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Using SAD data in Phaser.

Randy J Read1, Airlie J McCoy

  • 1CIMR Haematology, University of Cambridge, Wellcome Trust/MRC Building, Cambridge, England. rjr27@cam.ac.uk

Acta Crystallographica. Section D, Biological Crystallography
|April 5, 2011
PubMed
Summary
This summary is machine-generated.

Phaser software enhances macromolecular structure determination using likelihood-based methods for molecular replacement and single-wavelength anomalous diffraction (SAD) phasing. It improves accuracy by identifying atom sites and anomalous scatterers through log-likelihood gradient maps.

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Area of Science:

  • Crystallography
  • Structural Biology
  • Computational Biology

Background:

  • Macromolecular crystal structure determination is crucial for understanding biological processes.
  • Likelihood-based methods offer robust approaches to phasing in crystallography.
  • Molecular replacement and single-wavelength anomalous diffraction (SAD) are key phasing techniques.

Purpose of the Study:

  • To present Phaser, a program implementing advanced likelihood-based methods for macromolecular structure solution.
  • To detail the SAD phasing strategy within Phaser, utilizing a likelihood target.
  • To describe the log-likelihood gradient map and automated completion algorithm for atom identification.

Main Methods:

  • Phaser employs a likelihood target derived from joint probability distributions of Friedel-related structure factors.
  • Phasing initiates from a substructure (anomalous scatterers or protein model).
  • Log-likelihood gradient maps guide the addition of new atoms and identify anomalous scatterers.

Main Results:

  • The automated completion algorithm efficiently adds sites, refines parameters, and removes low-occupancy atoms.
  • Log-likelihood gradient maps are more sensitive than conventional methods for identifying anomalous scatterers.
  • Phaser's iterative completion algorithm successfully identifies a greater number of convincing atom sites.

Conclusions:

  • Phaser provides a powerful and sensitive tool for macromolecular structure determination.
  • The likelihood-based approach and log-likelihood gradient maps significantly advance SAD phasing capabilities.
  • The program facilitates more accurate and comprehensive identification of substructures and anomalous scatterers.