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Automatic local resolution-based sharpening of cryo-EM maps

Ramirez-Aportela, Erney; Luis Vilas, Jose; Glukhova, Alisa; Melero, Roberto; Conesa, Pablo; Martinez, Marta; Maluenda, David; Mota, Javier; Jimenez, Amaya; Vargas, Javier; Marabini, Roberto; Sexton, Patrick M.; Maria Carazo, Jose; Sorzano, Carlos Oscar S.

BIOINFORMATICS
2020
VL / 36 - BP / 765 - EP / 772
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.

AccesS level

Green published, Hybrid, Green submitted

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