Markov models and dynamical fingerprints: Unraveling the complexity of molecular kinetics

The equilibrium kinetics of biomolecules can be probed by techniques such as temperature-jump or fluorescence correlation spectroscopy. These measurements can be described by dynamical fingerprints, i.e., densities of relaxation timescales where each peak corresponds to an exponential relaxation process. In many cases, single-or double-peaked fingerprints are found, suggesting that a two-or three-state model may provide a satisfactory description of the biomolecule studied, while simulations often reveal a more complex picture with many kinetically relevant states. Here we sketch an approach combining Markov models of the simulated dynamics with dynamical fingerprints to link between simulation and experiment. This link sheds light on the relation between experimental setup and sensitivity of the experiment to particular kinetic processes. Furthermore, our approach can be used to design experiments such that specific processes appear with large amplitudes. This is illustrated by reviewing recent results from the analysis of the fluorescent 18-mer peptide MR121-(GS)(9)-W. (C) 2011 Elsevier B.V. All rights reserved.