Reference: Krishnarjuna B, et al. (2011) Amino acid selective unlabeling for sequence specific resonance assignments in proteins. J Biomol NMR 49(1):39-51

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Abstract


Sequence specific resonance assignment constitutes an important step towards high-resolution structure determination of proteins by NMR and is aided by selective identification and assignment of amino acid types. The traditional approach to selective labeling yields only the chemical shifts of the particular amino acid being selected and does not help in establishing a link between adjacent residues along the polypeptide chain, which is important for sequential assignments. An alternative approach is the method of amino acid selective 'unlabeling' or reverse labeling, which involves selective unlabeling of specific amino acid types against a uniformly (13)C/(15)N labeled background. Based on this method, we present a novel approach for sequential assignments in proteins. The method involves a new NMR experiment named, {(12)CO( i )-(15)N( i+1)}-filtered HSQC, which aids in linking the (1)H(N)/(15)N resonances of the selectively unlabeled residue, i, and its C-terminal neighbor, i + 1, in HN-detected double and triple resonance spectra. This leads to the assignment of a tri-peptide segment from the knowledge of the amino acid types of residues: i - 1, i and i + 1, thereby speeding up the sequential assignment process. The method has the advantage of being relatively inexpensive, applicable to (2)H labeled protein and can be coupled with cell-free synthesis and/or automated assignment approaches. A detailed survey involving unlabeling of different amino acid types individually or in pairs reveals that the proposed approach is also robust to misincorporation of (14)N at undesired sites. Taken together, this study represents the first application of selective unlabeling for sequence specific resonance assignments and opens up new avenues to using this methodology in protein structural studies.

Reference Type
Journal Article | Research Support, Non-U.S. Gov't
Authors
Krishnarjuna B, Jaipuria G, Thakur A, D'Silva P, Atreya HS
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