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Related Experiment Videos

Coevolving protein residues: maximum likelihood identification and relationship to structure.

D D Pollock1, W R Taylor, N Goldman

  • 1Division of Mathematical Biology, National Institute for Medical Research, The Ridgeway, Mill Hill, London, NW7 1AA, UK. dpollock@socrates.berkeley.edu

Journal of Molecular Biology
|March 13, 1999
PubMed
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Identifying protein site coevolution aids in understanding evolution and predicting protein structure. A new maximum likelihood method improves detection by accounting for phylogenetic relationships and evolutionary rates, revealing insights into protein folding and structure.

Area of Science:

  • Evolutionary biology
  • Structural biology
  • Bioinformatics

Background:

  • Correlated evolution (coevolution) of protein sites suggests proximity in 3D structure.
  • Identifying coevolving sites aids evolutionary understanding, substitution effect prediction, and protein structure prediction.
  • Previous methods for detecting coevolution have had limited success.

Purpose of the Study:

  • Develop and apply an improved maximum likelihood method for detecting protein site coevolution.
  • Address limitations of previous methods by incorporating phylogenetic correlations and evolutionary rate variations.
  • Reduce complexity by simplifying site data to a two-state system.

Main Methods:

  • Developed a maximum likelihood method to detect coevolution.

Related Experiment Videos

  • Reduced site data to a two-state system to simplify coevolutionary relationships.
  • Tested the method on myoglobin sequences, grouping residues by size and charge characteristics.
  • Categorized coevolution into positive and negative based on equilibrium state frequencies.

    • Main Results:

    • The new method effectively identifies simple correlations and insufficient data cases.
    • Detected a significant excess of negative coevolution (charge-based) at alpha-helix proximity sites.
    • Coevolving sites identified by the method showed a tendency to be close in 3D structure.
    • Surface sites coevolved both when close and distant, suggesting roles for folding and quaternary structure.

    Conclusions:

    • The improved method enhances the detection of protein site coevolution.
    • Coevolutionary patterns, particularly charge-based negative coevolution, are linked to protein structure and function.
    • Findings contribute to understanding evolutionary processes, predicting substitution effects, and protein structure prediction.