Combinatorial triple-selective labeling as a tool to assist membrane protein backbone resonance assignment

Area of Science:

• Structural Biology
• Biophysics
• Nuclear Magnetic Resonance (NMR) Spectroscopy

Background:

• NMR assignments for slowly tumbling molecules like membrane proteins face challenges due to low sensitivity and spectral overlap.
• Amino-acid specific isotope labeling combined with (15)N-(1)H correlation experiments can address these challenges.

Purpose of the Study:

• To propose an extended combinatorial selective in vitro labeling scheme to reduce the number of samples required for NMR assignment.
• To enable identification of more amino acid types and sequential pairs compared to existing methods.

Main Methods:

• Developed an extended combinatorial selective in vitro labeling scheme incorporating three amino acid species per sample: (15)N, 1-(13)C, and fully (13)C/(15)N labeled.
• Utilized up to five 2D triple-resonance experiments to distinguish isotopomeric dipeptide species.
• Analyzed the pattern of backbone NH cross peaks and compared spectra from samples with varying labeled amino acid compositions.

Main Results:

• The proposed scheme allows for the identification of more amino acid types and sequential pairs.
• Application to two α-helical membrane proteins demonstrated successful backbone assignments using no more than three samples.
• The method effectively fills gaps in assignments caused by signal overlap or inefficient 3D experiments.

Conclusions:

• The extended combinatorial labeling strategy significantly enhances the efficiency of NMR assignments for membrane proteins.
• This approach provides a robust solution for obtaining structural information from challenging biological macromolecules.
• The protocol facilitates complete backbone assignments, even in cases of spectral complexity or missing data.