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


ABSTRACT: 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.

SUBMITTER: Frenz B 

PROVIDER: S-EPMC6009829 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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

Frenz Brandon B   Walls Alexandra C AC   Egelman Edward H EH   Veesler David D   DiMaio Frank F  

Nature methods 20170619 8


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 confor  ...[more]

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