Literature DB >> 23816707

Chemical and genomic evolution of enzyme-catalyzed reaction networks.

Minoru Kanehisa1.   

Abstract

There is a tendency that a unit of enzyme genes in an operon-like structure in the prokaryotic genome encodes enzymes that catalyze a series of consecutive reactions in a metabolic pathway. Our recent analysis shows that this and other genomic units correspond to chemical units reflecting chemical logic of organic reactions. From all known metabolic pathways in the KEGG database we identified chemical units, called reaction modules, as the conserved sequences of chemical structure transformation patterns of small molecules. The extracted patterns suggest co-evolution of genomic units and chemical units. While the core of the metabolic network may have evolved with mechanisms involving individual enzymes and reactions, its extension may have been driven by modular units of enzymes and reactions.
Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Keywords:  Enzyme cluster; Evolution of metabolism; KEGG database; Metabolic pathway; Reaction module

Mesh:

Substances:

Year:  2013        PMID: 23816707     DOI: 10.1016/j.febslet.2013.06.026

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  10 in total

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Journal:  J Physiol       Date:  2017-07-27       Impact factor: 5.182

3.  Elements of the cellular metabolic structure.

Authors:  Ildefonso M De la Fuente
Journal:  Front Mol Biosci       Date:  2015-04-28

4.  The proportion of genes in a functional category is linked to mass-specific metabolic rate and lifespan.

Authors:  Kazuhiro Takemoto; Yuko Kawakami
Journal:  Sci Rep       Date:  2015-05-06       Impact factor: 4.379

5.  BiomeNet: a Bayesian model for inference of metabolic divergence among microbial communities.

Authors:  Mahdi Shafiei; Katherine A Dunn; Hugh Chipman; Hong Gu; Joseph P Bielawski
Journal:  PLoS Comput Biol       Date:  2014-11-20       Impact factor: 4.475

6.  KEGG as a reference resource for gene and protein annotation.

Authors:  Minoru Kanehisa; Yoko Sato; Masayuki Kawashima; Miho Furumichi; Mao Tanabe
Journal:  Nucleic Acids Res       Date:  2015-10-17       Impact factor: 16.971

7.  KEGG: new perspectives on genomes, pathways, diseases and drugs.

Authors:  Minoru Kanehisa; Miho Furumichi; Mao Tanabe; Yoko Sato; Kanae Morishima
Journal:  Nucleic Acids Res       Date:  2016-11-28       Impact factor: 16.971

8.  Importance of metabolic rate to the relationship between the number of genes in a functional category and body size in Peto's paradox for cancer.

Authors:  Kazuhiro Takemoto; Masato Ii; Satoshi S Nishizuka
Journal:  R Soc Open Sci       Date:  2016-09-07       Impact factor: 2.963

9.  Data, information, knowledge and principle: back to metabolism in KEGG.

Authors:  Minoru Kanehisa; Susumu Goto; Yoko Sato; Masayuki Kawashima; Miho Furumichi; Mao Tanabe
Journal:  Nucleic Acids Res       Date:  2013-11-07       Impact factor: 16.971

Review 10.  An appeal to magic? The discovery of a non-enzymatic metabolism and its role in the origins of life.

Authors:  Markus Ralser
Journal:  Biochem J       Date:  2018-08-30       Impact factor: 3.857

  10 in total

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