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FEM: feature-enhanced map.

Afonine PV, Moriarty NW, Mustyakimov M, Sobolev OV, Terwilliger TC, Turk D, Urzhumtsev A, Adams PD - Acta Crystallogr. D Biol. Crystallogr. (2015)

Bottom Line: This is followed by restricting the map to regions with convincing density and the application of sharpening.The final map is then created by combining a series of histogram-equalized intermediate maps.In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel σA-weighted map.

View Article: PubMed Central - HTML - PubMed

Affiliation: Physical Biosciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, MS64R0121, Berkeley, CA 94720, USA.

ABSTRACT
A method is presented that modifies a 2mFobs - DFmodel σA-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel σA-weighted map.

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Distribution of r.m.s. deviations between real-space refined models and the best available model: refinements against FEM (blue) and against the map from (1) (red). Clearly, the majority of structures refined closer to the true structure when the FEM was used as a target map.
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fig26: Distribution of r.m.s. deviations between real-space refined models and the best available model: refinements against FEM (blue) and against the map from (1) (red). Clearly, the majority of structures refined closer to the true structure when the FEM was used as a target map.

Mentions: To further illustrate the FEM procedure, we performed the following test. We selected PDB entry 3i9q (data resolution 1.45 Å), which we re-refined using phenix.refine (Afonine et al., 2012 ▶). Using this model, we calculated two maps: the FEM and the usual map from (1) (Figs. 24 ▶a and 24 ▶b). Since we wanted to compare the original σA map (Read, 1986 ▶) with the FEM, no modeling of missing reflections, anisotropy correction or sharpening was performed. What is remarkable about this structure is that the map from (1) is outstandingly poor, perhaps owing to poor completeness in the low-resolution zone (50% completeness in the 17.49–6.58 Å zone). We then removed everything but the macromolecule from the model and subjected this model to 1000 independent molecular-dynamics (MD) simulation runs using phenix.dynamics, with each run continuing until the root-mean-square deviation (r.m.s.d.) between the starting and current models exceeded 3 Å. This generated a diverse ensemble of 1000 structures as shown in Fig. 25 ▶. Next, each model from the ensemble was subjected to ten macrocycles of real-space refinement using phenix.real_space_refine (Afonine, Headd et al., 2013 ▶) against the FEM and the map from (1) independently. Each refinement macrocycle included model morphing (Terwilliger et al., 2012 ▶), simulated annealing with a slow-cooling protocol starting from 5000 K and local and overall gradient-driven minimization (Afonine et al., 2012 ▶). The refinement success was quantified by calculation of the r.m.s. deviation between the unperturbed model (before MD) that we consider to be the best available model and the model after real-space refinement. Fig. 26 ▶ shows a histogram of r.m.s. deviations for the refinement outcomes against the FEM and the map from (1). Clearly, in a majority of cases refinement against a feature-enhanced map resulted in refined models that were significantly closer to the true structure than those refined against a standard map.


FEM: feature-enhanced map.

Afonine PV, Moriarty NW, Mustyakimov M, Sobolev OV, Terwilliger TC, Turk D, Urzhumtsev A, Adams PD - Acta Crystallogr. D Biol. Crystallogr. (2015)

Distribution of r.m.s. deviations between real-space refined models and the best available model: refinements against FEM (blue) and against the map from (1) (red). Clearly, the majority of structures refined closer to the true structure when the FEM was used as a target map.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4356370&req=5

fig26: Distribution of r.m.s. deviations between real-space refined models and the best available model: refinements against FEM (blue) and against the map from (1) (red). Clearly, the majority of structures refined closer to the true structure when the FEM was used as a target map.
Mentions: To further illustrate the FEM procedure, we performed the following test. We selected PDB entry 3i9q (data resolution 1.45 Å), which we re-refined using phenix.refine (Afonine et al., 2012 ▶). Using this model, we calculated two maps: the FEM and the usual map from (1) (Figs. 24 ▶a and 24 ▶b). Since we wanted to compare the original σA map (Read, 1986 ▶) with the FEM, no modeling of missing reflections, anisotropy correction or sharpening was performed. What is remarkable about this structure is that the map from (1) is outstandingly poor, perhaps owing to poor completeness in the low-resolution zone (50% completeness in the 17.49–6.58 Å zone). We then removed everything but the macromolecule from the model and subjected this model to 1000 independent molecular-dynamics (MD) simulation runs using phenix.dynamics, with each run continuing until the root-mean-square deviation (r.m.s.d.) between the starting and current models exceeded 3 Å. This generated a diverse ensemble of 1000 structures as shown in Fig. 25 ▶. Next, each model from the ensemble was subjected to ten macrocycles of real-space refinement using phenix.real_space_refine (Afonine, Headd et al., 2013 ▶) against the FEM and the map from (1) independently. Each refinement macrocycle included model morphing (Terwilliger et al., 2012 ▶), simulated annealing with a slow-cooling protocol starting from 5000 K and local and overall gradient-driven minimization (Afonine et al., 2012 ▶). The refinement success was quantified by calculation of the r.m.s. deviation between the unperturbed model (before MD) that we consider to be the best available model and the model after real-space refinement. Fig. 26 ▶ shows a histogram of r.m.s. deviations for the refinement outcomes against the FEM and the map from (1). Clearly, in a majority of cases refinement against a feature-enhanced map resulted in refined models that were significantly closer to the true structure than those refined against a standard map.

Bottom Line: This is followed by restricting the map to regions with convincing density and the application of sharpening.The final map is then created by combining a series of histogram-equalized intermediate maps.In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel σA-weighted map.

View Article: PubMed Central - HTML - PubMed

Affiliation: Physical Biosciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, MS64R0121, Berkeley, CA 94720, USA.

ABSTRACT
A method is presented that modifies a 2mFobs - DFmodel σA-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel σA-weighted map.

Show MeSH