Selective High-resolution DNP-enhanced NMR of Biomolecular Binding Sites
authors Ildefonso Marin-Montesinos, David Goyard, Emilie Gillon, Olivier Renaudet, Anne Imberty,Sabine Hediger and Gaël De Paëpe
nationality International
journal Chemical Science
abstract Locating binding sites in biomolecular assemblies and solving their structures are of the utmost importanceto 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-raycrystallography, cryo-electron microscopy and NMR. In this work, we introduce a novel method calledSelective Dynamic Nuclear Polarization (Sel-DNP) that allows selective highlighting and identification ofresidues present in the binding site. This powerful site-directed approach relies on the use of localizedparamagnetic relaxation enhancement induced by a ligand-functionalized paramagnetic constructcombined with difference spectroscopy to recover high-resolution and high-sensitivity information frombinding sites. The identification of residues involved in the binding is performed using spectralfingerprints obtained from a set of high-resolution multidimensional spectra with varying selectivities.The methodology is demonstrated on the galactophilic lectin LecA, for which we report well-resolvedDNP-enhanced spectra with linewidths between 0.5 and 1 ppm, which enable thede novoassignmentof the binding interface residues, without using previous knowledge of the binding site location. Sincethis approach produces clean and resolved difference spectra containing a limited number of residues,resonance assignment can be performed without any limitation with respect to the size of thebiomolecular system and only requires the production of one protein sample (e.g.13C,15N-labeled protein).
year published 2019
volume 10
beginning page 3366
digital object identifier (doi) 10.1039/C8SC05696J
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journal analysis (jcr 2019):
journal impact factor 9.346
5 year journal impact factor 8.945
category normalized journal impact factor percentile 88.418
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