology · 2013Article
- An integrated open framework for thermodynamics of reactions that combines accuracy and coverage.Bioinformatics (Oxford, England) · 2012Article
- Quantitative assignment of reaction directionality in a multicompartmental human metabolic reconstruction.Biophysical journal · 2012Article
- A toolbox for developing bioinformatics software.Briefings in bioinformatics · 2012Article
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6 authors.
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Abstract
Mathematical analysis and modeling of biochemical reaction networks requires knowledge of the permitted directionality of reactions and membrane transport processes. This information can be gathered from the standard Gibbs energy changes (DeltaG(0)) of reactions and the concentration ranges of their reactants. Currently, experimental DeltaG(0) values are not available for the vast majority of cellular biochemical processes. We propose what we believe to be a novel computational method to infer the unknown DeltaG(0) value of a reaction from the known DeltaG(0) value of the chemically most similar reaction. The chemical similarity of two arbitrary reactions is measured by the relative number (T) of co-occurring changes in the chemical attributes of their reactants. Testing our method across a validated reference set of 173 biochemical reactions with experimentally determined DeltaG(0) values, we found that a minimum reaction similarity of T = 0.6 is required to infer DeltaG(0) values with an error of <10 kJ/mol. Applying this criterion, our method allows us to assign DeltaG(0) values to 458 additional reactions of the BioPath database. We believe our approach permits us to minimize the number of DeltaG(0) measurements required for a full coverage of a given reaction network with reliable DeltaG(0) values.
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