Solid-State NMR Provides Evidence for Small-Amplitude Slow Domain Motions in a Multispanning Transmembrane α-Helical Protein

Abstract

Proteins are dynamic entities and populate ensembles of conformations. Transitions between states within a conformational ensemble occur over a broad spectrum of amplitude and time scales, and are often related to biological function. Whereas solid-state NMR (SSNMR) spectroscopy has recently been used to characterize conformational ensembles of proteins in the microcrystalline states, its applications to membrane proteins remain limited. Here we use SSNMR to study conformational dynamics of a seven-helical transmembrane (TM) protein, Anabaena Sensory Rhodopsin (ASR) reconstituted in lipids. We report on site-specific measurements of the 15N longitudinal R1 and rotating frame R1ρ relaxation rates at two fields of 600 and 800 MHz and at two temperatures of 7 and 30 °C. Quantitative analysis of the R1 and R1ρ values and of their field and temperature dependencies provides evidence of motions on at least two time scales. We modeled these motions as fast local motions and slower collective motions of TM helices and of structured loops, and used the simple model-free and extended model-free analyses to fit the data and estimate the amplitudes, time scales and activation energies. Faster picosecond (tens to hundreds of picoseconds) local motions occur throughout the protein and are dominant in the middle portions of the TM helices. In contrast, the amplitudes of the slower collective motions occurring on the nanosecond (tens to hundreds of nanoseconds) time scales, are smaller in the central parts of helices, but increase toward their cytoplasmic sides as well as in the interhelical loops. ASR interacts with a soluble transducer protein on its cytoplasmic surface, and its binding affinity is modulated by light. The larger amplitude of motions on the cytoplasmic side of the TM helices correlates with the ability of ASR to undergo large conformational changes in the process of binding/unbinding the transducer.

Hidden motions and motion-induced invisibility: Dynamics-based spectral editing in solid-state NMR

“…The abovementioned dynamics information does not provide as comprehensive, quantitative or detailed a picture as has been obtained for a number of other proteins [24,52,58,126,127]. Nonetheless, the obtained results provided a unique perspective on these polyQ expansion disease-related protein deposits [7,115–120].…”

A combination of solid-state NMR and MD simulations reveals the binding mode of a rhomboid protease inhibitor

“…9 1 H-detected solid-state NMR has become a valuable approach to study membrane proteins due to the higher sensitivity compared to 13 C detection and the additional information available on H/D exchange and water accessibility. [29][30][31][32] Here we used it in combination with molecular docking and molecular dynamics (MD) simulations to investigate the effects of inhibitor binding on GlpG.…”

Microsecond motions probed by near-rotary-resonance R1ρ 15N MAS NMR experiments: the model case of protein overall-rocking in crystals

“…During the recent decade, measurements of the 15 N rotating-frame relaxation rate ( R 1ρ = 1/ T 1ρ ) have been widely applied in the solid-state NMR studies of protein dynamics. Combination of fast magic angle spinning (MAS) and/or partial deuteration of proteins enable obtaining well resolved 1 H– 15 N correlation spectra and, as a consequence, capability to measure site-specific relaxation rates with a negligible spin–spin contribution to the incoherent relaxation (Krushelnitsky et al 2010 ; Zinkevich et al 2013 ; Good et al 2014 , 2017 ; Lamley et al 2015a , b ; Ma et al 2015 ; Smith et al 2016 ; Kurauskas et al 2016 , 2017 ; Saurel et al 2017 ; Lakomek et al 2017 ; Gauto et al 2017 ). The ability to vary the spin-lock field strength from < 1 to 40–50 kHz enables covering a wide frequency range of dynamics, and the simultaneous analysis of both the chemical-exchange contribution to R 1ρ and the dipole/CSA relaxation mechanisms (Ma et al 2014 ; Lamley et al 2015b ) provides abundant data that characterize protein dynamics in much detail.…”