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Analysis of domain structural class using an automated class assignment protocol

A D Michie1, C A Orengo, J M Thornton

  • 1Department of Biochemistry & Molecular Biology, University College London, England.

Journal of Molecular Biology
|September 20, 1996
PubMed
Summary
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This study presents a method to automatically classify protein structures into distinct classes, achieving 90% accuracy. It also suggests merging the alpha/beta and alpha+beta classes into a single alpha beta class for better representation.

Area of Science:

  • Structural biology
  • Bioinformatics
  • Computational biology

Background:

  • The Levitt & Chothia (1976) classification defined four structural classes for protein domains.
  • Contemporary protein structure datasets require robust methods for accurate classification.

Purpose of the Study:

  • To examine the segregability of current protein structures into the original four classes.
  • To develop a simple, automated method for assigning protein domains to structural classes.
  • To investigate potential refinements to existing protein structure classification schemes.

Main Methods:

  • Analysis of known three-dimensional protein structures.
  • Development of an automated classification procedure using helix/sheet content, secondary structure contacts, and sequential order.

Related Experiment Videos

  • Application of the method to manually classified, non-homologous protein domains and a separate test set.

    • Main Results:

    • The automated method successfully classified approximately 90% of protein domains with high accuracy.
    • A subset of structures were borderline, requiring manual inspection.
    • Re-examination suggested merging the alpha/beta and alpha+beta classes into a single, more encompassing alpha beta class.

    Conclusions:

    • Distinct classes of protein structure exist, though some intermediate forms are observed.
    • A simple, automated method can classify 90% of protein domains with high accuracy.
    • The alpha beta class is a more natural representation, subdivisible by sheet type (parallel, antiparallel, mixed).
    • This work provides a foundation for automated phenetic description of protein structure.