Towards complete polypeptide backbone NH assignment via combinatorial labeling.

Area of Science:

• Structural Biology
• Biophysical Chemistry
• Nuclear Magnetic Resonance Spectroscopy

Background:

• Combinatorial selective isotope labeling is crucial for polypeptide backbone resonance assignment, especially with low sensitivity or overlapping chemical shifts.
• Current methods rely on 2D and 3D NMR spectra, often requiring matching 13C chemical shifts for residue assignment.
• Increasing sample numbers for combinatorial labeling is impractical due to cost and effort.

Purpose of the Study:

• To develop an improved combinatorial labeling strategy for unambiguous polypeptide backbone resonance assignment.
• To resolve ambiguities in residue assignment for non-unique sequence pairs.
• To enhance the efficiency and scope of protein sequence assignment using NMR.

Main Methods:

• Utilized combinatorial selective isotope labeling with enriched 15N or 13C isotopes in backbone heteronuclei.
• Recorded 15N-HSQC and 2D HN-projection spectra from samples with varied labeling combinations.
• Introduced a novel approach incorporating labeling information from residues i+1 and i-2 to resolve assignment ambiguities.

Main Results:

• Successfully assigned all detectable signals in the 15N HSQC for a 35-residue peptide with a repetitive sequence, overcoming previous difficulties.
• Achieved 88% backbone amide assignment for a 165-residue protein using only 2D 1H-15N correlated spectra.
• Demonstrated the effectiveness of including labeling states of flanking residues (i+1, i-2) for unambiguous assignments.

Conclusions:

• The refined combinatorial labeling strategy significantly improves the accuracy and completeness of polypeptide backbone resonance assignment.
• This method offers a powerful alternative for assigning complex protein structures, even with limited sample preparation.
• The approach expands the applicability of 2D NMR techniques for high-resolution protein structural studies.