Selected article for: "detergent micelle and large detergent micelle"

Author: Ali Punjani; Haowei Zhang; David J. Fleet
Title: Non-uniform refinement: Adaptive regularization improves single particle cryo-EM reconstruction
  • Document date: 2019_12_16
  • ID: bqwmx5dy_44
    Snippet: The next example is another small membrane protein with no soluble domain. This particle is C3 symmetric with a molecular weight of 90kDa, but unlike the PfCRT, does not have any Fabs bound. The protein mass is surrounded by a large detergent micelle, making alignments difficult. It is therefore a good test case for non-uniform alignment. The dataset, courtesy of Oliver Clarke [6] , contains 42,740 particles at a pixel size of 1.05Ã…. It is part .....
    Document: The next example is another small membrane protein with no soluble domain. This particle is C3 symmetric with a molecular weight of 90kDa, but unlike the PfCRT, does not have any Fabs bound. The protein mass is surrounded by a large detergent micelle, making alignments difficult. It is therefore a good test case for non-uniform alignment. The dataset, courtesy of Oliver Clarke [6] , contains 42,740 particles at a pixel size of 1.05Å. It is part of an on-going study that is not yet published, so statistics and figures are shown here with permission, but we do not name the protein or show the entire 3D map. Figure 5A shows FSC curves from uniform and non-uniform refinement. The overall global resolution of the map improves from 3.9Å to 3.6Å when using non-uniform refinement, but as with the STRA6-CaM . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2019.12.15.877092 doi: bioRxiv preprint Figure 4 : Results of uniform and non-uniform refinement from 16,905 particle images of PfCRT [15] in lipid nanodisc with a single Fab bound. A: FSC curves computed with the same mask show numerical improvement from 6.9Å to 3.6Å, a dramatic global improvement of signal. B: Histograms of change in particle alignments between uniform and non-uniform refinement. Optimal non-uniform regularization yields improved alignments through multiple iterations. Note that the x-axis limits are larger than in other figures. C: 3D density maps from uniform and non-uniform refinement, both filtered using the corresponding FSC curve, and sharpened with the same B-factor of −100Å 2 . No local filtering or sharpening is used, and thresholds are set to keep the enclosed volume constant. Density differences are thus due to algorithmic rather than visualization differences. Maps are colored by local resolution from Blocres [2] , all on the same color scale. D: Individual α-helical segments from the non-uniform map (purple) resolve backbone and side-chains while α-helices are barely resolved in uniform (grey) map density and β-strands are not separated.

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