Bioinformatics. 2019 Aug 26. pii: btz671.

Ramírez-Aportela E, Vilas J, Glukhova A, Melero R, Conesa P, Martínez M, Maluenda D, Mota J, Jiménez A, Vargas J, Marabini R, Sexton PM, Carazo JM, Oscar C, Sorzano S.

Abstract

MOTIVATION: Recent technological advances and computational developments have allowed the reconstruction of 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 modelling. 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: The source code (LocalDeblur) can be found at https://github.com/I2PC/scipion/blob/master/software/em/xmipp/ and can be run using Scipion (http://scipion.cnb.csic.es) (release numbers greater than or equal 1.2.1).

doi: 10.1093/bioinformatics/btz671.