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Protein fold recognition by mapping predicted secondary structures

R B Russell1, R R Copley, G J Barton

  • 1University of Oxford, Laboratory of Molecular Biophysics, England.

Journal of Molecular Biology
|June 14, 1996
PubMed
Summary
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This study introduces a novel protein fold recognition method using secondary structure assignments. The technique effectively identifies similar protein folds even without sequence similarity, improving accuracy over existing tools.

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein structure prediction

Background:

  • Protein fold recognition is crucial for understanding protein function.
  • Identifying similarities between protein folds is challenging, especially without sequence homology.
  • Existing methods often struggle with sequence-dissimilar proteins.

Purpose of the Study:

  • To develop a new strategy for protein fold recognition based on secondary structure assignments.
  • To enable detection of similarities between protein folds independent of sequence similarity.
  • To improve the accuracy and efficiency of protein fold identification.

Main Methods:

  • Secondary structure mapping to identify potential matches between query and known protein structures.

Related Experiment Videos

  • Application of structural filters to eliminate invalid structural configurations.
  • Ranking of surviving maps using alignment scores of predicted and experimental accessibilities.

    • Main Results:

    • The method correctly identified the fold in 8/11 cases for sequence-dissimilar proteins using secondary structure assignments.
    • Achieved 10/11 correct structural class predictions, outperforming the THREADER program.
    • Demonstrated high alignment accuracy (86%) with experimentally determined secondary structures.

    Conclusions:

    • The developed method offers a robust approach for protein fold recognition, particularly for sequence-dissimilar proteins.
    • Improvements in secondary structure prediction accuracy are expected to enhance the method's performance.
    • The technique shows promise for applications in NMR structure determination and other areas of structural biology.