Decision-Making in Structure Solution using Bayesian Estimates of Map Quality: The PHENIX AutoSol Wizard
Estimates of the quality of experimental maps are important in many stages of structure determination of macromolecules. Map quality is defined here as the correlation between a map and the map calculated based on a final refined model. Here we examine 10 different measures of experimental map quality using a set of 1359 maps calculated by reanalysis of 246 solved MAD, SAD, and MIR datasets. A simple Bayesian approach to estimation of map quality from one or more measures is presented. We find that a Bayesian estimator based on the skew of histograms of electron density is the most accurate of the 10 individual Bayesian estimators of map quality examined, with a correlation between estimated and actual map quality of 0.90. A combination of the skew of electron density with the local correlation of rms density gives a further improvement in estimating map quality, with an overall correlation coefficient of 0.92. The PHENIX AutoSol Wizard carries out automated structure solution based on any combination of SAD, MAD, SIR, or MIR datasets. The Wizard is based on tools from the PHENIX package and uses the Bayesian estimates of map quality described here to choose the highest-quality solutions after experimental phasing.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- Physical Biosciences Division
- DOE Contract Number:
- DE-AC02-05CH11231; 1P01 GM063210
- OSTI ID:
- 961603
- Report Number(s):
- LBNL-1970E; TRN: US200923%%210
- Journal Information:
- Acta Crystallographica D, Journal Name: Acta Crystallographica D
- Country of Publication:
- United States
- Language:
- English
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