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Bayesian weighing of electron cryo-microscopy data for integrative structural modeling

By Massimiliano Bonomi, Samuel Hanot, Charles H Greenberg, Andrej Sali, Michael Nilges, Michele Vendruscolo, Riccardo Pellarin

Posted 04 Mar 2017
bioRxiv DOI: 10.1101/113951 (published DOI: 10.1016/j.str.2018.09.011)

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 and 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.

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