Nature Methods: doi: /nmeth Supplementary Figure 1. Overview of the density-guided rebuilding and refinement protocol.
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1 Supplementary Figure 1 Overview of the density-guided rebuilding and refinement protocol. (a) Flowchart of the protocol. The protocol uses 250 cycles of local backbone rebuilding, followed by five cycles of alternating coordinate and B factor refinement. (b) An inset illustrating the new density-guided rebuilding step. A segment with poor fit to density is selected at random. Next, different backbone conformations consistent with the local sequence are first superimposed on the current model, then optimized into the map. Finally, the best fitting backbone conformation is selected, and backbone geometry near the segment is regularized.
2 Supplementary Figure 2 Model quality as a function of map resolution. For a given starting model of 20S, we compare refined model accuracy (the fraction of Cα atoms within 1 Å of the reference model on the y-axis) as a function of map resolution for Rosetta-refined models (solid) and MDFF-refined models (dashed). The comparison used (A) 1yar, (B) 1ryp and (C) 1m4y as representatives of easy, medium, and difficult refinement cases, respectively.
3 Supplementary Figure 3 Identification of model errors using the local density correlation. For each refined model of 20S, local correlation between each residue and the testing map is calculated. The fraction of residues deviate more than 1Å (black) or 2Å (green) from the reference model (y-axis) is plotted for each local correlation bin (x-axis) at (A) 3.3, (B) 4.1, (C) 4.4, and (D) 6.0Å resolutions.
4 Supplementary Figure 4 Cross-validation of Rosetta-refined models using FSC. The FSC (y-axis) is compared to the accuracy of refined models (x-axis). Refinement is carried out with reconstructed maps of (A) 20S proteasome at (magenta) 3.3Å, (cyan) 4.1 Å, (red) 4.4 Å, (blue) 5.0 Å and (green) 6.0 Å, and with maps of (B) prgh needle complex at (red) 4.6 Å, (blue) 5.4 Å and (green) 7.1 Å.
5 Supplementary Figure 5 An overview of map features necessary for accurate structure determination. (a) The 20S proteasome dataset at 4.1 Å nicely illustrates the necessary features for structure determination to atomic accuracy. The pitch of helices and individual strands are resolved, and while sidechains are not uniquely identifiable density for large sidechains is visible. (b) The same dataset at 6 Å resolution lacks these features: the pitch of helices in not identifiable, and sidechain density for large sidechains is not observed.
6 Supplementary Information Supplementary Table 1. A comparison to previously published methods. For a series of comparative models of 20S, our refinement was compared to two previously developed methods combining Rosetta refinement with experimental density data, comparing the fraction of Cα atoms within 1 Å using the same starting models. DiMaio as well as RosettaCM 2 augmented with fit-to-density-energy are both outperformed by the IterativeBuild method reported here. Results are reported for 20S maps at 3.3 and 4.4Å resolution. 20S proteosome (3.3Å) 20S proteosome (4.4Å) DiMaio 2009 Rosetta CM Iterative Build DiMaio 2009 Rosetta CM Iterative Build 1yar h4p iru unf nzj ryp q5q g0u hnz x3b g3k m4y Average
7 Supplementary References 1 DiMaio, F., Tyka, M. D., Baker, M. L., Chiu, W. & Baker, D. Refinement of protein structures into low-resolution density maps using rosetta. Journal of molecular biology 392, (2009). 2 Song, Y. et al. High-Resolution Comparative Modeling with RosettaCM. Structure 21, (2013). 3
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