Literature DB >> 28202588

Control and regulation of pathways via negative feedback.

Herbert M Sauro1.   

Abstract

The biochemical networks found in living organisms include a huge variety of control mechanisms at multiple levels of organization. While the mechanistic and molecular details of many of these control mechanisms are understood, their exact role in driving cellular behaviour is not. For example, yeast glycolysis has been studied for almost 80 years but it is only recently that we have come to understand the systemic role of the multitude of feedback and feed-forward controls that exist in this pathway. In this article, control theory is discussed as an approach to dissect the control logic of complex pathways. One of the key issues is distinguishing between the terms control and regulation and how these concepts are applied to regulated enzymes such as phosphofructokinase. In doing so, one of the paradoxes in metabolic regulation can be resolved where enzymes such as phosphofructokinase have little control but, nevertheless, possess significant regulatory influence.
© 2017 The Author(s).

Entities:  

Keywords:  control; metabolism; negative feedback

Mesh:

Substances:

Year:  2017        PMID: 28202588      PMCID: PMC5332569          DOI: 10.1098/rsif.2016.0848

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  56 in total

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Journal:  Science       Date:  1956-05-11       Impact factor: 47.728

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Journal:  Eur J Biochem       Date:  1989-12-08

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Journal:  Eur J Biochem       Date:  1986-07-01

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Journal:  Eur J Biochem       Date:  1974-02-15

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Authors:  D Kahn; H V Westerhoff
Journal:  Acta Biotheor       Date:  1993-06       Impact factor: 1.774

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Journal:  Eur J Biochem       Date:  1985-05-02

7.  Isolation and characterization of the two structural genes coding for phosphofructokinase in yeast.

Authors:  J Heinisch
Journal:  Mol Gen Genet       Date:  1986-01

8.  Effects of overexpression of phosphofructokinase on glycolysis in the yeast Saccharomyces cerevisiae.

Authors:  S E Davies; K M Brindle
Journal:  Biochemistry       Date:  1992-05-19       Impact factor: 3.162

9.  Overproduction of glycolytic enzymes in yeast.

Authors:  I Schaaff; J Heinisch; F K Zimmermann
Journal:  Yeast       Date:  1989 Jul-Aug       Impact factor: 3.239

10.  Testing biochemistry revisited: how in vivo metabolism can be understood from in vitro enzyme kinetics.

Authors:  Karen van Eunen; José A L Kiewiet; Hans V Westerhoff; Barbara M Bakker
Journal:  PLoS Comput Biol       Date:  2012-04-26       Impact factor: 4.475

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  13 in total

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5.  Metabolic buffer analysis reveals the simultaneous, independent control of ATP and adenylate energy ratios.

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Journal:  J R Soc Interface       Date:  2021-04-28       Impact factor: 4.118

Review 6.  Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

Authors:  Miroslava Cuperlovic-Culf
Journal:  Metabolites       Date:  2018-01-11

7.  The Dynamical Emergence of Biology From Physics: Branching Causation via Biomolecules.

Authors:  George F R Ellis; Jonathan Kopel
Journal:  Front Physiol       Date:  2019-01-25       Impact factor: 4.566

8.  Understanding biochemical design principles with ensembles of canonical non-linear models.

Authors:  Lukas Bromig; Andreas Kremling; Alberto Marin-Sanguino
Journal:  PLoS One       Date:  2020-04-30       Impact factor: 3.240

9.  Delving deeper: Relating the behaviour of a metabolic system to the properties of its components using symbolic metabolic control analysis.

Authors:  Carl D Christensen; Jan-Hendrik S Hofmeyr; Johann M Rohwer
Journal:  PLoS One       Date:  2018-11-28       Impact factor: 3.240

10.  Towards feedback-controlled nanomedicines for smart, adaptive delivery.

Authors:  Stephen J Jones; Annette F Taylor; Paul A Beales
Journal:  Exp Biol Med (Maywood)       Date:  2018-09-11
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