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Book Chapter

New Frontiers in Characterizing Structure and Dynamics by NMR


Habeck,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Developmental Biology, Max Planck Society;

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Nilges, M., Markwick, P., Malliavin, T., Rieping, W., & Habeck, M. (2008). New Frontiers in Characterizing Structure and Dynamics by NMR. In T. Schwede, & M. Peitsch (Eds.), Computational Structural Biology: Methods and Applications (pp. 655-679). New Jersey, NJ, USA: World Scientific.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-C989-9
Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as the method of choice for studying both the structure and the dynamics of biological macromolecule in solution. Despite the maturity
of the NMR method for structure determination, its application faces a number of challenges. The
method is limited to systems of relatively small molecular mass, data collection times are long,
data analysis remains a lengthy procedure, and it is difficult to evaluate the quality of the final
structures. The last years have seen significant advances in experimental techniques to overcome
or reduce some limitations.
The function of bio-macromolecules is determined by both their 3D structure and conformational
dynamics. These molecules are inherently flexible systems displaying a broad range of
dynamics on time–scales from picoseconds to seconds. NMR is unique in its ability to obtain dynamic
information on an atomic scale. The experimental information on structure and dynamics
is intricately mixed. It is however difficult to unite both structural and dynamical information into
one consistent model, and protocols for the determination of structure and dynamics are performed
This chapter deals with the challenges posed by the interpretation of NMR data on structure
and dynamics. We will first relate the standard structure calculation methods to Bayesian probability
theory. We will then briefly describe the advantages of a fully Bayesian treatment of structure
calculation. Then, we will illustrate the advantages of using Bayesian reasoning at least partly in
standard structure calculations. The final part will be devoted to interpretation of experimental
data on dynamics.