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bioRxiv · 10.1101/113951

Multi-scale Bayesian modeling of cryo-electron microscopy density maps

Hanot, S.·Bonomi, M.·Greenberg, C. H.·Sali, A.·Nilges, M.·Vendruscolo, M.·Pellarin, R.
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Abstract

SummaryCryo-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.\n\nHighlightsO_LIWe present a modeling approach to integrate cryo-EM data with other sources of information\nC_LIO_LIWe benchmark our approach using synthetic data on 21 complexes of known structure\nC_LIO_LIWe apply our approach to the GroEL/GroES, RNA polymerase II, and exosome complexes\nC_LI

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Hanot, S., Bonomi, M., Greenberg, C. H., Sali, A., Nilges, M., Vendruscolo, M., Pellarin, R.. 2017-03-04. Multi-scale Bayesian modeling of cryo-electron microscopy density maps. https://doi.org/10.1101/113951

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