Literature DB >> 30393052

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

Massimiliano Bonomi1, Samuel Hanot2, Charles H Greenberg3, Andrej Sali3, Michael Nilges2, Michele Vendruscolo4, Riccardo Pellarin5.   

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.
Copyright © 2018. Published by Elsevier Ltd.

Entities:  

Keywords:  Gaussian mixture model; bayesian inference; cross-linking mass spectrometry; cryo-electron microscopy; data weighing; integrative structural modeling; macromolecular complexes; structural biology

Mesh:

Substances:

Year:  2018        PMID: 30393052      PMCID: PMC6779587          DOI: 10.1016/j.str.2018.09.011

Source DB:  PubMed          Journal:  Structure        ISSN: 0969-2126            Impact factor:   5.006


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