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Related Experiment Videos

Comparison of performance in successive CASP experiments.

C Venclovas1, A Zemla, K Fidelis

  • 1Biology and Biotechnology Research Program, Lawrence Livermore National Laboratory, Livermore, California, USA.

Proteins
|February 9, 2002
PubMed
Summary

Protein structure prediction performance shows slow progress, with alignment quality improving slightly between CASP1 and CASP4. Alignment errors remain a key challenge in modeling, especially for low sequence identity targets.

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Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure prediction

Background:

  • The Critical Assessment of Protein Structure Prediction (CASP) experiments provide a benchmark for evaluating protein structure prediction methods.
  • Standardized performance comparison across successive CASP experiments is essential to track progress and identify areas needing improvement.

Purpose of the Study:

  • To analyze and compare performance across CASP1, CASP2, CASP3, and CASP4 using a unified difficulty scale.
  • To assess progress in protein structure prediction, particularly in sequence alignment and new fold modeling.

Main Methods:

  • Analysis of CASP1-CASP4 results, incorporating CASP4 data into previous analyses.
  • Utilization of a unified difficulty scale to compare performance as a function of target difficulty.

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  • Evaluation of performance in aligning target sequences to structural templates and in new fold modeling.

    • Main Results:

    • Clear improvement in alignment quality between CASP1 and CASP2, with minimal detectable improvement between CASP3 and CASP4.
    • Alignment remains the primary source of error for models with less than 30% sequence identity.
    • Limited numerical evidence for significant progress in new fold modeling between CASP3 and CASP4, despite subjective consensus on progress.

    Conclusions:

    • Protein structure prediction has seen slow, incremental progress, particularly in alignment quality.
    • Alignment accuracy is a critical bottleneck, especially for targets with low sequence identity.
    • Progress in new fold modeling is debated, with subjective agreement on advancement but limited quantitative support.