Abstract

Density modification uses expectations about features of a map such as a flat solvent and expected distributions of density in the region of the macromolecule to improve individual Fourier terms representing the map. This process transfers information from one part of a map to another and can improve the accuracy ofa map. Here, the assumptions behind density modification for maps from electron cryomicroscopy are examined and a procedure is presented that allows the incorporation of model-based information. Density modification works best in cases where unfiltered, unmasked maps with clear boundaries between the macromolecule and solvent are visible, and where there is substantial noise in the map, both in the region of the macromolecule and the solvent. It also is most effective if the characteristics of the map are relatively constant within regions of the macromolecule and the solvent. Model-based information can be used to improve density modification, but model bias can in principle occur. Here, model bias is reduced by using ensemble models that allow an estimation of model uncertainty. A test of model bias is presented that suggests that even if the expected density in a region of a map is specified incorrectly by using an incorrect model, the incorrect expectations do not strongly affect the final map.

Highlights

  • Density modification can be a useful procedure for improving the accuracy of cryo-EM maps

  • It is carried out starting with two half-maps and produces a density-modified final map

  • Density modification requires expectations about the density in the true map and requires that errors in the starting map are local in Fourier space

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Summary

Introduction

Single-particle electron cryomicroscopy (cryo-EM) has recently become a powerful tool for high-resolution visualization of macromolecules. Three-dimensional single-particle cryo-EM maps are obtained by combining information from many images of a macromolecule in differing orientations (Penczek, 2010a; Scheres, 2012; Nogales, 2016; Marques et al, 2019). Using a set of such projections with sufficient coverage, the three-dimensional Fourier transform of the molecule can be sampled on a set of grid points with indices hkl that are very similar to crystallographic structure factors. This yields Fourier terms that can in turn be used to

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