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The Impact of Oxygen on Metabolic Evolution: A Chemoinformatic Investigation

Overview of attention for article published in PLoS Computational Biology, March 2012
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Title
The Impact of Oxygen on Metabolic Evolution: A Chemoinformatic Investigation
Published in
PLoS Computational Biology, March 2012
DOI 10.1371/journal.pcbi.1002426
Pubmed ID
Authors

Ying-Ying Jiang, De-Xin Kong, Tao Qin, Xiao Li, Gustavo Caetano-Anollés, Hong-Yu Zhang

Abstract

The appearance of planetary oxygen likely transformed the chemical and biochemical makeup of life and probably triggered episodes of organismal diversification. Here we use chemoinformatic methods to explore the impact of the rise of oxygen on metabolic evolution. We undertake a comprehensive comparative analysis of structures, chemical properties and chemical reactions of anaerobic and aerobic metabolites. The results indicate that aerobic metabolism has expanded the structural and chemical space of metabolites considerably, including the appearance of 130 novel molecular scaffolds. The molecular functions of these metabolites are mainly associated with derived aspects of cellular life, such as signal transfer, defense against biotic factors, and protection of organisms from oxidation. Moreover, aerobic metabolites are more hydrophobic and rigid than anaerobic compounds, suggesting they are better fit to modulate membrane functions and to serve as transmembrane signaling factors. Since higher organisms depend largely on sophisticated membrane-enabled functions and intercellular signaling systems, the metabolic developments brought about by oxygen benefit the diversity of cellular makeup and the complexity of cellular organization as well. These findings enhance our understanding of the molecular link between oxygen and evolution. They also show the significance of chemoinformatics in addressing basic biological questions.

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Geographical breakdown

Country Count As %
Mexico 2 3%
United States 2 3%
Brazil 1 1%
Finland 1 1%
China 1 1%
Portugal 1 1%
Japan 1 1%
Spain 1 1%
Unknown 69 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 30%
Student > Ph. D. Student 23 29%
Professor > Associate Professor 5 6%
Student > Master 5 6%
Student > Bachelor 4 5%
Other 9 11%
Unknown 9 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 39%
Biochemistry, Genetics and Molecular Biology 17 22%
Computer Science 4 5%
Environmental Science 3 4%
Chemistry 3 4%
Other 9 11%
Unknown 12 15%