ArticleBioinformatics (Oxford, England)2012
An integrated open framework for thermodynamics of reactions that combines accuracy and coverage.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.
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61 citing papers in PubMed.
- Thermo-flux: generation and analysis of thermodynamic-stoichiometric metabolic network models.Molecular systems biology · 2026Article
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- Predicting the Rate Structure of an Evolved Metabolic Network.Metabolites · 2025Article
- Activating the d-Tagatose Production Capacity ofJournal of agricultural and food chemistry · 2025Article
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- Awakening the natural capability of psicose production in Escherichia coli.NPJ science of food · 2023Article
- Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients.BMC biology · 2023Article
- Alternative design strategies to help build the enzymatic retrosynthesis toolbox.RSC chemical biology · 2022Article
- Design, Analysis, and Implementation of a Novel Biochemical Pathway for Ethylene Glycol Production inACS synthetic biology · 2022Article
- eQuilibrator 3.0: a database solution for thermodynamic constant estimation.Nucleic acids research · 2022Article
- Thermodynamics of Potential CHO Metabolites in a Reducing Environment.Life (Basel, Switzerland) · 2021Article
- dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design.PLoS computational biology · 2021Article
- Analysis of metabolic network disruption in engineered microbial hosts due to enzyme promiscuity.Metabolic engineering communications · 2021Article
- Metabolic energy conservation for fermentative product formation.Microbial biotechnology · 2021Review
- Reaction lumping in metabolic networks for application with thermodynamic metabolic flux analysis.Scientific reports · 2021Article
- Quantum Mechanical Methods Predict Accurate Thermodynamics of Biochemical Reactions.ACS omega · 2021Article
- Seeding Biochemistry on Other Worlds: Enceladus as a Case Study.Astrobiology · 2021Article
- The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes.Nucleic acids research · 2021Article
1 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
motivationThe laws of thermodynamics describe a direct, quantitative relationship between metabolite concentrations and reaction directionality. Despite great efforts, thermodynamic data suffer from limited coverage, scattered accessibility and non-standard annotations. We present a framework for unifying thermodynamic data from multiple sources and demonstrate two new techniques for extrapolating the Gibbs energies of unmeasured reactions and conditions.
resultsBoth methods account for changes in cellular conditions (pH, ionic strength, etc.) by using linear regression over the ΔG(○) of pseudoisomers and reactions. The Pseudoisomeric Reactant Contribution method systematically infers compound formation energies using measured K' and pK(a) data. The Pseudoisomeric Group Contribution method extends the group contribution method and achieves a high coverage of unmeasured reactions. We define a continuous index that predicts the reversibility of a reaction under a given physiological concentration range. In the characteristic physiological range 3μM-3mM, we find that roughly half of the reactions in Escherichia coli's metabolism are reversible. These new tools can increase the accuracy of thermodynamic-based models, especially in non-standard pH and ionic strengths. The reversibility index can help modelers decide which reactions are reversible in physiological conditions. AVAILABILITY: Freely available on the web at: http://equilibrator.weizmann.ac.il. Website implemented in Python, MySQL, Apache and Django, with all major browsers supported. The framework is open-source (code.google.com/p/milo-lab), implemented in pure Python and tested mainly on Linux. CONTACT: ron.milo@weizmann.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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