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Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data
Molecular mass (MM) is one of the key structural parameters obtained by small-angle X-ray scattering (SAXS) of proteins in solution and is used to assess the sample quality, oligomeric composition and to guide subsequent structural modelling. Concentration-dependent assessment of MM relies on a numb...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940760/ https://www.ncbi.nlm.nih.gov/pubmed/29739979 http://dx.doi.org/10.1038/s41598-018-25355-2 |
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author | Hajizadeh, Nelly R. Franke, Daniel Jeffries, Cy M. Svergun, Dmitri I. |
author_facet | Hajizadeh, Nelly R. Franke, Daniel Jeffries, Cy M. Svergun, Dmitri I. |
author_sort | Hajizadeh, Nelly R. |
collection | PubMed |
description | Molecular mass (MM) is one of the key structural parameters obtained by small-angle X-ray scattering (SAXS) of proteins in solution and is used to assess the sample quality, oligomeric composition and to guide subsequent structural modelling. Concentration-dependent assessment of MM relies on a number of extra quantities (partial specific volume, calibrated intensity, accurate solute concentration) and often yields limited accuracy. Concentration-independent methods forgo these requirements being based on the relationship between structural parameters, scattering invariants and particle volume obtained directly from the data. Using a comparative analysis on 165,982 unique scattering profiles calculated from high-resolution protein structures, the performance of multiple concentration-independent MM determination methods was assessed. A Bayesian inference approach was developed affording an accuracy above that of the individual methods, and reports MM estimates together with a credibility interval. This Bayesian approach can be used in combination with concentration-dependent MM methods to further validate the MM of proteins in solution, or as a reliable stand-alone tool in instances where an accurate concentration estimate is not available. |
format | Online Article Text |
id | pubmed-5940760 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-59407602018-05-11 Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data Hajizadeh, Nelly R. Franke, Daniel Jeffries, Cy M. Svergun, Dmitri I. Sci Rep Article Molecular mass (MM) is one of the key structural parameters obtained by small-angle X-ray scattering (SAXS) of proteins in solution and is used to assess the sample quality, oligomeric composition and to guide subsequent structural modelling. Concentration-dependent assessment of MM relies on a number of extra quantities (partial specific volume, calibrated intensity, accurate solute concentration) and often yields limited accuracy. Concentration-independent methods forgo these requirements being based on the relationship between structural parameters, scattering invariants and particle volume obtained directly from the data. Using a comparative analysis on 165,982 unique scattering profiles calculated from high-resolution protein structures, the performance of multiple concentration-independent MM determination methods was assessed. A Bayesian inference approach was developed affording an accuracy above that of the individual methods, and reports MM estimates together with a credibility interval. This Bayesian approach can be used in combination with concentration-dependent MM methods to further validate the MM of proteins in solution, or as a reliable stand-alone tool in instances where an accurate concentration estimate is not available. Nature Publishing Group UK 2018-05-08 /pmc/articles/PMC5940760/ /pubmed/29739979 http://dx.doi.org/10.1038/s41598-018-25355-2 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Hajizadeh, Nelly R. Franke, Daniel Jeffries, Cy M. Svergun, Dmitri I. Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data |
title | Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data |
title_full | Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data |
title_fullStr | Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data |
title_full_unstemmed | Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data |
title_short | Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data |
title_sort | consensus bayesian assessment of protein molecular mass from solution x-ray scattering data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940760/ https://www.ncbi.nlm.nih.gov/pubmed/29739979 http://dx.doi.org/10.1038/s41598-018-25355-2 |
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