Bayesian analysis of static light scattering data for globular proteins.

Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that...

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Autores principales:	Fan Yin, Domarin Khago, Rachel W Martin, Carter T Butts
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2275c92744e641fba8f0122512179742
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spelling	oai:doaj.org-article:2275c92744e641fba8f01225121797422021-12-02T20:19:14ZBayesian analysis of static light scattering data for globular proteins.1932-620310.1371/journal.pone.0258429https://doaj.org/article/2275c92744e641fba8f01225121797422021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258429https://doaj.org/toc/1932-6203Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactions between particles, and hence is related to aggregation propensity, a property of considerable scientific and practical interest. Estimating the second virial coefficient from experimental data is challenging due both to the degree of precision required and the complexity of the error structure involved. In contrast to conventional approaches based on heuristic ordinary least squares estimates, Bayesian inference for the second virial coefficient allows explicit modeling of error processes, incorporation of prior information, and the ability to directly test competing physical models. Here, we introduce a fully Bayesian model for static light scattering experiments on small-particle systems, with joint inference for concentration, index of refraction, oligomer size, and the second virial coefficient. We apply our proposed model to study the aggregation behavior of hen egg-white lysozyme and human γS-crystallin using in-house experimental data. Based on these observations, we also perform a simulation study on the primary drivers of uncertainty in this family of experiments, showing in particular the potential for improved monitoring and control of concentration to aid inference.Fan YinDomarin KhagoRachel W MartinCarter T ButtsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0258429 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Fan Yin Domarin Khago Rachel W Martin Carter T Butts Bayesian analysis of static light scattering data for globular proteins.
description	Static light scattering is a popular physical chemistry technique that enables calculation of physical attributes such as the radius of gyration and the second virial coefficient for a macromolecule (e.g., a polymer or a protein) in solution. The second virial coefficient is a physical quantity that characterizes the magnitude and sign of pairwise interactions between particles, and hence is related to aggregation propensity, a property of considerable scientific and practical interest. Estimating the second virial coefficient from experimental data is challenging due both to the degree of precision required and the complexity of the error structure involved. In contrast to conventional approaches based on heuristic ordinary least squares estimates, Bayesian inference for the second virial coefficient allows explicit modeling of error processes, incorporation of prior information, and the ability to directly test competing physical models. Here, we introduce a fully Bayesian model for static light scattering experiments on small-particle systems, with joint inference for concentration, index of refraction, oligomer size, and the second virial coefficient. We apply our proposed model to study the aggregation behavior of hen egg-white lysozyme and human γS-crystallin using in-house experimental data. Based on these observations, we also perform a simulation study on the primary drivers of uncertainty in this family of experiments, showing in particular the potential for improved monitoring and control of concentration to aid inference.
format	article
author	Fan Yin Domarin Khago Rachel W Martin Carter T Butts
author_facet	Fan Yin Domarin Khago Rachel W Martin Carter T Butts
author_sort	Fan Yin
title	Bayesian analysis of static light scattering data for globular proteins.
title_short	Bayesian analysis of static light scattering data for globular proteins.
title_full	Bayesian analysis of static light scattering data for globular proteins.
title_fullStr	Bayesian analysis of static light scattering data for globular proteins.
title_full_unstemmed	Bayesian analysis of static light scattering data for globular proteins.
title_sort	bayesian analysis of static light scattering data for globular proteins.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/2275c92744e641fba8f0122512179742
work_keys_str_mv	AT fanyin bayesiananalysisofstaticlightscatteringdataforglobularproteins AT domarinkhago bayesiananalysisofstaticlightscatteringdataforglobularproteins AT rachelwmartin bayesiananalysisofstaticlightscatteringdataforglobularproteins AT cartertbutts bayesiananalysisofstaticlightscatteringdataforglobularproteins
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Bayesian analysis of static light scattering data for globular proteins.

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