RosettaES: a sampling strategy enabling automated interpretation of difficult cryo-EM maps

Nat Methods. 2017 Aug;14(8):797-800. doi: 10.1038/nmeth.4340. Epub 2017 Jun 19.


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-Å resolution. On a benchmark set of nine proteins, RosettaES was able to identify near-native conformations in 85% of segments. RosettaES was also used to determine models for three challenging macromolecular structures.

MeSH terms

  • Algorithms
  • Cryoelectron Microscopy / methods*
  • Data Interpretation, Statistical*
  • Image Enhancement / methods*
  • Imaging, Three-Dimensional / methods
  • Molecular Imaging / methods*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sample Size
  • Sensitivity and Specificity
  • Software
  • Specimen Handling / methods*