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RosettaEPR: Rotamer Library for Spin Label Structure and Dynamics

Overview of attention for article published in PLOS ONE, September 2013
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Title
RosettaEPR: Rotamer Library for Spin Label Structure and Dynamics
Published in
PLOS ONE, September 2013
DOI 10.1371/journal.pone.0072851
Pubmed ID
Authors

Nathan S. Alexander, Richard A. Stein, Hanane A. Koteiche, Kristian W. Kaufmann, Hassane S. Mchaourab, Jens Meiler

Abstract

An increasingly used parameter in structural biology is the measurement of distances between spin labels bound to a protein. One limitation to these measurements is the unknown position of the spin label relative to the protein backbone. To overcome this drawback, we introduce a rotamer library of the methanethiosulfonate spin label (MTSSL) into the protein modeling program Rosetta. Spin label rotamers were derived from conformations observed in crystal structures of spin labeled T4 lysozyme and previously published molecular dynamics simulations. Rosetta's ability to accurately recover spin label conformations and EPR measured distance distributions was evaluated against 19 experimentally determined MTSSL labeled structures of T4 lysozyme and the membrane protein LeuT and 73 distance distributions from T4 lysozyme and the membrane protein MsbA. For a site in the core of T4 lysozyme, the correct spin label conformation (Χ1 and Χ2) is recovered in 99.8% of trials. In surface positions 53% of the trajectories agree with crystallized conformations in Χ1 and Χ2. This level of recovery is on par with Rosetta performance for the 20 natural amino acids. In addition, Rosetta predicts the distance between two spin labels with a mean error of 4.4 Å. The width of the experimental distance distribution, which reflects the flexibility of the two spin labels, is predicted with a mean error of 1.3 Å. RosettaEPR makes full-atom spin label modeling available to a wide scientific community in conjunction with the powerful suite of modeling methods within Rosetta.

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Geographical breakdown

Country Count As %
United States 2 4%
Israel 1 2%
Canada 1 2%
United Kingdom 1 2%
Spain 1 2%
Taiwan 1 2%
Unknown 48 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 36%
Researcher 9 16%
Student > Doctoral Student 7 13%
Professor 6 11%
Student > Bachelor 3 5%
Other 4 7%
Unknown 6 11%
Readers by discipline Count As %
Chemistry 18 33%
Biochemistry, Genetics and Molecular Biology 17 31%
Agricultural and Biological Sciences 5 9%
Computer Science 3 5%
Arts and Humanities 1 2%
Other 5 9%
Unknown 6 11%