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. 2009 Sep 11;392(1):181-90.
doi: 10.1016/j.jmb.2009.07.008. Epub 2009 Jul 8.

Refinement of protein structures into low-resolution density maps using rosetta

Frank DiMaio  1 , Michael D Tyka, Matthew L Baker, Wah Chiu, David Baker
Affiliations

Refinement of protein structures into low-resolution density maps using rosetta

Frank DiMaio et al. J Mol Biol. .

Abstract

We describe a method based on Rosetta structure refinement for generating high-resolution, all-atom protein models from electron cryomicroscopy density maps. A local measure of the fit of a model to the density is used to directly guide structure refinement and to identify regions incompatible with the density that are then targeted for extensive rebuilding. Over a range of test cases using both simulated and experimentally generated data, the method consistently increases the accuracy of starting models generated either by comparative modeling or by hand-tracing the density. The method can achieve near-atomic resolution starting from density maps at 4-6 A resolution.

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Figures

Figure 1
Figure 1
The comparative modeling into density protocol. We initially build a threaded model from some alignment (blue), using cyclic coordinate descent to close gaps in the alignment (cyan). We then dock this threaded model into density, and identify regions that have a poor local agreement with the density data (red). We aggressively resample the conformations in these regions, scoring each potential conformation with Rosetta's low-resolution energy function together with an agreement-to-density score. Finally, we optimize sidechain rotamers and minimize all backbone and sidechain torsions using Rosetta's high-resolution potential, also augmented with this agreement-to-density score. We iterate over these final three steps until the lowest-energy models converge, at each iteration enriching our population for those models with both favorable Rosetta energy as well as good fit to density.
Figure 2
Figure 2
Comparative modeling into density on synthetic 10Å cryoEM maps for 1c2r (left) and 1cid (right). Three hundred homology models were constructed using Moulder. From these models, the best twenty were selected using fit-to-density score; these twenty were then further refined using the protocol outlined in Figure 1. The best Moulder structure is shown in red, while the crystal structure is shown is blue. The lowest-energy Rosetta model is in green.
Figure 3
Figure 3
A comparison of the starting homology model (red), the crystal structure (blue), and the model refined into density (green) for the upper domain of RDV P8 [1uf2, residues 173-292], docked into a 6.8Å cryoEM density map. The predicted model was built using a homology model from bluetongue virus [1bvp], aligned with mGenThreader, which was then iteratively refined using the method from Figure 1. The model has a Cα RMSd of 3.7Å, compared to 5.6Å in Rosetta's lowest-energy threaded model.
Figure 4
Figure 4
The hand annotated Cα trace of the equatorial domain of GroEL (red), the model refined into density (green), and the docked crystal structure [1oel, residues 2-136,410-525] (blue) in the 4.2Å cryoEM density. The model has a Cα RMSd of 3.4Å, compared to 3.6Å in the initial trace; however, the error in the core helices is much lower in the predicted model than in the original trace, 2.23 versus 3.41Å. (inset-upper) The lowest-energy refined models converge on near-native core packing. (inset-right) An error in the hand-traced model is corrected by the refinement protocol. The handtraced model (upper) does not have the crystal structure's (center) β pairing between residues 208-210 and 215-213. The refined model (lower) recovers this pairing.
Figure 5
Figure 5
Building a model from a Cα trace. The input trace is segmented into individual secondary structure elements. For each of these segments, a set of fragments is chosen based on both sequence similarity to the target as well as low Cα RMS to the target trace (thin black lines). Then these fragments are perturbed in a Monte Carlo simulation. Harmonic constraints on the original Cα positions from the input trace keep the model from deviating too far. The lowest energy model from each trajectory is chosen and loops are rebuilt using cyclic coordinate descent. Finally, each model is docked into the density and passed through the iterative refinement into density protocol (of Figure 1).
Figure 6
Figure 6
The starting model – a hand annotated Cα helix-only trace – of the lower domain of RDV P8 (red), the crystal structure [1uf2, residues 1-172,293-421] (blue), and the lowest-energy model refined into density (green), in 6.8Å cryoEM density data. The refined model has an overall Cα RMSd of 4.5Å from native, and an RMSd of 2.7Å in the 10 core helices. The initial Cα trace has an RMSd of 4.7Å over these same helices. (inset) Rosetta properly shifts a helix by two residues.
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References

    1. Jiang W, Baker ML, Ludtke SJ, Chiu W. Bridging the information gap: Computational tools for intermediate resolution structure interpretation. J Mol Bio. 2001;308:1033–1044. - PubMed
    1. Cowtan K. Modified phased translation functions and their application to molecular fragment location. Acta Cryst D. 1998;54:750–756. - PubMed
    1. Abeysinghe S, Ju T, Baker ML, Chiu W. Shape modeling and matching in identifying 3D protein structures. Computer-Aided Design. 2008;40:708–720.
    1. Topf M, Baker ML, Marti-Renoma MA, Chiu W, Sali A. Refinement of Protein Structures by Iterative Comparative Modeling and CryoEM Density Fitting. J Mol Bio. 2006;357:1655–1668. - PubMed
    1. Trabuco LG, Villa E, Mitra K, Frank J, Schulten K. Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics. Structure. 2008;16:673–683. - PMC - PubMed

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