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Sequence space and the ongoing expansion of the protein universe

Author

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  • Inna S. Povolotskaya

    (Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Calle Dr Aiguader 88, Barcelona Biomedical Research Park Building, 08003 Barcelona, Spain)

  • Fyodor A. Kondrashov

    (Bioinformatics and Genomics Programme, Centre for Genomic Regulation, Calle Dr Aiguader 88, Barcelona Biomedical Research Park Building, 08003 Barcelona, Spain)

Abstract

Proteins in the slow lane Protein evolution occurs only slowly, since most amino-acid substitutions are likely to be deleterious and selection will favour conservation of function. Inna Povolotskaya and Fyodor Kondrashov set out to find out just how slowly by asking the question, are ancient extant proteins — those that were present in the last universal common ancestor (LUCA) — continuing to diverge from the ancestral sequence? Their calculations, based on the approach used by Edwin Hubble in his study of the recession of galaxies in the physical Universe, suggests that extant protein sequences are still expanding from each other, and, therefore, from their common ancestor. Divergence is very slow: the 3.5 billion years or so since LUCA's time has not been long enough for the limit of sequence divergence to be reached. This tardiness is a consequence of the sparseness of functional protein sequences in sequence space and the ruggedness of the protein fitness landscape: 98% of sites cannot accept an amino-acid substitution at a given moment, yet most sites may eventually be permitted to evolve when other, compensatory, changes occur.

Suggested Citation

  • Inna S. Povolotskaya & Fyodor A. Kondrashov, 2010. "Sequence space and the ongoing expansion of the protein universe," Nature, Nature, vol. 465(7300), pages 922-926, June.
  • Handle: RePEc:nat:nature:v:465:y:2010:i:7300:d:10.1038_nature09105
    DOI: 10.1038/nature09105
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    Cited by:

    1. Krishnendu Chatterjee & Andreas Pavlogiannis & Ben Adlam & Martin A Nowak, 2014. "The Time Scale of Evolutionary Innovation," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-7, September.
    2. Jia Zheng & Ning Guo & Yuxiang Huang & Xiang Guo & Andreas Wagner, 2024. "High temperature delays and low temperature accelerates evolution of a new protein phenotype," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

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