Local computational methods to improve the interpretability and analysis of cryo-EM maps

Abstract Cryo-electron microscopy (cryo-EM) maps usually show heterogeneous distributions of B -factors and electron density occupancies are typically -factor sharpened to improve their contrast interpretability at high-resolutions. However, ‘over-sharpening’ due the application a single global can distort processed causing connected densities appear broken disconnected. This issue limits cryo-EM maps, i.e. ab initio modelling. In this work, we propose 1) approaches enhance high-resolution features while preventing map distortions 2) methods obtain local occupancy maps. These algorithms have as common link use spiral phase transformation called LocSpiral, LocBSharpen, LocBFactor LocOccupancy. Our results, which include improved recent SARS-CoV-2 structures, that our analysis obtained reconstructions.