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Estimating local protein model quality: prospects for molecular replacement.

Björn Wallner1

  • 1Division of Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping, Sweden.

Acta Crystallographica. Section D, Structural Biology
|March 6, 2020
PubMed
Summary

Local error estimates from ProQ3D software significantly improve protein model quality for molecular replacement (MR). This enhancement leads to more successful MR experiments, especially for challenging targets.

Keywords:
ProQ3Dlocal error estimatesmolecular replacementprotein model quality assessment

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Area of Science:

  • Structural biology
  • Computational biology
  • Biophysics

Background:

  • Protein model quality assessment is crucial for downstream applications like molecular replacement (MR).
  • Estimating local errors in protein models can guide refinement and improve model accuracy.
  • ProQ3D is an advanced software for assessing protein model quality and predicting local errors.

Purpose of the Study:

  • To evaluate the utility of local error estimates from ProQ3D for enhancing protein models in molecular replacement (MR).
  • To demonstrate the improvement in MR success rates using ProQ3D-derived error estimates compared to previous methods or no estimates.

Main Methods:

  • Utilizing local error estimates generated by ProQ3D to adjust B factors in protein homology models.
  • Assessing the impact of these adjustments on the log-likelihood gain (LLG) scores in MR.
  • Testing the method on a dataset of 431 homology models, including difficult MR targets.

Main Results:

  • Adjusting B factors with ProQ3D improved the average log-likelihood gain (LLG) score by over 50%.
  • Models with ProQ3D error estimates achieved an LLG >50 for 48.5% of targets, a significant improvement over ProQ2 (40.6%) and no estimates (17.2%).
  • ProQ3D demonstrated substantial added value in enabling MR for a larger proportion of challenging targets.

Conclusions:

  • Local error estimates from ProQ3D can substantially increase the quality and success rate of protein models in molecular replacement.
  • ProQ3D represents a significant advancement over previous methods for utilizing model quality information to facilitate MR.
  • The software is accessible as a server and standalone download, promoting wider adoption in structural biology research.