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Computer modeling of nitroxide spin labels on proteins
Author(s) -
Hatmal Ma'mon M.,
Li Yiyu,
Hegde Balachandra G.,
Hegde Prabhavati B.,
Jao Christine C.,
Langen Ralf,
Haworth Ian S.
Publication year - 2012
Publication title -
biopolymers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 125
eISSN - 1097-0282
pISSN - 0006-3525
DOI - 10.1002/bip.21699
Subject(s) - chemistry , conformational isomerism , algorithm , computation , weighting , electron paramagnetic resonance , interpretation (philosophy) , spin (aerodynamics) , biological system , nuclear magnetic resonance , computer science , physics , molecule , organic chemistry , biology , thermodynamics , acoustics , programming language
Electron paramagnetic resonance using site‐directed spin labeling can be used as an approach for determination of protein structures that are difficult to solve by other methods. One important aspect of this approach is the measurement of interlabel distances using the double electron–electron resonance (DEER) method. Interpretation of experimental data could be facilitated by a computational approach to calculation of interlabel distances. We describe an algorithm, PRONOX, for rapid computation of interlabel distances based on calculation of spin label conformer distributions at any site of a protein. The program incorporates features of the label distribution established experimentally, including weighting of favorable conformers of the label. Distances calculated by PRONOX were compared with new DEER distances for amphiphysin and annexin B12 and with published data for FCHo2 (F‐BAR), endophilin, and α‐synuclein, a total of 44 interlabel distances. The program reproduced these distances accurately (r 2 = 0.94, slope = 0.98). For 9 of the 11 distances for amphiphysin, PRONOX reproduced the experimental data to within 2.5 Å. The speed and accuracy of PRONOX suggest that the algorithm can be used for fitting to DEER data for determination of protein tertiary structure. © 2011 Wiley Periodicals, Inc. Biopolymers 97: 35–44, 2012.