A density-modification procedure for improving maps from single-particle electron cryogenic microscopy (cryo-EM) is presented. The theoretical basis of the method is identical to that of maximum-likelihood density modification, previously used to improve maps from macromolecular X-ray crystallography. Key differences from applications in crystallography are that the errors in Fourier coefficients are largely in the phases in crystallography but in both phases and amplitudes in cryo-EM, and that half-maps with independent errors are available in cryo-EM. These differences lead to a distinct approach for combination of information from starting maps with information obtained in the density-modification process. The density-modification procedure was applied to a set of 104 datasets and improved map-model correlation and increased the visibility of details in many of the maps. The procedure requires two unmasked half-maps and a sequence file or other source of information on the volume of the macromolecule that has been imaged.
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The source data for Figs. 1 and 2 are available as Excel worksheets. The spreadsheet and underlying data used to generate the figures in this work and examples of the density-modified maps presented in the figures are available at http://phenix-online.org/phenix_data/terwilliger/denmod_2020/.
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This work was supported by the National Institutes of Health (grant no. GM063210 to P.D.A., R.J.R. and T.C.T. and grant no. R01-GM080139 to S.J.L.), the Wellcome Trust (grant no. 20947/Z/17/Z to R.J.R.) and the Phenix Industrial Consortium. This work was supported in part by the US Department of Energy under Contract No. DE-AC02-05CH11231 at the Lawrence Berkeley National Laboratory.
The authors declare no competing interests.
Peer review information Arunima Singh was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
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Terwilliger, T.C., Ludtke, S.J., Read, R.J. et al. Improvement of cryo-EM maps by density modification. Nat Methods 17, 923–927 (2020). https://doi.org/10.1038/s41592-020-0914-9
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