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      The Next Generation in Membrane Protein Structure Determination 

      Serial Millisecond Crystallography of Membrane Proteins

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          Crystallizing membrane proteins using lipidic mesophases.

          A detailed protocol for crystallizing membrane proteins that makes use of lipidic mesophases is described. This has variously been referred to as the lipid cubic phase or in meso method. The method has been shown to be quite general in that it has been used to solve X-ray crystallographic structures of prokaryotic and eukaryotic proteins, proteins that are monomeric, homo- and hetero-multimeric, chromophore-containing and chromophore-free, and alpha-helical and beta-barrel proteins. Its most recent successes are the human-engineered beta(2)-adrenergic and adenosine A(2A) G protein-coupled receptors. Protocols are provided for preparing and characterizing the lipidic mesophase, for reconstituting the protein into the monoolein-based mesophase, for functional assay of the protein in the mesophase and for setting up crystallizations in manual mode. Methods for harvesting microcrystals are also described. The time required to prepare the protein-loaded mesophase and to set up a crystallization plate manually is about 1 h.
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            Lipidic cubic phase injector facilitates membrane protein serial femtosecond crystallography.

            Lipidic cubic phase (LCP) crystallization has proven successful for high-resolution structure determination of challenging membrane proteins. Here we present a technique for extruding gel-like LCP with embedded membrane protein microcrystals, providing a continuously renewed source of material for serial femtosecond crystallography. Data collected from sub-10-μm-sized crystals produced with less than 0.5 mg of purified protein yield structural insights regarding cyclopamine binding to the Smoothened receptor.
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              CrystFEL: a software suite for snapshot serial crystallography

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                Author and book information

                Book Chapter
                2016
                : 137-149
                10.1007/978-3-319-35072-1_10
                27553240
                289978c6-4b71-44db-91ad-3cd1afa49c40

                http://www.springer.com/tdm

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