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De novo protein structure determination from near-atomic-resolution cryo-EM maps

Nature Methods volume 12, pages 335–338 (2015)Cite this article

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Abstract

We present a de novo model-building approach that combines predicted backbone conformations with side-chain fit to density to accurately assign sequence into density maps. This method yielded accurate models for six of nine experimental maps at 3.3- to 4.8-Å resolution and produced a nearly complete model for an unsolved map containing a 660-residue heterodimeric protein. This method should enable rapid and reliable protein structure determination from near-atomic-resolution cryo-electron microscopy (cryo-EM) maps.

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Figure 1: Protocol overview.
Figure 2: High-accuracy model building in near-atomic-resolution cryo-EM maps.
Figure 3: Blind structure determination of the VipA/VipB complex from V. cholerae.

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Electron Microscopy Data Bank

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Electron Microscopy Data Bank

Protein Data Bank

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Acknowledgements

The authors thank K. Laidig and D. Alonso for setting up and managing the computational resources. This work was supported by the US National Institutes of Health under award numbers R01GM092802 (R.Y.-R.W. and D.B.), EB001567 (E.H.E.) and R01GM098672 (Y.C.); the Swiss systems biology initiative SystemsX.ch grant CINA (M.K.); the University of California, San Francisco, Program for Breakthrough Biomedical Research (Y.C.); and Howard Hughes Medical Institute (D.B.). We thank Y. Liu for the use of his clustering algorithm.

Author information

Author notes

  1. Xueming Li

    Present address: Present address: School of Life Science, Tsinghua University, Beijing, China.,

Authors and Affiliations

  1. Graduate program in Biological Physics, Structure and Design, University of Washington, Seattle, Washington, USA

    Ray Yu-Ruei Wang

  2. Department of Biochemistry, University of Washington, Seattle, Washington, USA

    Ray Yu-Ruei Wang, David Baker & Frank DiMaio

  3. Focal Area Infection Biology, Biozentrum, University of Basel, Basel, Switzerland

    Mikhail Kudryashev & Marek Basler

  4. Center for Cellular Imaging and NanoAnalytics, Biozentrum, University of Basel, Basel, Switzerland

    Mikhail Kudryashev

  5. Department of Biochemistry and Biophysics, The Keck Advanced Microscopy Laboratory, University of California, San Francisco, San Francisco, California, USA.,

    Xueming Li & Yifan Cheng

  6. Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA

    Edward H Egelman

  7. Howard Hughes Medical Institute, University of Washington, Seattle, Washington, USA

    David Baker

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Contributions

R.Y.-R.W. performed the research and drafted the manuscript. F.D. and D.B. supervised the research and edited the draft. M.K., E.H.E. and M.B. provided the helical reconstruction map of the VipA/VipB complex and compared the automated model with their manually traced model initially. X.L. and Y.C. provided the 20S map at 4.8-Å resolution. All authors edited the final manuscript.

Corresponding author

Correspondence to Frank DiMaio.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 RosettaCM fixes placement errors in the final partial model of FrhA.

(a) One case where there is an error in fragment placement. (b) Density-guided rebuilding in RosettaCM is able to correct this error as the missing residues are rebuilt. The backbone trace in grey indicates the native structure (4ci0).

Supplementary Figure 2 Problems in building β-sheets.

Each row indicates a case where our automatic approach failed to determine the structure: VP6 at 3.8 Å (top) and STIV at 3.9 Å (bottom). Illustrated are the density map (left), the partial model at the iteration with highest accuracy (middle), and the native structure (right).

Supplementary Figure 3 Real-space density correlation over ambiguous region in the map.

A structural alignment of the residues with a discrepancy in sequence registration is indicated on the x-axis (the residues in between the orange and blue arrows in Figure 3a and 3b). The sequence assignment of the automated and manual models is labeled on the upper and lower axes, respectively. The blue line (automated model) and the red line (manual model) show the real-space density correlation for each assignment (y-axis). Real-space density correlation was calculated using density_tools in Rosetta with a 2.5Å mask.

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Supplementary Figures 1–3 and Supplementary Tables 1–3 (PDF 1340 kb)

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Wang, RR., Kudryashev, M., Li, X. et al. De novo protein structure determination from near-atomic-resolution cryo-EM maps. Nat Methods 12, 335–338 (2015). https://doi.org/10.1038/nmeth.3287

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