Determination of Peptide Backbone Torsion Angles Using Double-Quantum Dipolar Recoupling Solid-State NMR Spectroscopy

• Published in: Journal of the American Chemical Society Vol. 130; no. 7; pp. 2202 - 2212
• Main Authors: Mehta, Manish A, Eddy, Matthew T, McNeill, Seth A, Mills, Frank D, Long, Joanna R
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 20.02.2008
• Subjects: Computer Simulation; Nuclear Magnetic Resonance, Biomolecular - methods; Oligopeptides - chemistry; Protein Structure, Secondary; Quantum Theory; X-Ray Diffraction
• ISSN: 0002-7863; 1520-5126
• DOI: 10.1021/ja074244w

Several approaches for utilizing dipolar recoupling solid-state NMR (ssNMR) techniques to determine local structure at high resolution in peptides and proteins have been developed. However, many of these techniques measure only one torsion angle or are accurate for only certain classes of secondary structure. Additionally, the efficiency with which these dipolar recoupling experiments suppress the deleterious effects of chemical shift anisotropy (CSA) at high magnetic field strengths varies. Dipolar recoupling with a windowless sequence (DRAWS) has proven to be an effective pulse sequence for exciting double-quantum (DQ) coherences between adjacent carbonyl carbons along the peptide backbone. By allowing this DQ coherence to evolve, it is possible to measure the relative orientations of the CSA tensors and subsequently use this information to determine the Ramachandran torsion angles φ and ψ. Here, we explore the accuracies of the assumptions made in interpreting DQ-DRAWS data and demonstrate their fidelity in measuring torsion angles corresponding to a variety of secondary structures irrespective of hydrogen-bonding patterns. It is shown how a simple choice of isotopic labels and experimental conditions allows accurate measurement of backbone secondary structures without any prior knowledge. This approach is considerably more sensitive for determining structure in helices and has comparable accuracy for β-sheet and extended conformations relative to other methods. We also illustrate the ability of DQ-DRAWS to distinguish between structures in heterogeneous samples.