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Integrative structural modeling with small angle X-ray scattering profiles
Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS pr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427135/ https://www.ncbi.nlm.nih.gov/pubmed/22800408 http://dx.doi.org/10.1186/1472-6807-12-17 |
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author | Schneidman-Duhovny, Dina Kim, Seung Joong Sali, Andrej |
author_facet | Schneidman-Duhovny, Dina Kim, Seung Joong Sali, Andrej |
author_sort | Schneidman-Duhovny, Dina |
collection | PubMed |
description | Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types. |
format | Online Article Text |
id | pubmed-3427135 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-34271352012-08-27 Integrative structural modeling with small angle X-ray scattering profiles Schneidman-Duhovny, Dina Kim, Seung Joong Sali, Andrej BMC Struct Biol Review Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types. BioMed Central 2012-07-16 /pmc/articles/PMC3427135/ /pubmed/22800408 http://dx.doi.org/10.1186/1472-6807-12-17 Text en Copyright ©2012 Schneidman-Duhovny et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Schneidman-Duhovny, Dina Kim, Seung Joong Sali, Andrej Integrative structural modeling with small angle X-ray scattering profiles |
title | Integrative structural modeling with small angle X-ray scattering profiles |
title_full | Integrative structural modeling with small angle X-ray scattering profiles |
title_fullStr | Integrative structural modeling with small angle X-ray scattering profiles |
title_full_unstemmed | Integrative structural modeling with small angle X-ray scattering profiles |
title_short | Integrative structural modeling with small angle X-ray scattering profiles |
title_sort | integrative structural modeling with small angle x-ray scattering profiles |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3427135/ https://www.ncbi.nlm.nih.gov/pubmed/22800408 http://dx.doi.org/10.1186/1472-6807-12-17 |
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