Markov models and dynamical fingerprints: unraveling the complexity of molecular kinetics
Please always quote using this URN:urn:nbn:de:0296-matheon-10986
- Dynamical fingerprints of macromolecules obtained from experiments often seem to indicate two- or three state kinetics while simulations typically reveal a more complex picture. Markov state models of molecular conformational dynamics can be used to predict these dynamical fingerprints and to reconcile experiment with simulation. This is illustrated on two model systems: a one-dimensional energy surface and a four-state model of a protein folding equilibrium. We show that (i) there might be no process which corresponds to our notion of folding, (ii) often the experiment will be insensitive to some of the processes present in the system, (iii) with a suitable combination the observable and initial conditions in a relaxation experiment one can selectively measure specific processes. Furthermore, our method can be used to design experiments such that specific processes appear with large amplitudes. We demonstrate that for a fluorescence quenching experiment of the MR121-G9-W peptide.
Author: | Bettina Keller, Jan-Hendrik Prinz, Frank Noe |
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URN: | urn:nbn:de:0296-matheon-10986 |
Referee: | Christof Schütte |
Document Type: | Preprint, Research Center Matheon |
Language: | English |
Date of first Publication: | 2012/02/27 |
Release Date: | 2012/02/27 |
Tag: | FCS; FRET; Markov models; T-jump; dynamical fingerprints; molecular dynamics; protein folding; single-molecule spectroscopy |
Institute: | Research Center Matheon |
Freie Universität Berlin | |
MSC-Classification: | 62-XX STATISTICS / 62Mxx Inference from stochastic processes / 62M05 Markov processes: estimation |
Preprint Number: | 940 |