Markov state and diffusive stochastic models in electron spin resonance

Sezer, Deniz and Roux, Benoit (2014) Markov state and diffusive stochastic models in electron spin resonance. In: Bowman, Gregory R. and Pande, Vijay S. and Noe, Frank, (eds.) An Introduction to Markov State Models and Their Application to Long Timescale Molecular Simulation. Advances in Experimental Medicine and Biology (797). Springer Science+Business Media, Dordrecht, pp. 115-138. ISBN 978-94-007-7605-0 (Print) 978-94-007-7606-7 (Online)

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Electron spin resonance (ESR) spectra of biological macromolecules reflect a wide range of dynamical molecular motions. However, because an electron spin is strongly coupled to its environment, the quantal degrees of freedom must be propagated for hundreds of nanoseconds to calculate spectra with a reasonable resolution of detail. Furthermore, a large number of independent “samples” are necessary for a reliable estimate of the ESR spectrum. For this reason, a direct calculation from molecular dynamics (MD) simulations is inefficient and wasteful route. As a practical alternative, we present a methodology in which stochastic are first constructed from MD simulations and then used to calculate ESR spectra. Discrete Markov state models (MSMs) offer a natural representation of the jump-like isomerization dynamics of a spin label attached to a protein through a flexible linker. A pedagogical introduction to the second half of the formalism—accounting for the coupling between the molecular and the spin dynamics—is also provided. The chapter concludes with a successful application of the methodology to multi-frequency ESR spectroscopy of spin-labeled T4 Lysozyme.
Item Type: Book Section / Chapter
Subjects: Q Science > QD Chemistry
Q Science > QC Physics
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Biological Sciences & Bio Eng.
Faculty of Engineering and Natural Sciences > Basic Sciences > Physics
Faculty of Engineering and Natural Sciences
Depositing User: Deniz Sezer
Date Deposited: 19 Dec 2014 21:06
Last Modified: 26 Apr 2022 08:32

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