| Literature DB >> 30393052 |
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.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