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UCSF ChimeraX: Tools for structure building and analysis

Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3–4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine‐learni...

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Autores principales: Meng, Elaine C., Goddard, Thomas D., Pettersen, Eric F., Couch, Greg S., Pearson, Zach J., Morris, John H., Ferrin, Thomas E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10588335/
https://www.ncbi.nlm.nih.gov/pubmed/37774136
http://dx.doi.org/10.1002/pro.4792
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author Meng, Elaine C.
Goddard, Thomas D.
Pettersen, Eric F.
Couch, Greg S.
Pearson, Zach J.
Morris, John H.
Ferrin, Thomas E.
author_facet Meng, Elaine C.
Goddard, Thomas D.
Pettersen, Eric F.
Couch, Greg S.
Pearson, Zach J.
Morris, John H.
Ferrin, Thomas E.
author_sort Meng, Elaine C.
collection PubMed
description Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3–4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine‐learning structure predictions, provide likelihood‐based fitting in maps, and compute per‐residue scores to identify modeling errors. Additional model‐building tools assist analysis of mutations, post‐translational modifications, and interactions with ligands. We present the latest ChimeraX model‐building capabilities, including several community‐developed extensions. ChimeraX is available free of charge for noncommercial use at https://www.rbvi.ucsf.edu/chimerax.
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spelling pubmed-105883352023-11-01 UCSF ChimeraX: Tools for structure building and analysis Meng, Elaine C. Goddard, Thomas D. Pettersen, Eric F. Couch, Greg S. Pearson, Zach J. Morris, John H. Ferrin, Thomas E. Protein Sci Tools for Protein Science Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3–4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine‐learning structure predictions, provide likelihood‐based fitting in maps, and compute per‐residue scores to identify modeling errors. Additional model‐building tools assist analysis of mutations, post‐translational modifications, and interactions with ligands. We present the latest ChimeraX model‐building capabilities, including several community‐developed extensions. ChimeraX is available free of charge for noncommercial use at https://www.rbvi.ucsf.edu/chimerax. John Wiley & Sons, Inc. 2023-11-01 /pmc/articles/PMC10588335/ /pubmed/37774136 http://dx.doi.org/10.1002/pro.4792 Text en © 2023 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Tools for Protein Science
Meng, Elaine C.
Goddard, Thomas D.
Pettersen, Eric F.
Couch, Greg S.
Pearson, Zach J.
Morris, John H.
Ferrin, Thomas E.
UCSF ChimeraX: Tools for structure building and analysis
title UCSF ChimeraX: Tools for structure building and analysis
title_full UCSF ChimeraX: Tools for structure building and analysis
title_fullStr UCSF ChimeraX: Tools for structure building and analysis
title_full_unstemmed UCSF ChimeraX: Tools for structure building and analysis
title_short UCSF ChimeraX: Tools for structure building and analysis
title_sort ucsf chimerax: tools for structure building and analysis
topic Tools for Protein Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10588335/
https://www.ncbi.nlm.nih.gov/pubmed/37774136
http://dx.doi.org/10.1002/pro.4792
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