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Fold recognition using sequence and secondary structure information.

K K Koretke1, R B Russell, R R Copley

  • 1Microbial Bioinformatics Group, SmithKline Beecham Pharmaceuticals, Collegeville, Pennsylvania 19426-0989, USA.

Proteins
|October 20, 1999
PubMed
Summary
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Researchers developed a protein structure prediction method for the CASP3 experiment. This approach correctly identified the fold for seven out of twenty-one protein targets, highlighting potential for improvement through automation.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Protein Structure Prediction

Background:

  • The Critical Assessment of protein Structure Prediction (CASP) experiment benchmarks protein structure prediction methods.
  • Accurate protein fold recognition is crucial for understanding protein function and biological processes.
  • Existing sequence and structure-based methods have limitations in identifying novel or distantly related protein folds.

Purpose of the Study:

  • To apply and evaluate a combination of sequence search and structure prediction techniques for protein fold recognition in the CASP3 experiment.
  • To assess the effectiveness of expanding sequence space and utilizing secondary structure prediction for identifying protein folds.
  • To determine the success rate of the developed computational pipeline in predicting protein folds compared to known structures.

Related Experiment Videos

Main Methods:

  • Iterative sequence searching using PSI-BLAST, followed by searches for low-scoring sequences and conserved patterns.
  • Hierarchical protein family division and multiple sequence alignment using the MACAW program.
  • Consensus secondary structure prediction via Jpred server and structure space searching with MAP program.
  • Comparison with SCOP database folds and visual inspection for unassigned targets.

Main Results:

  • The applied methodology achieved correct fold recognition for seven out of twenty-one CASP3 targets.
  • One additional target received a partially correct fold prediction.
  • Retrospective analysis indicated that automating sequence search procedures could have improved results by at least three additional correct predictions.

Conclusions:

  • The developed pipeline demonstrated moderate success in protein fold recognition for the CASP3 targets.
  • The study highlights the importance of comprehensive sequence space exploration and integration of secondary structure information.
  • Automation of sequence search steps is identified as a key area for future improvement in protein structure prediction.