Abstract

The estimate of the root-mean-square deviation (r.m.s.d.) in coordinates between the model and the target is an essential parameter for calibrating likelihood functions for molecular replacement (MR). Good estimates of the r.m.s.d. lead to good estimates of the variance term in the likelihood functions, which increases signal to noise and hence success rates in the MR search. Phaser has hitherto used an estimate of the r.m.s.d. that only depends on the sequence identity between the model and target and which was not optimized for the MR likelihood functions. Variance-refinement functionality was added to Phaser to enable determination of the effective r.m.s.d. that optimized the log-likelihood gain (LLG) for a correct MR solution. Variance refinement was subsequently performed on a database of over 21 000 MR problems that sampled a range of sequence identities, protein sizes and protein fold classes. Success was monitored using the translation-function Z-score (TFZ), where a TFZ of 8 or over for the top peak was found to be a reliable indicator that MR had succeeded for these cases with one molecule in the asymmetric unit. Good estimates of the r.m.s.d. are correlated with the sequence identity and the protein size. A new estimate of the r.m.s.d. that uses these two parameters in a function optimized to fit the mean of the refined variance is implemented in Phaser and improves MR outcomes. Perturbing the initial estimate of the r.m.s.d. from the mean of the distribution in steps of standard deviations of the distribution further increases MR success rates.

Highlights

  • The estimate of the root-mean-square deviation (RMSD) in coordinates between the model and the target is an essential parameter for calibrating likelihood functions for molecular replacement (MR) [1]

  • Good estimates of the RMSD lead to good estimates of the variance term, in the likelihood functions [2], which increases signal to noise and success rates in the MR search

  • Variance refinement functionality was added to Phaser to enable determination of the VRMS, the RMSD that optimises the log-likelihood gain (LLG) for a correct MR solution

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Summary

Introduction

[MS04-P11] Improved estimates of coordinate error for molecular replacement Robert D Oeffnera, Gábor Bunkóczia, Airlie J McCoya and Randy J Reada aCambridge Institute for Medical Research, University of Cambridge, Hills Road, Cambridge, CB2 0XY, United Kingdom. VRMS values has an approximately Gaussian deviation from the eVRMS, with the size of the error being proportional to the eVRMS. The eVRMS estimates have a small but measurable dependence on SCOP fold class [5].

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