https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2023Punjani_3DFlex2023Punjani 3DFlex - Revision history2026-05-24T21:07:10ZRevision history for this page on the wikiMediaWiki 1.44.2https://3demmethods.i2pc.es/index.php?title=2023Punjani_3DFlex&diff=4443&oldid=prevWikiSysop: Created page with "== Citation == Punjani, Ali / Fleet, David J. 3DFlex: determining structure and motion of flexible proteins from cryo-EM. 2023. Nature Methods, Vol. 20, p. 860-870 == Abstr..."2023-08-28T06:35:44Z<p>Created page with "== Citation == Punjani, Ali / Fleet, David J. 3DFlex: determining structure and motion of flexible proteins from cryo-EM. 2023. Nature Methods, Vol. 20, p. 860-870 == Abstr..."</p>
<p><b>New page</b></p><div>== Citation ==<br />
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Punjani, Ali / Fleet, David J. 3DFlex: determining structure and motion of flexible proteins from cryo-EM. 2023. Nature Methods, Vol. 20, p. 860-870 <br />
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== Abstract ==<br />
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Modeling flexible macromolecules is one of the foremost challenges in<br />
single-particle cryogenic-electron microscopy (cryo-EM), with the potential<br />
to illuminate fundamental questions in structural biology. We introduce<br />
Three-Dimensional Flexible Refinement (3DFlex), a motion-based neural<br />
network model for continuous molecular heterogeneity for cryo-EM data.<br />
3DFlex exploits knowledge that conformational variability of a protein is<br />
often the result of physical processes that transport density over space and<br />
tend to preserve local geometry. From two-dimensional image data, 3DFlex<br />
enables the determination of high-resolution 3D density, and provides<br />
an explicit model of a flexible protein’s motion over its conformational<br />
landscape. Experimentally, for large molecular machines (tri-snRNP<br />
spliceosome complex, translocating ribosome) and small flexible proteins<br />
(TRPV1 ion channel, αVβ8 integrin, SARS-CoV-2 spike), 3DFlex learns<br />
nonrigid molecular motions while resolving details of moving secondary<br />
structure elements. 3DFlex can improve 3D density resolution beyond the<br />
limits of existing methods because particle images contribute coherent<br />
signal over the conformational landscape.<br />
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== Keywords ==<br />
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== Links ==<br />
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https://www.nature.com/articles/s41592-023-01853-8<br />
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== Related software ==<br />
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== Related methods ==<br />
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== Comments ==</div>WikiSysop