Determining protein complex structures based on a Bayesian model of in vivo Forster resonance energy transfer (FRET) data.

ABSTRACT: The use of in vivo Förster resonance energy transfer (FRET) data to determine the molecular architecture of a protein complex in living cells is challenging due to data sparseness, sample heterogeneity, signal contributions from multiple donors and acceptors, unequal fluorophore brightness, photobleaching, flexibility of the linker connecting the fluorophore to the tagged protein, and spectral cross-talk. We addressed these challenges by using a Bayesian approach that produces the posterior probability of a model, given the input data. The posterior probability is defined as a function of the dependence of our FRET metric FRETR on a structure (forward model), a model of noise in the data, as well as prior information about the structure, relative populations of distinct states in the sampl

SUBMITTER: Bonomi M 

PROVIDER: S-EPMC4223474 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature