Trajectory-Based Simulation of EPR Spectra: Models of Rotational Motion for Spin Labels on Proteins

Peter D. Martin, Bengt Svensson, David D. Thomas, Stefan Stoll

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Direct time-domain simulation of continuous-wave (CW) electron paramagnetic resonance (EPR) spectra from molecular dynamics (MD) trajectories has become increasingly popular, especially for proteins labeled with nitroxide spin labels. Due to the time-consuming nature of simulating adequately long MD trajectories, two approximate methods have been developed to reduce the MD-trajectory length required for modeling EPR spectra: hindered Brownian diffusion (HBD) and hidden Markov models (HMMs). Here, we assess the accuracy of these two approximate methods relative to direct simulations from MD trajectories for three spin-labeled protein systems (a simple helical peptide, a soluble protein, and a membrane protein) and two nitroxide spin labels with differing mobilities (R1 and 2,2,6,6-tetramethylpiperidine-1-oxyl-4-amino-4-carboxylic acid (TOAC)). We find that the HMMs generally outperform HBD. Although R1 dynamics partially resembles hindered Brownian diffusion, HMMs accommodate the multiple dynamic time scales for the transitions between rotameric states of R1 that cannot be captured accurately by a HBD model. The MD trajectories of the TOAC-labeled proteins show that its dynamics closely resembles slow multisite exchange between twist-boat and chair ring puckering states. This motion is modeled well by HMM but not by HBD. All MD-trajectory data processing, stochastic trajectory simulations, and CW EPR spectral simulations are implemented in EasySpin, a free software package for MATLAB.

Original languageEnglish (US)
Pages (from-to)10131-10141
Number of pages11
JournalJournal of Physical Chemistry B
Volume123
Issue number48
DOIs
StatePublished - Dec 5 2019

Bibliographical note

Funding Information:
This work was supported by NIH grants GM27906 (D.D.T.), AR32961 (D.D.T.), AG026160 (D.D.T.), and GM125753 (S.S.) and by NSF grant CHE-1452967 (S.S.). P.D.M. was supported by NIH Training Grant AR007612. Computational resources for MD simulations were provided by the Minnesota Supercomputing Institute. We thank Jack H. Freed (Cornell) for providing the CW EPR experimental data for V131R1 T4 lysozyme. We also thank Andrew Reid for performing the MD simulation on TOAC-labeled phospholamban.

Publisher Copyright:
© 2019 American Chemical Society.

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