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Automated determination of fibrillar structures by simultaneous model building and fiber diffraction refinement

Abstract

For highly oriented fibrillar molecules, three-dimensional structures can often be determined from X-ray fiber diffraction data. However, because of limited information content, structure determination and validation can be challenging. We demonstrate that automated structure determination of protein fibers can be achieved by guiding the building of macromolecular models with fiber diffraction data. We illustrate the power of our approach by determining the structures of six bacteriophage viruses de novo using fiber diffraction data alone and together with solid-state NMR data. Furthermore, we demonstrate the feasibility of molecular replacement from monomeric and fibrillar templates by solving the structure of a plant virus using homology modeling and protein-protein docking. The generated models explain the experimental data to the same degree as deposited reference structures but with improved structural quality. We also developed a cross-validation method for model selection. The results highlight the power of fiber diffraction data as structural constraints.

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Figure 1: Macromolecular modeling plays a large role in structure determination from fiber diffraction data.
Figure 2: Fiber diffraction intensity calculations in real and reciprocal space at a given layer line.
Figure 3: Cross-validation with χ2free.
Figure 4: De novo structure determination of bacteriophages.
Figure 5: Molecular replacement of hibiscus latent Singapore virus.

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Acknowledgements

This work was supported by the Crafoord Foundation and the Sven and Lilly Lawski Foundation. The simulations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at Lunarc. We thank S.K. Tewary (University of Kansas) for sharing fiber diffraction data of HLSV and input files for X-PLOR simulations. We thank S. Bjelic, S. Rämisch and R. Lizatovic for critically reading the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

W.P. and I.A. designed the research, developed the methods and analyzed the data. W.P. carried out the simulations. W.P. and I.A. wrote the manuscript.

Corresponding authors

Correspondence to Wojciech Potrzebowski or Ingemar André.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Comparison between observed and calculated intensities.

For non-crystalline systems experimental fiber diffraction data (black) is confined to layer lines. Each layer is spaced along meridional direction at Z=l/c, where l is the layer line number and c is helical repeat; and sampled along the equator at an interval of R=0.0025 1/Å. Intensities were calculated from atomic coordinates in reciprocal space (blue, equation 5).

Supplementary Figure 2 Determining structures of bacteriophage viruses de novo with and without experimental data.

We ran Fold-And-Dock simulations guided by fiber diffraction data (blue) and in the absence of experimental data (green). The comparison is shown for: (a) Pf3 filamentous bacteriophage (PDB code: 1ifp), (b) filamentous bacteriophage PH75 (PDB code: 1hgv), (c) filamentous bacteriophage Pf1 (PDB code: 1ql1), (d) filamentous bacteriophage Pf1 (PDB code: 4ifm) and (e) fd filamentous bacteriophage (PDB code: 2c0w). (f) Additionally, fd filamentous bacteriophage (PDB code: 2c0x) simulations were guided by multiple experimental data sets (fiber diffraction and solid state NMR). Models generated without fiber diffraction were validated against work set with the Rosetta score application.

Supplementary Figure 3 Coarse-grained symmetrical docking of HLSV.

Coarse-grained symmetrical docking of (a) the monomeric structure of hibiscus latent Singapore virus (PDB code: 3pdm) and (b) the homology model based on the monomer of tobacco mosaic virus (PDB code: 2tmv). Blue dots corresponds to models obtained from docking guided by fiber diffraction data, while green for models generated without experimental restraints.

Supplementary Figure 4 CPU and GPU performance on calculations of all-atom intensity and derivatives.

All-atom intensity (equation 5) and derivatives (equations S5-S8) can be calculated sequentially using standard CPU or in parallel mode on a Graphical Processor Unit (GPU). We use a structure of hibiscus latent Singapore virus (HLSV) to compare the performance on both architectures. Monomer of HLSV has 162 amino-acid residues and was truncated by factor of 20 to perform calculations on models that consisted of 82, 102, 122 and 142 amino acid residues.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Table 1, Supplementary Notes 1 and 2 and Supplementary Protocol (PDF 1655 kb)

Supplementary Data 1

Protein models (ZIP 11329 kb)

Supplementary Data 2

Command files for running fiber diffraction modeling with Rosetta (ZIP 28624 kb)

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Potrzebowski, W., André, I. Automated determination of fibrillar structures by simultaneous model building and fiber diffraction refinement. Nat Methods 12, 679–684 (2015). https://doi.org/10.1038/nmeth.3399

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