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Related Experiment Videos

The two-dimensional histogram as a constraint for protein phase improvement.

A Goldstein1, K Y Zhang

  • 1Division of Basic Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA.

Acta Crystallographica. Section D, Biological Crystallography
|March 25, 1999
PubMed
Summary

The 2D histogram of protein electron density and its gradient is sensitive to phase error but not structure conformation. This finding aids in predicting ideal histograms and improving phasing methods.

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Area of Science:

  • Crystallography
  • Structural Biology
  • Computational Biology

Background:

  • Protein electron density maps are crucial for determining 3D structures.
  • Analyzing the distribution of electron density and its gradient provides insights into map quality.

Purpose of the Study:

  • To investigate the joint distribution of electron density and its gradient using a 2D histogram.
  • To assess the impact of resolution, temperature factor, conformation, and phase error on this 2D histogram.
  • To establish the utility of the 2D histogram in phasing and density modification.

Main Methods:

  • Generation of 2D histograms from electron density and gradient modulus for 16 protein structures.
  • Quantitative analysis of histogram similarity using correlation coefficient and residual.

Related Experiment Videos

  • Evaluation of sensitivity to resolution, temperature factor, conformation, and phase error.

    • Main Results:

    • The 2D histogram varies with resolution and temperature factor but is insensitive to protein structure conformation.
    • A 10-degree phase difference results in a correlation coefficient of 0.71 and a residual of 0.18.
    • Conformational changes introduce a phase error equivalent of approximately 4 degrees.

    Conclusions:

    • The 2D histogram is a robust descriptor of electron density map quality, conserved across different protein folds.
    • Its sensitivity to phase error makes it valuable for optimizing density modification and ab initio phasing.
    • The method can predict ideal 2D histograms for unknown structures, guiding experimental and computational efforts.