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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Autores principales:	Nelly R. Hajizadeh, Daniel Franke, Cy M. Jeffries, Dmitri I. Svergun
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/64ea8341bdef4605ab3728253d908a36
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spelling	oai:doaj.org-article:64ea8341bdef4605ab3728253d908a362021-12-02T16:07:52ZConsensus Bayesian assessment of protein molecular mass from solution X-ray scattering data10.1038/s41598-018-25355-22045-2322https://doaj.org/article/64ea8341bdef4605ab3728253d908a362018-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-25355-2https://doaj.org/toc/2045-2322Abstract 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.Nelly R. HajizadehDaniel FrankeCy M. JeffriesDmitri I. SvergunNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-13 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nelly R. Hajizadeh Daniel Franke Cy M. Jeffries Dmitri I. Svergun Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data
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.
format	article
author	Nelly R. Hajizadeh Daniel Franke Cy M. Jeffries Dmitri I. Svergun
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 Portfolio
publishDate	2018
url	https://doaj.org/article/64ea8341bdef4605ab3728253d908a36
work_keys_str_mv	AT nellyrhajizadeh consensusbayesianassessmentofproteinmolecularmassfromsolutionxrayscatteringdata AT danielfranke consensusbayesianassessmentofproteinmolecularmassfromsolutionxrayscatteringdata AT cymjeffries consensusbayesianassessmentofproteinmolecularmassfromsolutionxrayscatteringdata AT dmitriisvergun consensusbayesianassessmentofproteinmolecularmassfromsolutionxrayscatteringdata
_version_	1718384660211302400

Consensus Bayesian assessment of protein molecular mass from solution X-ray scattering data

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