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Related Experiment Videos

Fitting molecular fragments into electron density.

Kevin Cowtan1

  • 1Department of Chemistry, University of York, Heslington, York YO10 5DD, England. cowtan@ysbl.york.ac.uk

Acta Crystallographica. Section D, Biological Crystallography
|December 21, 2007
PubMed
Summary
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Molecular replacement helps locate large structures using only magnitude data. Phase information enables finding smaller fragments, aiding automated protein model building and main-chain tracing.

Area of Science:

  • Structural biology
  • Computational crystallography

Background:

  • Molecular replacement (MR) is a key technique for determining the three-dimensional structure of molecules using diffraction data.
  • MR typically utilizes the magnitudes of structure factors to position known structural components within an unknown crystal structure.

Purpose of the Study:

  • To review various approaches to molecular replacement, particularly when phase information is available.
  • To explore the application of MR techniques in automated model building, focusing on protein main-chain trace sequencing.

Main Methods:

  • Review of established and novel molecular replacement methodologies.
  • Detailed examination of a specific MR technique applied to automated model building.
  • Focus on computational strategies for six-dimensional rotation and translation searches.

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Main Results:

  • Molecular replacement is effective for locating large models using structure-factor magnitudes.
  • The inclusion of phase information significantly enhances the ability to locate smaller structural fragments, from individual atoms to entire domains.
  • A specific MR approach demonstrates utility in automated protein model building, including main-chain trace sequencing.

Conclusions:

  • Molecular replacement, especially with phase information, is a versatile tool for structural determination.
  • Advanced MR techniques are crucial for the automation of complex tasks like protein model building.
  • The ability to trace protein main chains is a significant advancement facilitated by these computational methods.