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Protein interaction networks revealed by proteome coevolution.

Qian Cong1,2, Ivan Anishchenko1,2, Sergey Ovchinnikov3

  • 1Department of Biochemistry, University of Washington, Seattle, WA 98105, USA.

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|July 13, 2019
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This summary is machine-generated.

We analyzed protein coevolution across entire proteomes, finding it useful for predicting protein-protein interactions (PPIs) more accurately than other methods. This work identifies many new PPIs in E. coli and M. tuberculosis.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Residue-residue coevolution is known at protein interfaces.
  • Systematic study of coevolution across whole proteomes is lacking.

Purpose of the Study:

  • Investigate proteome-wide coevolution between protein families.
  • Develop accurate protein-protein interaction (PPI) prediction methods.
  • Identify novel PPIs in Escherichia coli and Mycobacterium tuberculosis.

Main Methods:

  • Analyzed 5.4 million protein pairs in E. coli and 3.9 million in M. tuberculosis.
  • Examined coevolution patterns in relation to complex size and function.
  • Integrated coevolution data with structure modeling for PPI prediction.

Main Results:

  • Strong coevolution observed in binary metabolic complexes; weaker in larger genetic complexes.
  • Predicted PPIs with higher accuracy than proteome-wide two-hybrid and mass spectrometry.
  • Identified hundreds of previously uncharacterized PPIs in both organisms.

Conclusions:

  • Proteome-wide coevolution analysis is a powerful tool for PPI prediction.
  • This approach significantly expands the known interactomes of E. coli and M. tuberculosis.
  • New PPIs contribute to known and reveal novel protein complexes and networks.