Journal
NATURE METHODS
Volume 14, Issue 8, Pages 797-+Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/NMETH.4340
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Funding
- STF at the University of Washington
- National Institutes of Health (NIH) [GM120553, GM035269, T32GM008268]
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Accurate atomic modeling of macromolecular structures into cryo-electron microscopy (cryo-EM) maps is a major challenge, as the moderate resolution makes accurate placement of atoms difficult. We present Rosetta enumerative sampling (RosettaES), an automated tool that uses a fragment-based sampling strategy for de novo model completion of macromolecular structures from cryo-EM density maps at 3-5-angstrom resolution. On a benchmark set of nine proteins, RosettaESES was able to identify near-native conformations in 85% of segments. RosettaES was also used to determine models for three challenging macromolecular structures.
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