Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data
Abstract 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...
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doaj-64ea8341bdef4605ab3728253d908a362020-12-08T06:11:17ZengNature Publishing GroupScientific Reports2045-23222018-05-018111310.1038/s41598-018-25355-2Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering dataNelly R. Hajizadeh0Daniel Franke1Cy M. Jeffries2Dmitri I. Svergun3European Molecular Biology Laboratory (EMBL) Hamburg Outstation, DESYEuropean Molecular Biology Laboratory (EMBL) Hamburg Outstation, DESYEuropean Molecular Biology Laboratory (EMBL) Hamburg Outstation, DESYEuropean Molecular Biology Laboratory (EMBL) Hamburg Outstation, DESYAbstract 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.https://doi.org/10.1038/s41598-018-25355-2 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nelly R. Hajizadeh Daniel Franke Cy M. Jeffries Dmitri I. Svergun |
spellingShingle |
Nelly R. Hajizadeh Daniel Franke Cy M. Jeffries Dmitri I. Svergun Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data Scientific Reports |
author_facet |
Nelly R. Hajizadeh Daniel Franke Cy M. Jeffries Dmitri I. Svergun |
author_sort |
Nelly R. Hajizadeh |
title |
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_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_sort |
consensus bayesian assessment of protein molecular mass from solution x-ray scattering data |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2018-05-01 |
description |
Abstract 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. |
url |
https://doi.org/10.1038/s41598-018-25355-2 |
work_keys_str_mv |
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