Computational Detection of Protein Structure Components from 3-Dimensional Images Obtained from Cryo-Electron Microscopy
Location
Old Dominion University, Learning Commons at Perry Library, West Foyer
Start Date
4-8-2017 8:30 AM
End Date
4-8-2017 10:00 AM
Description
Cryo-electron microscopy is an emerging biophysical technique for structural determination of large protein complexes. While more atomic structures are being determined using this technique, it is still challenging to derive atomic structures from density maps produced at medium resolution when no suitable templates are available. A critical step in structure determination is how a protein chain threads through the 3- dimensional density map. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. The results show that our proposed method sensitively distinguishes lateral and longitudinal discrepancies between the two axes, which makes the method particularly suitable for the systematic investigation of cryoEM map-model pairs.
Presentation Type
Poster
Computational Detection of Protein Structure Components from 3-Dimensional Images Obtained from Cryo-Electron Microscopy
Old Dominion University, Learning Commons at Perry Library, West Foyer
Cryo-electron microscopy is an emerging biophysical technique for structural determination of large protein complexes. While more atomic structures are being determined using this technique, it is still challenging to derive atomic structures from density maps produced at medium resolution when no suitable templates are available. A critical step in structure determination is how a protein chain threads through the 3- dimensional density map. When the central axis of a helix is detectable in a cryo-EM density map, it is possible to quantify the agreement between this central axis and a central axis calculated from the atomic model or structure. We propose a novel arc-length association method to compare the two axes reliably. The results show that our proposed method sensitively distinguishes lateral and longitudinal discrepancies between the two axes, which makes the method particularly suitable for the systematic investigation of cryoEM map-model pairs.