Solid-State NMR Investigations of the MHC II Transmembrane Domains: Topological Equilibria and Lipid Interactions.
Christopher AisenbreyEvgeniy S SalnikovBurkhard BechingerPublished in: The Journal of membrane biology (2019)
The major histocompatibility complex class II (MHC II) membrane proteins are key players in the adaptive immune response. An aberrant function of these molecules is associated with a large number of autoimmune diseases such as diabetes type I and chronic inflammatory diseases. The MHC class II is assembled from DQ alpha 1 and DQ beta 1 which come together as a heterodimer through GXXXG-mediated protein-protein interactions and a highly specific protein-sphingomyelin-C18 interaction motif located on DQA1. This association can have important consequences in regulating the function of these membrane proteins. Here, we investigated the structure and topology of the DQA1 and DQB1 transmembrane helical domains by CD-, oriented 2H and 15N solid-state NMR spectroscopies. The spectra at peptide-to-lipid ratios of 0.5 to 2 mol% are indicative of a topological equilibrium involving a helix crossing the membrane with a tilt angle of about 20° and another transmembrane topology with around 30° tilt. The latter is probably representing a dimer. Furthermore, at the lowest peptide-to-lipid ratio, a third polypeptide population becomes obvious. Interestingly, the DQB1 and to a lesser extent the DQA1 transmembrane helical domains exhibit a strong fatty acyl chain disordering effect on the inner segments of the 2H-labelled palmitoyl chain of POPC bilayers. This phosphatidylcholine disordering requires the presence of sphingomyelin-C18 suggesting that the ensemble of transmembrane polypeptide and sphingolipid exerts positive curvature strain.
Keyphrases
- solid state
- fatty acid
- immune response
- type diabetes
- molecular dynamics simulations
- high resolution
- cardiovascular disease
- oxidative stress
- magnetic resonance
- dendritic cells
- molecular dynamics
- celiac disease
- small molecule
- binding protein
- machine learning
- amino acid
- deep learning
- drug induced
- atomic force microscopy
- density functional theory