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Related Experiment Video

Updated: Jul 8, 2026

RNA Secondary Structure Prediction Using High-throughput SHAPE
13:42

RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Rapid and automated substructure solution by Shake-and-Bake.

Hongliang Xu1, Charles M Weeks

  • 1Hauptman-Woodward Medical Research Institute and Department of Structural Biology, School of Medicine and Biomedical Sciences, State University of New York at Buffalo, 700 Ellicott Street, Buffalo, NY 14203, USA. xu@hwi.buffalo.edu

Acta Crystallographica. Section D, Biological Crystallography
|January 26, 2008
PubMed
Summary
This summary is machine-generated.

The Shake-and-Bake procedure, implemented in the SnB program, has been optimized for rapid and automated heavy-atom substructure determination. New features ensure higher success rates and cost-effectiveness in crystal structure analysis.

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Area of Science:

  • Crystallography
  • Structural Biology
  • Biophysics

Background:

  • Direct methods are crucial for determining heavy-atom substructures.
  • The Shake-and-Bake procedure is a successful direct method for this purpose.
  • The SnB program implements Shake-and-Bake within the BnP package.

Purpose of the Study:

  • To optimize the SnB program for rapid and automated substructure determination.
  • To enhance the success rates and cost-effectiveness of heavy-atom substructure determination.
  • To improve the reliability of substructure solution detection.

Main Methods:

  • Upgraded SnB with a new statistical minimal function.
  • Implemented an optimal FFT grid size for improved computational efficiency.
  • Introduced a dynamic figure of merit for automatic solution detection.
  • Employed alternation of anomalous and isomorphous dispersive differences.

Main Results:

  • Achieved higher success rates in substructure determination.
  • Significantly improved cost-effectiveness through optimized FFT grid size.
  • Enabled automatic detection of substructure solutions.
  • Virtually guaranteed substructure solutions through difference data alternation.

Conclusions:

  • The optimized SnB program offers a robust and efficient solution for automated heavy-atom substructure determination.
  • Enhancements lead to increased success rates and computational efficiency.
  • The upgraded SnB program is a valuable tool for protein structure determination.