European Biophysics Journal

, Volume 36, Issue 6, pp 637–646

An investigation of the dynamics of spermine bound to duplex and quadruplex DNA by 13C NMR spectroscopy

Original Paper

DOI: 10.1007/s00249-007-0136-4

Cite this article as:
Keniry, M.A. & Owen, E.A. Eur Biophys J (2007) 36: 637. doi:10.1007/s00249-007-0136-4


A detailed analysis of the 13C relaxation of 13C-labelled spermine bound to duplex and quadruplex DNA is presented. T1, T2 and heteronuclear NOE data were collected at four 13C frequencies (75.4, 125.7, 150.9 and 201.2 MHz). The data were analyzed in terms of a frequency-dependent order parameter, S2(ω), to estimate the generalized order parameter and the contributions to the relaxation from different motional frequencies in the picosecond–nanosecond timescale and from any exchange processes that may be occurring on the microsecond–millisecond timescale. The relaxation data was surprisingly similar for spermine bound to two different duplexes and a linear parallel quadruplex. Analysis of the relaxation data from these complexes confirmed the conclusions of previous studies that the dominant motion of spermine is independent of the macroscopic tumbling of the DNA and has an effective correlation time of ∼50 ps. In contrast, spermine bound to a folded antiparallel quadruplex had faster relaxation rates, especially R2. As with the other complexes, a fast internal motion of the order of 50 ps makes a substantial contribution to the relaxation. The generalized order parameter for spermine bound to duplex DNA and the linear quadruplex is small but is larger for spermine bound to the folded quadruplex. In the latter case, there is evidence for exchange between at least two populations of spermine occurring on the microsecond–millisecond timescale.


DNA NMR spectroscopy Spin relaxation Order parameter Nucleic acids Spermine Quadruplex 

Supplementary material

Copyright information

© EBSA 2007

Authors and Affiliations

  1. 1.Research School of ChemistryAustralian National UniversityCanberraAustralia

Personalised recommendations