Automatic local resolution-based sharpening of cryo-EM maps

Abstract

Motivation Recent technological advances and computational developments have allowed the reconstruction of Cryo-Electron Microscopy (cryo-EM) maps at near-atomic resolution. On a typical workflow and once the cryo-EM map has been calculated, a sharpening process is usually performed to enhance map visualization, a step that has proven very important in the key task of structural modeling. However, sharpening approaches, in general, neglects the local quality of the map, which is clearly suboptimal. Results Here, a new method for local sharpening of cryo-EM density maps is proposed. The algorithm, named LocalDeblur, is based on a local resolution-guided Wiener restoration approach of the original map. The method is fully automatic and, from the user point of view, virtually parameter-free, without requiring either a starting model or introducing any additional structure factor correction or boosting. Results clearly show a significant impact on map interpretability, greatly helping modeling. In particular, this local sharpening approach is especially suitable for maps that present a broad resolution range, as is often the case for membrane proteins or macromolecules with high flexibility, all of them otherwise very suitable and interesting specimens for cryo-EM. To our knowledge, and leaving out the use of local filters, it represents the first application of local resolution in cryo-EM sharpening. Availability and implementation The source code (LocalDeblur) can be found at https://github.com/I2PC/xmipp and can be run using Scipion (http://scipion.cnb.csic.es) (release numbers greater than or equal 1.2.1). Supplementary information Supplementary data are available at Bioinformatics online.

Mitigating Local Over-fitting During Single Particle Reconstruction with SIDESPLITTER

“…where signal becomes indistinguishable from noise (Stewart & Grigorieff, 2004). Several methods for evaluation and treatment of local resolution in cryo-EM reconstruction have previously been proposed (Stewart & Grigorieff, 2004;Cardone et al, 2013;Chen et al, 2013;Kucukelbir et al, 2014;Vilas et al, 2018a;Ramírez-Aportela et al, 2018), however none provide a way to minimise over-fitting during the reconstruction process.…”

Structures of virus-like capsids formed by the Drosophila neuronal Arc proteins

“…E) The Ty3 three-fold CACTD interface also contains a three-fold symmetric histidine cluster (H170) positioned at the outer edge of the pore. (Kucukelbir et al, 2014) and LocalDeblur (Ramírez-Aportela et al, 2018).…”

“…For all maps, local resolutions were calculated using ResMap (Kucukelbir et al, 2014) (Fig. S3) and the maps were locally sharpened using LocalDeblur (Ramírez-Aportela et al, 2018).…”

“…dArc1 and dArc2 density maps colored according to local resolution. Local resolutions were calculated using ResMap(Kucukelbir et al, 2014) and subsequently used for local sharpening of the maps using LocalDeblur(Ramírez-Aportela et al, 2018). A) The unsharpened and sharpened maps of dArc1 capsid (top) and locally-refined capsomeres (bottom) colored from high (blue) to low (red) local resolution.…”

FSC-Q: A CryoEM map-to-atomic model quality validation based on the local Fourier Shell Correlation

“…In our method, this is due to the mask used in calculating the local resolution. For simplicity, we restrict ourselves to those cases in which sharpening is done globally, rather than on more precise local methods (such as Ramírez-Aportela et al (Ramirez-Aportela et al, 2020), that, however, would complicate the presentation of these results significantly.…”