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Practical lessons from protein structure prediction.

Krzysztof Ginalski1, Nick V Grishin, Adam Godzik

  • 1BioInfoBank Institute ul. Limanowskiego 24A, 60-744 Poznań, Poland.

Nucleic Acids Research
|April 5, 2005
PubMed
Summary
This summary is machine-generated.

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Protein structure prediction methods offer a fast and cost-effective way to determine protein folds, especially when experimental methods are slow. Community assessments are driving improvements in these valuable computational tools.

Area of Science:

  • Structural biology
  • Computational biology
  • Bioinformatics

Background:

  • Automated protein structure determination is slow, leaving many protein families without known spatial structures.
  • Structural genomics projects face challenges in assigning folds for entire proteomes.

Purpose of the Study:

  • To provide an overview of current practical protein structure prediction approaches.
  • To discuss recent advances in assessing prediction quality.

Main Methods:

  • Review of existing protein structure prediction algorithms.
  • Analysis of community-wide assessment experiments for prediction methods.

Main Results:

  • Prediction algorithms offer valuable structural information for many proteins.

Related Experiment Videos

  • High-quality prediction methods have advanced significantly due to objective assessments.

    • Conclusions:

    • Practical protein structure prediction methods can generate accurate fold assignments.
    • Advances in assessment experiments are crucial for improving prediction accuracy.