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Related Experiment Videos

Fitting electron density by systematic search.

R J Read1, J Moult

  • 1Department of Medical Microbiology and Infectious Diseases, University of Alberta, Edmonton, Canada.

Acta Crystallographica. Section A, Foundations of Crystallography
|March 1, 1992
PubMed
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This study introduces a systematic method for automatically refining protein structures, reducing manual work. It systematically generates and scores protein conformations against diffraction data, improving structural accuracy.

Area of Science:

  • Structural Biology
  • Computational Biology
  • Biophysics

Background:

  • Manual refinement of protein structures is labor-intensive and time-consuming.
  • Accurate protein structure determination is crucial for understanding biological function and disease.

Purpose of the Study:

  • To develop a systematic, automated approach for refining protein structures.
  • To reduce the reliance on manual intervention in protein structure refinement.
  • To evaluate the effectiveness of different scoring functions in this automated process.

Main Methods:

  • Systematic generation of possible polypeptide chain conformations.
  • Scoring trial segments based on agreement with observed diffraction data.
  • Exhaustive sampling of conformational space to ensure inclusion of reasonable conformations.

Related Experiment Videos

  • Testing various score functions, including local electron-density correlations and global structure-factor agreements.

    • Main Results:

    • The developed systematic search approach can automatically refine protein structures.
    • The best score functions demonstrate reasonable predictive power for protein conformation.
    • Score functions vary in predictive power and bias towards the current model.
    • Related functions can identify poorly fitting regions, aiding manual inspection.

    Conclusions:

    • Automated protein structure refinement using systematic search is feasible.
    • The choice of scoring function significantly impacts refinement accuracy.
    • This approach has the potential to streamline the protein structure determination process.
    • Identifying poorly fitting regions can enhance the efficiency of manual model inspection.