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Originally published as Biophys J. BioFAST on January 30, 2008.
doi:10.1529/biophysj.107.125419
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Biophysical Journal 94:3798-3809 (2008)
© 2008 The Biophysical Society

Simulation of Nitroxide Electron Paramagnetic Resonance Spectra from Brownian Trajectories and Molecular Dynamics Simulations

Susan C. DeSensi *, David P. Rangel {dagger}, Albert H. Beth {ddagger}, Terry P. Lybrand * and Eric J. Hustedt {ddagger}

* Department of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, Tennessee 37235; {dagger} Department of Chemistry, University of Washington, Seattle, Washington 98195; and {ddagger} Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee 37232

Correspondence: Address reprint requests to Eric J. Hustedt, 735B Light Hall, Vanderbilt University, Nashville, TN 37232. Tel.: 615-322-3181; Fax: 615-322-7236; E-mail: eric.hustedt{at}vanderbilt.edu.

A simulated continuous wave electron paramagnetic resonance spectrum of a nitroxide spin label can be obtained from the Fourier transform of a free induction decay. It has been previously shown that the free induction decay can be calculated by solving the time-dependent stochastic Liouville equation for a set of Brownian trajectories defining the rotational dynamics of the label. In this work, a quaternion-based Monte Carlo algorithm has been developed to generate Brownian trajectories describing the global rotational diffusion of a spin-labeled protein. Also, molecular dynamics simulations of two spin-labeled mutants of T4 lysozyme, T4L F153R1, and T4L K65R1 have been used to generate trajectories describing the internal dynamics of the protein and the local dynamics of the spin-label side chain. Trajectories from the molecular dynamics simulations combined with trajectories describing the global rotational diffusion of the protein are used to account for all of the dynamics of a spin-labeled protein. Spectra calculated from these combined trajectories correspond well to the experimental spectra for the buried site T4L F153R1 and the helix surface site T4L K65R1. This work provides a framework to further explore the modeling of the dynamics of the spin-label side chain in the wide variety of labeling environments encountered in site-directed spin labeling studies.







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