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

Structure. 2019 Jan 2;27(1):175-188.e6. doi: 10.1016/j.str.2018.09.011. Epub 2018 Nov 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 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 (, thus enabling integrative structure determination by combining cryo-EM data with other sources of information.

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

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacterial Proteins / chemistry
  • Bayes Theorem
  • Chaperonin 10 / chemistry
  • Chaperonin 60 / chemistry
  • Cryoelectron Microscopy / methods*
  • Mass Spectrometry / methods
  • Molecular Dynamics Simulation*
  • RNA Polymerase II / chemistry


  • Bacterial Proteins
  • Chaperonin 10
  • Chaperonin 60
  • RNA Polymerase II