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An oft-used concept in modeling macromolecules is the free energy landscape,obtained by coarse-graining a vast number of microstates into a low-dimensionalmesh of mesostates. If the landscape contains two or more local minima(macrostates),one can compute global rate constants provided the dynamics ofthe dividing barrier regions are known. Here we compared experimental rateconstants between ordered states in a kinetic Ising model with rates calculatedfrom a coarse-grained master equation derived from the microcanonical ensemble.The coarse-grained macroscopic rate constants were roughly 50 % larger thanexperiment across a range of environmental constraints, suggesting a systematicimpediment of configurational progress on the microscopic scale that isspecific to the structure of the Ising model. The error in coarse-graining laywith the calculation of the diffusion coefficient rather than with the shape ofthe free energy landscape, as ensemble- and time-averaged estimates of thelatter were indistinguishable. Fluctuation analysis in the form of Nyquisttheorem also failed to substantially improve the value of the effectivediffusion coefficient, suggesting a failure of the fluctuation-dissipationtheorem. These findings from the Ising model raises doubts over the validity ofthe free energy landscape approach in calculating absolute transition rates formore complex systems such as proteins.

Is the free energy landscape informative about transition rates? Lessons from the kinetic Ising model