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Bayesian Weighing of Electron Cryo-Microscopy Data for Integrative Structural Modeling.


ABSTRACT: Cryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternative structural models of a macromolecular system based on their consistency with a cryo-EM density map as well as other experimental and prior information. The accuracy of this approach is benchmarked using complexes of known structure and illustrated in three applications: the structural determination of the GroEL/GroES, RNA polymerase II, and exosome complexes. The approach is implemented in the open-source Integrative Modeling Platform (http://integrativemodeling.org), thus enabling integrative structure determination by combining cryo-EM data with other sources of information.

SUBMITTER: Bonomi M 

PROVIDER: S-EPMC6779587 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Bayesian Weighing of Electron Cryo-Microscopy Data for Integrative Structural Modeling.

Bonomi Massimiliano M   Hanot Samuel S   Greenberg Charles H CH   Sali Andrej A   Nilges Michael M   Vendruscolo Michele M   Pellarin Riccardo R  

Structure (London, England : 1993) 20181101 1


Cryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternativ  ...[more]

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