A parametrically constrained optimization method for fitting sedimentation velocity experiments

Gary Gorbet; Taylor Devlin; Blanca I. Hernandez Uribe; Aysha K. Demeler; Zachary L. Lindsey; Suma Ganji; Sabrah Breton; Laura Weise-Cross; Eileen M. Lafer; Emre H. Brookes; Borries Demeler

doi:10.1016/j.bpj.2014.02.022

A parametrically constrained optimization method for fitting sedimentation velocity experiments

Gary Gorbet, Taylor Devlin, Blanca I. Hernandez Uribe, Aysha K. Demeler, Zachary L. Lindsey, Suma Ganji, Sabrah Breton, Laura Weise-Cross, Eileen M. Lafer, Emre H. Brookes, Borries Demeler

Chemistry

University of North Carolina at Chapel Hill

Research output: Contribution to journal › Article › peer-review

47 Scopus citations

Abstract

A method for fitting sedimentation velocity experiments using whole boundary Lamm equation solutions is presented. The method, termed parametrically constrained spectrum analysis (PCSA), provides an optimized approach for simultaneously modeling heterogeneity in size and anisotropy of macromolecular mixtures. The solutions produced by PCSA are particularly useful for modeling polymerizing systems, where a single-valued relationship exists between the molar mass of the growing polymer chain and its corresponding anisotropy. The PCSA uses functional constraints to identify this relationship, and unlike other multidimensional grid methods, assures that only a single molar mass can be associated with a given anisotropy measurement. A description of the PCSA algorithm is presented, as well as several experimental and simulated examples that illustrate its utility and capabilities. The performance advantages of the PCSA method in comparison to other methods are documented. The method has been added to the UltraScan-III software suite, which is available for free download from http://www.ultrascan.uthscsa.edu.

Original language	English
Pages (from-to)	1741-1750
Number of pages	10
Journal	Biophysical Journal
Volume	106
Issue number	8
DOIs	https://doi.org/10.1016/j.bpj.2014.02.022
State	Published - Apr 15 2014

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10.1016/j.bpj.2014.02.022

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title = "A parametrically constrained optimization method for fitting sedimentation velocity experiments",

abstract = "A method for fitting sedimentation velocity experiments using whole boundary Lamm equation solutions is presented. The method, termed parametrically constrained spectrum analysis (PCSA), provides an optimized approach for simultaneously modeling heterogeneity in size and anisotropy of macromolecular mixtures. The solutions produced by PCSA are particularly useful for modeling polymerizing systems, where a single-valued relationship exists between the molar mass of the growing polymer chain and its corresponding anisotropy. The PCSA uses functional constraints to identify this relationship, and unlike other multidimensional grid methods, assures that only a single molar mass can be associated with a given anisotropy measurement. A description of the PCSA algorithm is presented, as well as several experimental and simulated examples that illustrate its utility and capabilities. The performance advantages of the PCSA method in comparison to other methods are documented. The method has been added to the UltraScan-III software suite, which is available for free download from http://www.ultrascan.uthscsa.edu.",

author = "Gary Gorbet and Taylor Devlin and {Hernandez Uribe}, {Blanca I.} and Demeler, {Aysha K.} and Lindsey, {Zachary L.} and Suma Ganji and Sabrah Breton and Laura Weise-Cross and Lafer, {Eileen M.} and Brookes, {Emre H.} and Borries Demeler",

note = "Funding Information: This work was supported by grants No. NSF/DAC-1339649 and No. NSF/TG-MCB070038/39/40 (to B.D.) and grants No. NIH/K25GM090154 and No. NSF/OCI-1032742 (to E.B.). The clathrin experiments were supported by grant No. NIH/NS029051 (to E.M.L.). We are grateful to the trustees of the Max and Minnie Tomerlin Voelcker Fund for the financial support of the Voelcker Biomedical Research Academy scholars (T.D., B.H.U., and Z.L.) ",

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AU - Devlin, Taylor

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AU - Lindsey, Zachary L.

AU - Ganji, Suma

AU - Breton, Sabrah

AU - Weise-Cross, Laura

AU - Lafer, Eileen M.

AU - Brookes, Emre H.

AU - Demeler, Borries

N1 - Funding Information: This work was supported by grants No. NSF/DAC-1339649 and No. NSF/TG-MCB070038/39/40 (to B.D.) and grants No. NIH/K25GM090154 and No. NSF/OCI-1032742 (to E.B.). The clathrin experiments were supported by grant No. NIH/NS029051 (to E.M.L.). We are grateful to the trustees of the Max and Minnie Tomerlin Voelcker Fund for the financial support of the Voelcker Biomedical Research Academy scholars (T.D., B.H.U., and Z.L.)

PY - 2014/4/15

Y1 - 2014/4/15

N2 - A method for fitting sedimentation velocity experiments using whole boundary Lamm equation solutions is presented. The method, termed parametrically constrained spectrum analysis (PCSA), provides an optimized approach for simultaneously modeling heterogeneity in size and anisotropy of macromolecular mixtures. The solutions produced by PCSA are particularly useful for modeling polymerizing systems, where a single-valued relationship exists between the molar mass of the growing polymer chain and its corresponding anisotropy. The PCSA uses functional constraints to identify this relationship, and unlike other multidimensional grid methods, assures that only a single molar mass can be associated with a given anisotropy measurement. A description of the PCSA algorithm is presented, as well as several experimental and simulated examples that illustrate its utility and capabilities. The performance advantages of the PCSA method in comparison to other methods are documented. The method has been added to the UltraScan-III software suite, which is available for free download from http://www.ultrascan.uthscsa.edu.

AB - A method for fitting sedimentation velocity experiments using whole boundary Lamm equation solutions is presented. The method, termed parametrically constrained spectrum analysis (PCSA), provides an optimized approach for simultaneously modeling heterogeneity in size and anisotropy of macromolecular mixtures. The solutions produced by PCSA are particularly useful for modeling polymerizing systems, where a single-valued relationship exists between the molar mass of the growing polymer chain and its corresponding anisotropy. The PCSA uses functional constraints to identify this relationship, and unlike other multidimensional grid methods, assures that only a single molar mass can be associated with a given anisotropy measurement. A description of the PCSA algorithm is presented, as well as several experimental and simulated examples that illustrate its utility and capabilities. The performance advantages of the PCSA method in comparison to other methods are documented. The method has been added to the UltraScan-III software suite, which is available for free download from http://www.ultrascan.uthscsa.edu.

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A parametrically constrained optimization method for fitting sedimentation velocity experiments

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