Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement
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Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement. / DiMaio, Frank; Song, Yifan; Li, Xueming; Brunner, Matthias J; Xu, Chunfu; Conticello, Vincent; Egelman, Edward; Marlovits, Thomas C; Cheng, Yifan; Baker, David.
in: NAT METHODS, Jahrgang 12, Nr. 4, 04.2015, S. 361-5.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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TY - JOUR
T1 - Atomic-accuracy models from 4.5-Å cryo-electron microscopy data with density-guided iterative local refinement
AU - DiMaio, Frank
AU - Song, Yifan
AU - Li, Xueming
AU - Brunner, Matthias J
AU - Xu, Chunfu
AU - Conticello, Vincent
AU - Egelman, Edward
AU - Marlovits, Thomas C
AU - Cheng, Yifan
AU - Baker, David
PY - 2015/4
Y1 - 2015/4
N2 - We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-Å resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.
AB - We describe a general approach for refining protein structure models on the basis of cryo-electron microscopy maps with near-atomic resolution. The method integrates Monte Carlo sampling with local density-guided optimization, Rosetta all-atom refinement and real-space B-factor fitting. In tests on experimental maps of three different systems with 4.5-Å resolution or better, the method consistently produced models with atomic-level accuracy largely independently of starting-model quality, and it outperformed the molecular dynamics-based MDFF method. Cross-validated model quality statistics correlated with model accuracy over the three test systems.
KW - Chemistry, Physical
KW - Cryoelectron Microscopy
KW - Models, Molecular
KW - Monte Carlo Method
KW - Proteins
U2 - 10.1038/nmeth.3286
DO - 10.1038/nmeth.3286
M3 - SCORING: Journal article
C2 - 25707030
VL - 12
SP - 361
EP - 365
JO - NAT METHODS
JF - NAT METHODS
SN - 1548-7091
IS - 4
ER -