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001     600655
005     20250724132655.0
024 7 _ |a 10.1002/wcms.1642
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100 1 _ |a Beton, Joseph
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245 _ _ |a Integrating model simulation tools and cryo‐electron microscopy
260 _ _ |a Malden, MA
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520 _ _ |a 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
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700 1 _ |a Cragnolini, Tristan
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700 1 _ |a Kaleel, Manaz
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700 1 _ |a Mulvaney, Thomas
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700 1 _ |a Sweeney, Aaron
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700 1 _ |a Topf, Maya
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773 _ _ |a 10.1002/wcms.1642
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