Selected article for: "local resolution and non uniform refinement"

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_35
    Snippet: Non-uniform refinement appears to improve 3D reconstruction by improving particle image alignments. The STRA6-CaM particle is encased in a lipid nanodisc that has significant mass relative to the protein itself. Also, the CaM subunits are not completely rigid. The presence of this substantial disordered density breaks the assumptions behind uniform refinement. Noise is permitted to iteratively build up within the lipid nanodisc and flexible regio.....
    Document: Non-uniform refinement appears to improve 3D reconstruction by improving particle image alignments. The STRA6-CaM particle is encased in a lipid nanodisc that has significant mass relative to the protein itself. Also, the CaM subunits are not completely rigid. The presence of this substantial disordered density breaks the assumptions behind uniform refinement. Noise is permitted to iteratively build up within the lipid nanodisc and flexible regions, while the core protein density is over-regularized and information useful for alignments is lost. In non-uniform refinement, the structure is optimally regular-8 . 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 It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the .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 3 : Results of uniform and non-uniform refinement from 28,848 particle images of STRA6-CaM [4] in lipid nanodisc. A: FSC curves computed with the same mask for both refinements. Numerical improvement from 4.0Å to 3.6Å reflects a spatially global improvement of signal. Improvement in some regions is even larger. B: Histograms of change in particle alignment pose and shift between uniform and non-uniform refinement. Optimal regularization in non-uniform refinement improves the ability to align particles over iterations. C: 3D density maps from uniform and non-uniform refinement are filtered using the corresponding FSC curves and sharpened with the same B-factor, −140Å 2 . No local filtering or sharpening is used, and thresholds are set to keep the enclosed volume constant. Map differences are due to algorithmic rather than visualization differences. Map color depicts local resolution (Blocres [2] ), on a single color scale. D: Individual α-helical segments from the non-uniform map (purple) resolve backbone and side-chains while the uniform map (grey) does not in most cases. The left-most α-helix is peripheral while the right-most is central.

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