Integrating model simulation tools and cryo‐electron microscopy

The power of computer simulations, including machine‐learning, has become an inseparable part of scientific analysis of biological data. This has significantly impacted the field of cryogenic electron microscopy (cryo‐EM), which has grown dramatically since the “resolution‐revolution.” Many maps are...

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Published inWiley interdisciplinary reviews. Computational molecular science Vol. 13; no. 3
Main Authors Beton, Joseph George, Cragnolini, Tristan, Kaleel, Manaz, Mulvaney, Thomas, Sweeney, Aaron, Topf, Maya
Format Journal Article
LanguageEnglish
Published Hoboken, USA Wiley Periodicals, Inc 01.05.2023
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ISSN1759-0876
1759-0884
DOI10.1002/wcms.1642

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Abstract The power of computer simulations, including machine‐learning, has become an inseparable part of scientific analysis of biological data. This has significantly impacted the field of cryogenic electron microscopy (cryo‐EM), which has grown dramatically since the “resolution‐revolution.” Many maps are now solved at 3–4 Å or better resolution, although a significant proportion of maps deposited in the Electron Microscopy Data Bank are still at lower resolution, where the positions of atoms cannot be determined unambiguously. Additionally, cryo‐EM maps are often characterized by a varying local resolution, partly due to conformational heterogeneity of the imaged molecule. To address such problems, many computational methods have been developed for cryo‐EM map reconstruction and atomistic model building. Here, we review the development in algorithms and tools for building models in cryo‐EM maps at different resolutions. We describe methods for model building, including rigid and flexible fitting of known models, model validation, small‐molecule fitting, and model visualization. We provide examples of how these methods have been used to elucidate the structure and function of dynamic macromolecular machines. This article is categorized under: Structure and Mechanism > Molecular Structures Structure and Mechanism > Computational Biochemistry and Biophysics Software > Molecular Modeling Combining cryo‐EM data and molecular simulation to understand protein structure and dynamics.
AbstractList The power of computer simulations, including machine‐learning, has become an inseparable part of scientific analysis of biological data. This has significantly impacted the field of cryogenic electron microscopy (cryo‐EM), which has grown dramatically since the “resolution‐revolution.” Many maps are now solved at 3–4 Å or better resolution, although a significant proportion of maps deposited in the Electron Microscopy Data Bank are still at lower resolution, where the positions of atoms cannot be determined unambiguously. Additionally, cryo‐EM maps are often characterized by a varying local resolution, partly due to conformational heterogeneity of the imaged molecule. To address such problems, many computational methods have been developed for cryo‐EM map reconstruction and atomistic model building. Here, we review the development in algorithms and tools for building models in cryo‐EM maps at different resolutions. We describe methods for model building, including rigid and flexible fitting of known models, model validation, small‐molecule fitting, and model visualization. We provide examples of how these methods have been used to elucidate the structure and function of dynamic macromolecular machines. This article is categorized under: Structure and Mechanism > Molecular Structures Structure and Mechanism > Computational Biochemistry and Biophysics Software > Molecular Modeling Combining cryo‐EM data and molecular simulation to understand protein structure and dynamics.
Author Topf, Maya
Cragnolini, Tristan
Mulvaney, Thomas
Sweeney, Aaron
Beton, Joseph George
Kaleel, Manaz
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Snippet The power of computer simulations, including machine‐learning, has become an inseparable part of scientific analysis of biological data. This has significantly...
SourceID wiley
SourceType Publisher
SubjectTerms cryo‐EM
model validation
molecular modeling
molecular simulations
Title Integrating model simulation tools and cryo‐electron microscopy
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fwcms.1642
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