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Cryo-EM has revealed the structures of many challenging yet exciting macromolecular assemblies at near-atomic resolution (3-4.5Å), providing biological phenomena with molecular descriptions. However, at these resolutions, accurately positioning individual atoms remains challenging and error-prone. Manually refining thousands of amino acids - typical in a macromolecular assembly - is tedious and time-consuming. We present an automated method that can improve the atomic details in models that are manually built in near-atomic-resolution cryo-EM maps. Applying the method to three systems recently solved by cryo-EM, we are able to improve model geometry while maintaining the fit-to-density. Backbone placement errors are automatically detected and corrected, and the refinement shows a large radius of convergence. The results demonstrate that the method is amenable to structures with symmetry, of very large size, and containing RNA as well as covalently bound ligands. The method should streamline the cryo-EM structure determination process, providing accurate and unbiased atomic structure interpretation of such maps.
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Wang et al. (Mon,) studied this question.
synapsesocial.com/papers/6a0a5004a9576e6c7db4ea84 — DOI: https://doi.org/10.7554/elife.17219
Ray Yu‐Ruei Wang
University of California, San Francisco
Yifan Song
Benjamin A. Barad
Oregon Health & Science University
eLife
University of Washington
University of California, San Francisco
Seattle University
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