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Related Experiment Videos

Refinement of protein structures by iterative comparative modeling and CryoEM density fitting.

Maya Topf1, Matthew L Baker, Marc A Marti-Renom

  • 1Department of Biopharmaceutical Sciences, California Institute for Quantitative Biomedical Research, QB3, 1700 4th Street, Suite 503B, University of California at San Francisco, San Francisco, CA 94143-2552, USA.

Journal of Molecular Biology
|February 24, 2006
PubMed
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We developed an iterative method for protein structure modeling to improve component characterization in cryo-electron microscopy (cryoEM) density maps. This approach enhances model accuracy for macromolecular assemblies, aiding structural biology research.

Area of Science:

  • Structural Biology
  • Biophysics
  • Computational Biology

Background:

  • Cryo-electron microscopy (cryoEM) is crucial for determining macromolecular assembly structures.
  • Accurate protein structure modeling is essential for interpreting cryoEM density maps, especially for components with low sequence identity to known structures.

Purpose of the Study:

  • To develop and validate an iterative comparative protein structure modeling method for enhanced structure characterization within cryoEM density maps.
  • To improve the accuracy of protein models derived from low-resolution cryoEM data and remote templates.

Main Methods:

  • Iterative comparative protein structure modeling integrating sequence alignment, model building, and model assessment (Moulder protocol).
  • Optimization of model fitting into corresponding cryoEM density maps.

Related Experiment Videos

  • Benchmarking using simulated cryoEM density maps and known protein structures with <30% sequence identity.

    • Main Results:

    • The developed method improved the percentage of C(alpha) atoms within 5A of native structures from 52% to 66% compared to existing methods.
    • Application to the rice dwarf virus P8 capsid protein demonstrated improved C(alpha) root-mean-square deviation (RMSD) from 8.7A to 6.0A.
    • The fitness function remains a bottleneck for further error reduction, despite overall accuracy improvements.

    Conclusions:

    • The iterative modeling method significantly enhances protein structure characterization from cryoEM data, particularly for distantly related structures.
    • The protocol provides more accurate models that better fit cryoEM density maps, advancing the study of macromolecular assemblies.
    • The method is being integrated into MODELLER, promising broader applicability to the growing cryoEM structural database.