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A fully automatic method yielding initial models from high-resolution cryo-electron microscopy maps

Nature Methods volume 15, pages 905–908 (2018)Cite this article

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Abstract

We report a fully automated procedure for the optimization and interpretation of reconstructions from cryo-electron microscopy (cryo-EM) data, available in Phenix as phenix.map_to_model. We applied our approach to 476 datasets with resolution of 4.5 Å or better, including reconstructions of 47 ribosomes and 32 other protein–RNA complexes. The median fraction of residues in the deposited structures reproduced automatically was 71% for reconstructions determined at resolutions of 3 Å or better and 47% for those at resolutions worse than 3 Å.

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Fig. 1: Automated interpretation of cryo-EM maps.
Fig. 2: Residues in deposited PDB models reproduced by automated analysis of cryo-EM reconstructions.

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Data availability

The datasets generated and/or analyzed during the current study are available in the Phenix data repository at https://phenix-online.org/phenix_data/terwilliger/map_to_model_2018. All the parameters, including resolution and specifications of reconstruction symmetry used in this work, are available on this site, along with all of the models produced.

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Acknowledgements

This work was supported by the NIH (grant GM063210 to P.D.A. and T.C.T.) and the Phenix Industrial Consortium. This work was supported in part by the US Department of Energy under Contract No. DE-AC02-05CH11231 at Lawrence Berkeley National Laboratory. This research used resources provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the US Department of Energy National Nuclear Security Administration under Contract No. DE-AC52-06NA25396. We thank G. Terashi and D. Kihara for providing the MAINMAST and Rosetta models built into segmented maps.

Author information

Authors and Affiliations

  1. Los Alamos National Laboratory, Los Alamos, NM, USA

    Thomas C. Terwilliger

  2. New Mexico Consortium, Los Alamos, NM, USA

    Thomas C. Terwilliger

  3. Molecular Biophysics & Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Paul D. Adams, Pavel V. Afonine & Oleg V. Sobolev

  4. Department of Bioengineering, University of California, Berkeley, Berkeley, CA, USA

    Paul D. Adams

  5. Department of Physics and International Centre for Quantum and Molecular Structures, Shanghai University, Shanghai, China

    Pavel V. Afonine

Authors
  1. Thomas C. Terwilliger
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  2. Paul D. Adams
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  3. Pavel V. Afonine
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  4. Oleg V. Sobolev
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Contributions

P.V.A. and O.V.S. developed core tools for map segmentation and secondary-structure restraints; P.D.A. and P.V.A. developed the real space refinement tools; T.C.T. developed the phenix.map_to_model tool and carried out the analyses; and P.D.A. and T.C.T. supervised the work.

Corresponding author

Correspondence to Thomas C. Terwilliger.

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The authors declare no competing interests.

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Integrated supplementary information

Supplementary Figure 1 Automatic map segmentation.

A. Automatic segmentation of map for β-galactosidase1 at a resolution of 2.2 Å (EMD entry 2984). Symmetry was identified using the Phenix tool phenix.map_symmetry and specifying the symmetry as D2. The map, the sequence of β-galactosidase and the symmetry file were supplied as inputs to the Phenix tool phenix.map_box with the keyword extract_unique=True. The automatically extracted unique part of the map is shown in red and the entire map is shown in yellow. B. Automatic segmentation of map for group II chaperonin2 at a resolution of 4.3 Å (EMD entry 5137). The map, the sequence and symmetry (D8) were supplied as inputs to the Phenix tool phenix.map_box along with the keyword extract_unique=True. The automatically extracted unique part of the map is shown in red and chains A (green) and H (blue) of the deposited model (3Los) are shown. Graphics created with Chimera3. References: 1. Bartesaghi, A. et al. Science 348, 1147–1151 (2015). 2. Zhang, J. et al. Nature 463, 379–383 (2010). 3. Pettersen, E.F. et al. J. Comput. Chem. 25, 1605–1612 (2004).

Supplementary Figure 2 Evaluation of model quality, and comparison with deposited models.

Validation measures for deposited models from PDB (blue columns) and automatically generated models (orange columns), and automatically generated models after removal of an average of 0.4% of side chains and 0.4% of full residues that clashed using the Phenix tool phenix.remove_clashes (gray). A. Clashscore (bad contacts per 1,000 atoms). B. Map correlation. C. Ramachandran outliers (%), D, rotamer outliers (%), E, Bond rmsd (Å), F. Angle rmsd (degrees), G. C-β deviations.

Supplementary Figure 3 Evaluation of model quality as a function of map resolution.

Validation measures for automatically generated models at resolutions of 3.5–4.5 Å (blue) and at 2.2–3.49 Å (orange). A. Clashscore (bad contacts per 1,000 atoms). B. Map correlation. C. Ramachandran outliers (%), D, rotamer outliers (%), E, Bond rmsd (A), F. Angle rmsd (degrees), G. C-β deviations.

Supplementary Figure 4 RNA model building.

RNA model-building into a cut-out region of RNA density from Leishmania ribosome1 at a resolution of 2.5 Å (EMDB entry 7025). A. Model building and real-space refinement using base-paired RNA helices. B. Model building and real-space refinement with the same map using standard nucleic acid model building. Potential hydrogen bonds indicated by dotted red lines. Graphics created with Chimera2. References: 1. Shalev-Benami, M. et al. Nat. Commun. 8, 1589 (2017). 2. Pettersen, E.F. et al. J. Comput. Chem. 25, 1605–1612 (2004).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Table 1 and Supplementary Results

Reporting Summary

Supplementary Data 1

Summary data for all map_to_model results

Supplementary Data 2

Summary data for Figure 2 map_to_model results

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Terwilliger, T.C., Adams, P.D., Afonine, P.V. et al. A fully automatic method yielding initial models from high-resolution cryo-electron microscopy maps. Nat Methods 15, 905–908 (2018). https://doi.org/10.1038/s41592-018-0173-1

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