Model-independent decomposition of two-state data.
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.
Department of Physics, DePaul University, Chicago, Illinois 60614, USA.
Eric C
EC
Landahl
Department of Cell and Molecular Biology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, USA.
Sarah E
SE
Rice
D045304:Cytochromes c / Q000737:chemistry / Q000378:metabolism; D004578:Electron Spin Resonance Spectroscopy; D016547:Kinesins / Q000737:chemistry / Q000378:metabolism; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D053838:Scattering, Small Angle; D013050:Spectrometry, Fluorescence; D014364:Tryptophan / Q000737:chemistry; D014961:X-Ray Diffraction
D011506:Proteins; D014364:Tryptophan; D045304:Cytochromes c; D016547:Kinesins