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De Novo High-Resolution Protein Structure Determination from Sparse Spin-Labeling EPR Data

Authors
Journal
Structure
0969-2126
Publisher
Elsevier
Publication Date
Volume
16
Issue
2
Identifiers
DOI: 10.1016/j.str.2007.11.015
Keywords
  • Proteins
Disciplines
  • Biology
  • Computer Science
  • Mathematics

Abstract

Summary As many key proteins evade crystallization and remain too large for nuclear magnetic resonance spectroscopy, electron paramagnetic resonance (EPR) spectroscopy combined with site-directed spin labeling offers an alternative approach for obtaining structural information. Such information must be translated into geometric restraints to be used in computer simulations. Here, distances between spin labels are converted into distance ranges between β carbons by using a “motion-on-a-cone” model, and a linear-correlation model links spin-label accessibility to the number of neighboring residues. This approach was tested on T4-lysozyme and αA-crystallin with the de novo structure prediction algorithm Rosetta. The results demonstrate the feasibility of obtaining highly accurate, atomic-detail models from EPR data by yielding 1.0 Å and 2.6 Å full-atom models, respectively. Distance restraints between amino acids far apart in sequence but close in space are most valuable for structure determination. The approach can be extended to other experimental techniques such as fluorescence spectroscopy, substituted cysteine accessibility method, or mutational studies.

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