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Super-resolution biomolecular crystallography with low-resolution data

X-ray diffraction plays a pivotal role in understanding of biological systems by revealing atomic structures of proteins, nucleic acids, and their complexes, with much recent interest in very large assemblies like the ribosome. Since crystals of such large assemblies often diffract weakly (resolutio...

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Autores principales: Schröder, Gunnar F., Levitt, Michael, Brunger, Axel T.
Formato: Texto
Lenguaje:English
Publicado: 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2859093/
https://www.ncbi.nlm.nih.gov/pubmed/20376006
http://dx.doi.org/10.1038/nature08892
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author Schröder, Gunnar F.
Levitt, Michael
Brunger, Axel T.
author_facet Schröder, Gunnar F.
Levitt, Michael
Brunger, Axel T.
author_sort Schröder, Gunnar F.
collection PubMed
description X-ray diffraction plays a pivotal role in understanding of biological systems by revealing atomic structures of proteins, nucleic acids, and their complexes, with much recent interest in very large assemblies like the ribosome. Since crystals of such large assemblies often diffract weakly (resolution worse than 4 Å), we need methods that work at such low resolution. In macromolecular assemblies, some of the components may be known at high resolution, while others are unknown: current refinement methods fail as they require a high-resolution starting structure for the entire complex1. Determining such complexes, which are often of key biological importance, should be possible in principle as the number of independent diffraction intensities at a resolution below 5 Å generally exceed the number of degrees of freedom. Here we introduce a new method that adds specific information from known homologous structures but allows global and local deformations of these homology models. Our approach uses the observation that local protein structure tends to be conserved as sequence and function evolve. Cross-validation with R(free) determines the optimum deformation and influence of the homology model. For test cases at 3.5 – 5 Å resolution with known structures at high resolution, our method gives significant improvements over conventional refinement in the model coordinate accuracy, the definition of secondary structure, and the quality of electron density maps. For re-refinements of a representative set of 19 low-resolution crystal structures from the PDB, we find similar improvements. Thus, a structure derived from low-resolution diffraction data can have quality similar to a high-resolution structure. Our method is applicable to studying weakly diffracting crystals using X-ray micro-diffraction2 as well as data from new X-ray light sources3. Use of homology information is not restricted to X-ray crystallography and cryo-electron microscopy: as optical imaging advances to sub-nanometer resolution4,5, it can use similar tools.
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spelling pubmed-28590932010-10-22 Super-resolution biomolecular crystallography with low-resolution data Schröder, Gunnar F. Levitt, Michael Brunger, Axel T. Nature Article X-ray diffraction plays a pivotal role in understanding of biological systems by revealing atomic structures of proteins, nucleic acids, and their complexes, with much recent interest in very large assemblies like the ribosome. Since crystals of such large assemblies often diffract weakly (resolution worse than 4 Å), we need methods that work at such low resolution. In macromolecular assemblies, some of the components may be known at high resolution, while others are unknown: current refinement methods fail as they require a high-resolution starting structure for the entire complex1. Determining such complexes, which are often of key biological importance, should be possible in principle as the number of independent diffraction intensities at a resolution below 5 Å generally exceed the number of degrees of freedom. Here we introduce a new method that adds specific information from known homologous structures but allows global and local deformations of these homology models. Our approach uses the observation that local protein structure tends to be conserved as sequence and function evolve. Cross-validation with R(free) determines the optimum deformation and influence of the homology model. For test cases at 3.5 – 5 Å resolution with known structures at high resolution, our method gives significant improvements over conventional refinement in the model coordinate accuracy, the definition of secondary structure, and the quality of electron density maps. For re-refinements of a representative set of 19 low-resolution crystal structures from the PDB, we find similar improvements. Thus, a structure derived from low-resolution diffraction data can have quality similar to a high-resolution structure. Our method is applicable to studying weakly diffracting crystals using X-ray micro-diffraction2 as well as data from new X-ray light sources3. Use of homology information is not restricted to X-ray crystallography and cryo-electron microscopy: as optical imaging advances to sub-nanometer resolution4,5, it can use similar tools. 2010-04-07 2010-04-22 /pmc/articles/PMC2859093/ /pubmed/20376006 http://dx.doi.org/10.1038/nature08892 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Schröder, Gunnar F.
Levitt, Michael
Brunger, Axel T.
Super-resolution biomolecular crystallography with low-resolution data
title Super-resolution biomolecular crystallography with low-resolution data
title_full Super-resolution biomolecular crystallography with low-resolution data
title_fullStr Super-resolution biomolecular crystallography with low-resolution data
title_full_unstemmed Super-resolution biomolecular crystallography with low-resolution data
title_short Super-resolution biomolecular crystallography with low-resolution data
title_sort super-resolution biomolecular crystallography with low-resolution data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2859093/
https://www.ncbi.nlm.nih.gov/pubmed/20376006
http://dx.doi.org/10.1038/nature08892
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