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Improved estimates of coordinate error for molecular replacement.

Robert D Oeffner1, Gábor Bunkóczi, Airlie J McCoy

  • 1Cambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge CB2 0XY, England.

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|November 6, 2013
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Summary
This summary is machine-generated.

Improving molecular replacement (MR) success rates involves refining the root-mean-square deviation (r.m.s.d.) estimate. New methods using sequence identity and protein size enhance accuracy and boost MR outcomes.

Keywords:
Phasermaximum likelihoodmolecular replacement

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Area of Science:

  • Structural Biology
  • Computational Biology
  • Crystallography

Background:

  • Accurate estimation of root-mean-square deviation (r.m.s.d.) in coordinates is crucial for calibrating likelihood functions in molecular replacement (MR).
  • Existing r.m.s.d. estimates in Phaser, based solely on sequence identity, were not optimized for MR likelihood functions, potentially limiting success rates.
  • Improved variance term estimation in likelihood functions enhances signal-to-noise ratio, directly impacting the success of MR searches.

Purpose of the Study:

  • To develop and implement an improved r.m.s.d. estimation method within Phaser to optimize molecular replacement (MR) outcomes.
  • To determine the effective r.m.s.d. that maximizes log-likelihood gain (LLG) for correct MR solutions through variance refinement.
  • To validate the new r.m.s.d. estimation strategy across a diverse dataset of MR problems.

Main Methods:

  • Implemented variance-refinement functionality in Phaser to identify optimal r.m.s.d. values.
  • Performed variance refinement on a large database (>21,000) of MR problems with varying sequence identities, protein sizes, and fold classes.
  • Monitored MR success using the translation-function Z-score (TFZ), with TFZ ≥ 8 indicating reliable solutions for single-molecule asymmetric units.

Main Results:

  • Found that optimal r.m.s.d. estimates are correlated with sequence identity and protein size.
  • Developed a new r.m.s.d. estimation function incorporating sequence identity and protein size, optimized to fit the mean of refined variances.
  • Demonstrated that the new r.m.s.d. estimation in Phaser improves MR success rates.
  • Showed that perturbing the initial r.m.s.d. estimate from the distribution mean in standard deviation steps further increases MR success.

Conclusions:

  • The refined r.m.s.d. estimation, dependent on sequence identity and protein size, significantly enhances molecular replacement (MR) success rates.
  • Variance refinement and strategic perturbation of r.m.s.d. estimates are effective strategies for optimizing MR.
  • The updated Phaser implementation provides more reliable MR solutions by improving the accuracy of essential parameter estimations.