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

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


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 languageEnglish (US)
Pages (from-to)1741-1750
Number of pages10
JournalBiophysical Journal
Issue number8
StatePublished - Apr 15 2014

ASJC Scopus subject areas

  • Biophysics


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