Bayesian weighing of electron cryo-microscopy data for integrative structural modeling (original) (raw)

New Results

, Samuel Hanot, Charles H. Greenberg, Andrej Sali, Michael Nilges, Michele Vendruscolo, Riccardo Pellarin

Abstract

Summary 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.

Highlights

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

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