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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Published in | Protein science Vol. 32; no. 11; pp. e4792 - n/a |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Hoboken, USA
John Wiley & Sons, Inc
01.11.2023
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | 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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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Review Editor: Nir Ben‐Tal |
ISSN: | 0961-8368 1469-896X 1469-896X |
DOI: | 10.1002/pro.4792 |