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Related Experiment Videos

What are the baselines for protein fold recognition?

L J McGuffin1, K Bryson, D T Jones

  • 1Bioinformatics Group, Department of Biological Sciences, Brunel University, Uxbridge UB8 3PH, UK.

Bioinformatics (Oxford, England)
|February 27, 2001
PubMed
Summary

Establishing baseline success for protein fold recognition is crucial. Simple methods using secondary structure information provide useful baselines but cannot alone create accurate protein classifications.

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Area of Science:

  • Bioinformatics
  • Structural Biology
  • Computational Biology

Background:

  • Protein fold recognition benchmarks lack established baseline success levels.
  • Intelligent guesswork and simple methods using secondary structure information are explored for fold determination.
  • The utility of these methods for constructing hierarchical classifications is questioned.

Purpose of the Study:

  • To establish baseline success levels for protein fold recognition methods.
  • To assess the accuracy of methods using varying levels of information, including secondary structure.
  • To evaluate the potential of simple methods for creating viable protein structural classifications.

Main Methods:

  • Devised and tested rapid automatic methods for scoring protein domain similarities.

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  • Included methods with no secondary structure information and complex secondary structure alignments.
  • Assessed accuracy against the Class Architecture Topology Homology (CATH) classification, using random assignment and FSSP as controls.

    • Main Results:

    • A random fold assignment method established a lower baseline of 11% true positives (3% false positives).
    • The optimal secondary structure alignment method achieved 27% true positives (3% false positives) against CATH.
    • In CASP-like assessments, random guessing yielded 6% accuracy, while secondary structure methods reached 32%.

    Conclusions:

    • Simple methods using secondary structure information are insufficient for accurate protein taxonomy.
    • These methods, however, provide valuable baselines for protein fold recognition.
    • Approximately 6% of targets could be randomly assigned, and up to 32% recognized using secondary structure comparisons.