Evidence map›Paper›PMID 24586134›Full record

ArticlePLoS computational biology2014

Pathway thermodynamics highlights kinetic obstacles in central metabolism.

Elad Noor, Arren Bar-Even, Avi Flamholz, Ed Reznik, Wolfram Liebermeister, Ron Milo

Abstract read
In one paragraph

Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 160 papers.

0numbers the graph read from it
0cells of the map it votes in
160citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

160 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. The return of metabolism: biochemistry and physiology of glycolysis.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  16. Article
  17. Article
  18. Article
  19. Multicriteria evaluation of ethylene glycol assimilation pathways.Journal of industrial microbiology & biotechnology · 2026
    Article
  20. Article

100 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Elad NoorDepartment of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel.
Arren Bar-EvenDepartment of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel.
Avi FlamholzDepartment of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel ; Department of Molecular and Cellular Biology, University of California, Berkely, Berkely, California, United States of America.
Ed ReznikComputational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Wolfram LiebermeisterInstitut für Biochemie, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Ron MiloDepartment of Plant Sciences, The Weizmann Institute of Science, Rehovot, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (ΔrG'). Accordingly, if an enzyme catalyzes a reaction with a ΔrG' of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As ΔrG' approaches equilibrium (ΔrG' = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating the thermodynamic and kinetic quality of different pathway chemistries that produce the same molecules.

Indexed as

Metabolic Networks and PathwaysModels, BiologicalCitric Acid CycleComputational BiologyEnzymesEscherichia coliFermentationKineticsMalate DehydrogenaseOsmolar ConcentrationPhosphorylationThermodynamicsEnzymesMalate Dehydrogenase

Identifiers

PMID24586134
PMCPMC3930492

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.