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The Plasmodium protein network diverges from those of other eukaryotes

Author

Listed:
  • Silpa Suthram

    (Bioinformatics Program
    University of California)

  • Taylor Sittler

    (University of California)

  • Trey Ideker

    (Bioinformatics Program
    University of California)

Abstract

What makes a parasite tick A powerful approach for understanding protein function is to identify which proteins bind to each other, as protein complexes are at the heart of most biological processes. Protein–protein interactions have now been mapped for one quarter of the malaria parasite's proteins. This large data set sheds new light on how parasites infect red blood cells and will be a vital tool for the development of new antimalarial drugs and vaccines. The primary data are freely available on the PlasmoDB database. Suthram et al. have used this new resource and find that the Plasmodium network has significantly less cross-species similarity than other eukaryotes. Its novel life style is reflected in a novel protein network, which therefore has a good chance of providing drug targets unique to the malaria parasite.

Suggested Citation

  • Silpa Suthram & Taylor Sittler & Trey Ideker, 2005. "The Plasmodium protein network diverges from those of other eukaryotes," Nature, Nature, vol. 438(7064), pages 108-112, November.
    • Handle: RePEc:nat:nature:v:438:y:2005:i:7064:d:10.1038_nature04135
    DOI: 10.1038/nature04135
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    Cited by:

    1. B J Morrison McKay & Clare Sansom, 2009. "Webb Miller and Trey Ideker To Receive Top International Bioinformatics Awards for 2009 from the International Society for Computational Biology," PLOS Computational Biology, Public Library of Science, vol. 5(4), pages 1-4, April.
    2. Oleksii Kuchaiev & Marija Rašajski & Desmond J Higham & Nataša Pržulj, 2009. "Geometric De-noising of Protein-Protein Interaction Networks," PLOS Computational Biology, Public Library of Science, vol. 5(8), pages 1-10, August.
    3. Juan A G Ranea & Ian Morilla & Jon G Lees & Adam J Reid & Corin Yeats & Andrew B Clegg & Francisca Sanchez-Jimenez & Christine Orengo, 2010. "Finding the “Dark Matter” in Human and Yeast Protein Network Prediction and Modelling," PLOS Computational Biology, Public Library of Science, vol. 6(9), pages 1-14, September.

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