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Fig. 3. Square displacement analysis of the different eYFP-H-Ras constructs. Cumulative probability, P(r², t_lag), plotted versus the square displacements, r². (A) Cumulative probability, P(r², 50 mseconds) distributions of the inactive mutant eYFP-H-Ras(N17) (red dots) and the active mutant eYFP-H-Ras(V12) (green squares). These distributions were fitted to the one-component model (Eqn 1) or two-component model (Eqn 2). (B,C) Show the distributions and the results of the fits to the one-component (dashed line) and two-component (solid line) model. (D) Cumulative probability, P(r², 60 mseconds) distributions of wild-type eYFP-H-Ras(wt) before (red triangles) and after 5 minutes insulin stimulation (green triangles). (E,F) The distributions and the results of the fits to the one-component (dashed line) and two-component (solid line) model. B,C,E and F clearly show that the two-component model describes the cumulative probability distributions significantly better than the one-component model. For all cumulative probability distributions of H-Ras that were obtained and analyzed in this study, the two-component model yielded significantly better fit results than the one-component model.

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