Journal of Biomolecular NMR

, Volume 52, Issue 2, pp 115-126

First online:

Efficient sequential assignments in proteins with reduced dimensionality 3D HN(CA)NH

  • Kousik ChandraAffiliated withNMR Research Centre, Indian Institute of Science
  • , Garima JaipuriaAffiliated withNMR Research Centre, Indian Institute of ScienceSolid State and Structural Chemistry Unit, Indian Institute of Science
  • , Divya ShetAffiliated withNMR Research Centre, Indian Institute of Science
  • , Hanudatta S. AtreyaAffiliated withNMR Research Centre, Indian Institute of Science Email author 

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We present reduced dimensionality (RD) 3D HN(CA)NH for efficient sequential assignment in proteins. The experiment correlates the 15N and 1H chemical shift of a residue (‘i’) with those of its immediate N-terminal (i − 1) and C-terminal (i + 1) neighbors and provides four-dimensional chemical shift correlations rapidly with high resolution. An assignment strategy is presented which combines the correlations observed in this experiment with amino acid type information obtained from 3D CBCA(CO)NH. By classifying the 20 amino acid types into seven distinct categories based on 13Cβ chemical shifts, it is observed that a stretch of five sequentially connected residues is sufficient to map uniquely on to the polypeptide for sequence specific resonance assignments. This method is exemplified by application to three different systems: maltose binding protein (42 kDa), intrinsically disordered domain of insulin-like growth factor binding protein-2 and Ubiquitin. Fast data acquisition is demonstrated using longitudinal 1H relaxation optimization. Overall, 3D HN(CA)NH is a powerful tool for high throughput resonance assignment, in particular for unfolded or intrinsically disordered polypeptides.


Sequence specific resonance assignment Reduced dimensionality NMR Protein structure GFT NMR