25-30 August 2019
Henry Ford Building
Europe/Berlin timezone

Selective High-Resolution DNP-Enhanced NMR of Biomolecular Binding Sites

26 Aug 2019, 16:15
Lecture Hall D (Henry Ford Building)

Lecture Hall D

Henry Ford Building

Invited talk Biological applications Biomolecules


Dr Sabine Hediger (CNRS)


Locating binding sites in biomolecular assemblies and solving their structures is crucial to unravel functional aspects of the system and provide experimental data that can be used for structure-based drug design. This often still remains a challenge, both in terms of selectivity and sensitivity for X-ray crystallography, cryo-electron microscopy and NMR.
Dynamic Nuclear Polarization (DNP) has revolutionized the scope of many solid-state NMR experiments by enabling new sensitivity-limited experiments to be recorded. Its use for biomolecular systems is however often limited by the necessity to run experiments at cryogenic temperatures, which can induce line broadening and loss of resolution. We present here a new method, called Selective DNP (Sel-DNP) that provides specific selectivity with high spectral resolution for the binding region of biomolecules, allowing for the identification of the residues present in the binding site. This powerful site-directed approach relies on the combined use of localized paramagnetic relaxation enhancement, induced by a ligand-functionalized paramagnetic construct, and difference spectroscopy to recover high-resolution and high-sensitivity information from binding sites.
The Sel-DNP approach is demonstrated on the galactophilic lectin LecA, a 12.75 kDa protein. The identification of residue types present in the galactose-binding region occurs using spectral fingerprints obtained from a set of high-resolution multidimensional spectra with varying selectivity. Experimental and computational strategies are then combined to assign the identified residues types to the specific residues in the sequence of the protein. In particular, a hierarchical alignment procedure using a modified genetic algorithm will be presented, which is able to perform de novo assignment and to locate the binding site in the protein sequence on the sole basis of the residue-type list extracted from Sel-DNP spectra.

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