Abstract
Cryo-electron microscopy produces 3D density maps of molecular machines, which consist of various molecular components such as proteins and RNA. Segmentation of individual components in such maps is a challenging task, and is mostly accomplished interactively. We present an approach based on the immersive watershed method and grouping of the resulting regions using progressively smoothed maps. The method requires only three parameters: the segmentation threshold, a smoothing step size, and the number of smoothing steps. We first apply the method to maps generated from molecular structures and use a quantitative metric to measure the segmentation accuracy. The method does not attain perfect accuracy, however it produces single or small groups of regions that roughly match individual proteins or subunits. We also present two methods for fitting of structures into density maps, based on aligning the structures with single regions or small groups of regions. The first method aligns centers and principal axes, whereas the second aligns centers and then rotates the structure to find the best fit. We describe both interactive and automated ways of using these two methods. Finally, we show segmentation and fitting results for several experimentally-obtained density maps.
MeSH Terms
Algorithms
Bacteriophage lambda/chemistry,ultrastructure
Chaperonin 10/chemistry,ultrastructure
Chaperonin 60/chemistry,ultrastructure
Computer Simulation
Cryoelectron Microscopy/statistics & numerical data
Models, Molecular
Molecular Conformation
Protein Conformation
Protein Subunits
Reoviridae/chemistry,ultrastructure
Ribosomes/chemistry,ultrastructure
Static Electricity
Structural Homology, Protein
Chemicals
Chaperonin 10
Chaperonin 60
Protein Subunits
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Pintilie Grigore D
Electrical Engineering and Computer Science, MIT, Cambridge, MA 02139, USA. gdp@csail.mit.edu <gdp@csail.mit.edu>
Zhang Junjie
Goddard Thomas D
Chiu Wah
Gossard David C
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