Figure 2

Analysis of typical FRET data recovers true values of K _d and E _fr . A typical three-cube FRET experiment is simulated from three virtual cells, each containing the indicated concentrations of donor- and acceptor- tagged proteins (A, left). The data is summarized in bar graphs with mean ± SD (A, right). Ten measurements/channel are made for each cell with 5% added measurement noise. For other parameters, see Methods. The data was analyzed in two ways to find the values of K _d and E _fr consistent with the data. We first calculated the energy for an array of parameter values; as the energy contour plot shows (B), the energy was minimal near the true parameter values. We also used a Monte Carlo algorithm to explore K _d -E _fr space, running 3 biased random walks starting from different initial positions (white *) and running for 12,000 steps. The paths of the walks (for clarity only the first 2,000 steps are shown) are superimposed on the contour plot (B) and all three converged to a region around the true value which coincides with the energy minimum. Histograms of the locations visited by all three walks, including only post-convergence steps (11,000 steps are included from each walk) act as approximate posterior distributions for K _d and E _fr (C). The dashed red lines indicate the true values of K _d and E _fr used to generate the data.