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Related Experiment Video

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A Practical Guide to Phylogenetics for Nonexperts
12:00

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Published on: February 6, 2014

A perturbation-based method for calculating explicit likelihood of evolutionary co-variance in multiple sequence

John P Dekker1, Anthony Fodor, Richard W Aldrich

  • 1Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.

Bioinformatics (Oxford, England)
|February 14, 2004
PubMed
Summary

This study introduces a new algorithm to detect co-varying amino acids in protein families. The method improves the identification of physically interacting residues in protein structures.

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Area of Science:

  • Biochemistry
  • Structural Biology
  • Bioinformatics

Background:

  • Protein structure and function arise from the interplay of constituent amino acids.
  • Evolutionary analysis of protein families reveals interdependence between amino acid positions.
  • Previous methods explored sequence subsets to infer residue associations.

Purpose of the Study:

  • To develop a quantitative algorithm for assessing amino acid covariation.
  • To enhance the detection of physically proximate residues in protein structures.

Main Methods:

  • Developed a quantitative algorithm based on explicit likelihood calculations.
  • Applied the algorithm to 138 Pfam protein families with known structures.

Main Results:

  • The algorithm demonstrates improved power in identifying physically close residues.
  • The method outperforms a previous approach by Ranganathan and colleagues.

Conclusions:

  • The developed algorithm effectively identifies co-varying amino acids.
  • This approach enhances our understanding of protein structure-function relationships through evolutionary analysis.