Abstract
'q-Titration' refers to the systematic comparison of signal intensities in solution NMR spectra of uniformly (15)N labeled membrane proteins solubilized in micelles and isotropic bicelles as a function of the molar ratios (q) of the long-chain lipids (typically DMPC) to short-chain lipids (typically DHPC). In general, as q increases, the protein resonances broaden and correspondingly have reduced intensities due to the overall slowing of protein reorientation. Since the protein backbone signals do not broaden uniformly, the differences in line widths (and intensities) enable the narrower (more intense) signals associated with mobile residues to be differentiated from the broader (less intense) signals associated with "structured" residues. For membrane proteins with between one and seven trans-membrane helices in isotropic bicelles, we have been able to find a value of q between 0.1 and 1.0 where only signals from mobile residues are observed in the spectra. The signals from the structured residues are broadened so much that they cannot be observed under standard solution NMR conditions. This q value corresponds to the ratio of DMPC:DHPC where the signals from the structured residues are "titrated out" of the spectrum. This q value is unique for each protein. In magnetically aligned bilayers (q>2.5) no signals are observed in solution NMR spectra of membrane proteins because the polypeptides are "immobilized" by their interactions with the phospholipid bilayers on the relevant NMR timescale (∼10(5)Hz). No signals are observed from proteins in liposomes (only long-chain lipids) either. We show that it is feasible to obtain complementary solution NMR and solid-state NMR spectra of the same membrane protein, where signals from the mobile residues are present in the solution NMR spectra, and signals from the structured residues are present in the solid-state NMR spectra. With assigned backbone amide resonances, these data are sufficient to describe major features of the secondary structure and basic topology of the protein. Even in the absence of assignments, this information can be used to help establish optimal experimental conditions.