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Detergent optimized membrane protein reconstitution in liposomes for solid state NMR.


ABSTRACT: For small helical membrane proteins, their structures are highly sensitive to their environment, and solid state NMR is a structural technique that can characterize these membrane proteins in native-like lipid bilayers and proteoliposomes. To date, a systematic method by which to evaluate the effect of the solubilizing detergent on proteoliposome preparations for solid state NMR of membrane proteins has not been presented in the literature. A set of experiments are presented aimed at determining the conditions most amenable to dialysis mediated reconstitution sample preparation. A membrane protein from M. tuberculosis is used to illustrate the method. The results show that a detergent that stabilizes the most protein is not always ideal and sometimes cannot be removed by dialysis. By focusing on the lipid and protein binding properties of the detergent, proteoliposome preparations can be readily produced, which provide double the signal-to-noise ratios for both the oriented sample and magic angle spinning solid state NMR. The method will allow more membrane protein drug targets to be structurally characterized in lipid bilayer environments.

SUBMITTER: Murray DT 

PROVIDER: S-EPMC4004220 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Detergent optimized membrane protein reconstitution in liposomes for solid state NMR.

Murray Dylan T DT   Griffin James J   Cross Timothy A TA  

Biochemistry 20140409 15


For small helical membrane proteins, their structures are highly sensitive to their environment, and solid state NMR is a structural technique that can characterize these membrane proteins in native-like lipid bilayers and proteoliposomes. To date, a systematic method by which to evaluate the effect of the solubilizing detergent on proteoliposome preparations for solid state NMR of membrane proteins has not been presented in the literature. A set of experiments are presented aimed at determining  ...[more]

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