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A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing
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Evolutionary rate in the protein interaction network.

Hunter B Fraser1, Aaron E Hirsh, Lars M Steinmetz

  • 1Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA. hunter@ocf.berkeley.edu

Science (New York, N.Y.)
|April 27, 2002
PubMed
Summary
This summary is machine-generated.

Proteins with more interaction partners in yeast evolve slower due to functional constraints. This molecular evolution study reveals that interacting proteins often evolve at similar rates, driven by coevolutionary changes.

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Area of Science:

  • Molecular evolution
  • Systems biology
  • Yeast genetics

Background:

  • High-throughput screens are elucidating the protein interaction network in Saccharomyces cerevisiae.
  • Understanding how network organization influences protein evolution is crucial in molecular evolution.

Purpose of the Study:

  • To investigate the relationship between protein connectivity within the yeast interactome and evolutionary rates.
  • To determine if protein importance or functional involvement explains the correlation between connectivity and evolution.

Main Methods:

  • Analysis of protein-protein interaction data from Saccharomyces cerevisiae.
  • Correlation analysis between protein connectivity (number of interactors) and evolutionary rates.
  • Examination of evolutionary rates at interaction sites and across interacting protein pairs.

Main Results:

  • A negative correlation exists between protein connectivity and evolutionary rate in yeast.
  • Proteins with more interactors evolve slower, not due to importance, but due to greater functional involvement of their structure.
  • Interacting proteins exhibit similar evolutionary rates, supporting the role of coevolution.

Conclusions:

  • Protein network architecture significantly impacts molecular evolution.
  • Functional constraints at interaction interfaces drive slower evolution in highly connected proteins.
  • Coevolutionary dynamics between interacting proteins lead to correlated rates of evolution.