Uniaxial Diffusional Narrowing of NMR Lineshapes for Membrane Proteins Reconstituted in Magnetically Aligned Bicelles and Macrodiscs

Аннотация

Structure and dynamics of membrane proteins can be effectively studied by oriented-sample solid-state nuclear magnetic resonance (NMR) techniques when the lipid bilayers are macroscopically aligned with respect to the main magnetic field. Magnetic alignment of the protein-containing membrane bilayer results from the negative susceptibility anisotropy of the lipid hydrocarbon interior yielding perpendicular sample alignment. At this orientation, while the uniformity of alignment represents an essential prerequisite for obtaining high-quality NMR spectra, further line narrowing is obtained by uniaxial motional averaging of the azimuthal parts of the chemical shift anisotropies and dipolar couplings. The motional averaging is brought about by uniaxial rotational diffusion of the protein molecules about the normal to the membrane surface, which is perpendicular to the magnetic field. Uniaxial averaging is efficient when the motion about the axis of alignment becomes sufficiently fast (on the timescale of the dipolar couplings and chemical shift anisotropies). Line narrowing under uniaxial rotation can be theoretically modeled using the stochastic Liouville equation. In this mini-review, we illustrate the method of uniaxial averaging for the relatively small Pf1 coat protein which exhibits excellent resolution in magnetically aligned bicelles due to its fast uniaxial diffusion and even superior resolution in large (30 nm) nanodiscs (macrodiscs) stabilized by a belt peptide. Spectra of Pf1 coat protein in polymer-stabilized macrodiscs, an alternative and more robust alignment media, are presented. We also report on preliminary spectra of a much larger protein—uniformly ¹⁵N labeled M1-M4 domain for the human acetylcholine receptor. While some spectral resolution is apparent, significantly broader linewidths emphasize the need for creating fast rotating discoidal membrane mimetics.