Model-independent decomposition of two-state data

Eric C. Landahl*, Sarah E. Rice

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Two-state models often provide a reasonable approximation of protein behaviors such as partner binding, folding, and conformational changes. Many different techniques have been developed to determine the population ratio between two states as a function of different experimental conditions. Data analysis is accomplished either by fitting individual measured spectra to a linear combination of known basis spectra or alternatively by decomposing the entire set of spectra into two components using a least-squares optimization of free parameters within an assumed population model. Here we demonstrate that it is possible to determine the population ratio in a two-state system directly from data without an a priori model for basis spectra or populations by applying physical constraints iteratively to a singular value decomposition of optical fluorescence, x-ray-scattering, and electron paramagnetic resonance data.

Original languageEnglish (US)
Article number062713
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume88
Issue number6
DOIs
StatePublished - Dec 16 2013

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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