Evidence map›Paper›PMID 30086174›Full record

ArticlePLoS computational biology2018

Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials.

James T Yurkovich, Miguel A Alcantar, Zachary B Haiman, Bernhard O Palsson

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In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

4 authors.

James T YurkovichDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0002-9403-509X
Miguel A AlcantarDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
Zachary B HaimanDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
Bernhard O PalssonDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0003-2357-6785

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Allosteric regulation has traditionally been described by mathematically-complex allosteric rate laws in the form of ratios of polynomials derived from the application of simplifying kinetic assumptions. Alternatively, an approach that explicitly describes all known ligand-binding events requires no simplifying assumptions while allowing for the computation of enzymatic states. Here, we employ such a modeling approach to examine the "catalytic potential" of an enzyme-an enzyme's capacity to catalyze a biochemical reaction. The catalytic potential is the fundamental result of multiple ligand-binding events that represents a "tug of war" among the various regulators and substrates within the network. This formalism allows for the assessment of interacting allosteric enzymes and development of a network-level understanding of regulation. We first define the catalytic potential and use it to characterize the response of three key kinases (hexokinase, phosphofructokinase, and pyruvate kinase) in human red blood cell glycolysis to perturbations in ATP utilization. Next, we examine the sensitivity of the catalytic potential by using existing personalized models, finding that the catalytic potential allows for the identification of subtle but important differences in how individuals respond to such perturbations. Finally, we explore how the catalytic potential can help to elucidate how enzymes work in tandem to maintain a homeostatic state. Taken together, this work provides an interpretation and visualization of the dynamic interactions and network-level effects of interacting allosteric enzymes.

Indexed as

Allosteric RegulationBiophysical PhenomenaCatalysisComputer SimulationGlycolysisHexokinaseHumansKineticsLigandsPhosphofructokinase-1Protein BindingPyruvate KinaseThermodynamicsHexokinaseLigandsPhosphofructokinase-1Pyruvate Kinase

Identifiers

PMID30086174
PMCPMC6097697

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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.