Conformation of a seven-helical transmembrane photosensor in the lipid environment.
Conformation of a seven-helical transmembrane photosensor in the lipid environment.
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DOI：
10.1002/anie.201004422
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发表时间：
2011-02
影响因子：
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通讯作者：
Lichi Shi;I. Kawamura;K. Jung;L. Brown;V. Ladizhansky
中科院分区：
文献类型：
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作者：
Lichi Shi;I. Kawamura;K. Jung;L. Brown;V. Ladizhansky
固态核磁共振波谱（SSNMR）已经成为膜蛋白在其天然脂质环境中的结构和动态研究的主要工具之一，并且已经提供了大量生物学和医学重要系统的丰富信息。[1-8]大螺旋蛋白的应用正在进行中，并有望增加我们对膜生物学的理解。[9-13]在此，我们提出了来自鱼腥藻属PCC 7120（ASR）的七螺旋膜光感受器，感觉视紫红质的魔角旋转[14]（MAS）SSNMR研究。[15]我们报告的骨干和侧链信号的蛋白质，其二级结构的分析，并分析了许多极性残基的环境的分配。我们使用特定位点的H/D交换测量来确定蛋白质的水可及表面及其在脂质双层内的拓扑结构。虽然从我们的数据中得出的ASR的二级结构与先前通过X射线晶体学确定的二级结构总体上一致，[16]但我们已经确定了一些重要的差异和补充，这使我们能够建立一个精细的结构模型。我们采用3D化学位移相关光谱法对单个脂质重构的均匀13 C，15 N标记的样品进行。从结构的角度来看，ASR与G蛋白偶联受体共享其七螺旋结构。我们的研究表明，类似的方法原则上可以应用于这类蛋白质，而不需要结晶和/或去污剂增溶。重要的是，从SSNMR获得的结构信息属于脂质环境中的蛋白质，与其天然状态密切相关。在脂质中重构的ASR可提供分辨率良好的光谱，具有高信噪比，典型的碳和氮线宽为0.5 ppm（支持信息中的图1和图S1）。蛋白质在这种环境中是功能性的和稳定的。[17]光谱分配是从单个样品上获得的五个3D化学位移相关实验中获得的：CONCA，两个NCACX实验，偶极辅助旋转异构体共振（DARR）[18]混合时间为20 ms和50 ms，以及两个NCOCX实验，DARR混合时间为50 ms和100 ms。虽然CONCA光谱提供了几乎完全的骨架分辨率，并建立了CO [i]、N [i+ 1]和CA-[i+ 1]原子之间的残基间相关性，但NCACX和NCOCX实验允许记录侧链碳原子的化学位移，用于鉴定氨基酸类型。较短的混合时间实验主要提供单键和双键相关性，例如，NCOCX和NCACX实验中的N [i+ 1]-CO [i]-CA [i]和N [i]-CA [i]-CO [i]/CB [i]，而较长的混合时间建立整个碳侧链的位移，并提供额外的残基间相关性用于赋值验证。
Solid-state NMR spectroscopy (SSNMR) has emerged as one of the main tools for structural and dynamic investigation of membrane proteins in their native-like lipid environment, and has already provided a wealth of information on a number of biologically and medically important systems.[1–8] Applications to large helical proteins are underway and promise to add to our understanding of membrane biology.[9–13] Herein we present a magic-angle spinning [14](MAS) SSNMR study of a seven-helical membrane photoreceptor, sensory rhodopsin from Anabaena sp. PCC 7120 (ASR).[15] We report the assignment of backbone and side-chain signals of the protein, analysis of its secondary structure, and analysis of the environment of many polar residues. We use sitespecific H/D exchange measurements to determine the wateraccessible surface of the protein and its topology within the lipid bilayer. Although the secondary structure of ASR derived from our data is overall consistent with that previously determined by X-ray crystallography,[16] we have identified a number of important differences and additions, which allowed us to build a refined structural model. We employed 3D chemical shift correlation spectroscopy performed on a single lipid-reconstituted uniformly 13C, 15N-labeled sample. From a structural perspective, ASR shares its seven-helical architecture with G-protein-coupled receptors. Our studies demonstrate that a similar methodology can in principle be applied to this class of proteins without the need for crystallization and/or detergent solubilization. Importantly, the structural information obtained from SSNMR pertains to a protein in the lipid environment, closely related to its native state. ASR reconstituted in lipids gives wellresolved spectra with high signal-to-noise ratios, with typical carbon and nitrogen line widths of 0.5 ppm (Figure 1 and FigureS1 in the Supporting Information). The protein is functional and stable in this environment.[17]Spectroscopic assignments were obtained from five 3D chemical shift correlation experiments acquired on a single sample: CONCA, two NCACX experiments with dipoleassisted rotamer resonance (DARR)[18] mixing times of 20 ms and 50 ms, and two NCOCX experiments with DARR mixing times of 50ms and 100ms. While the CONCA spectrum provides nearly complete backbone resolution and establishes inter-residue correlations between CO [i], N [i+ 1], and CA-[i+ 1] atoms, the NCACX and NCOCX experiments allow to record chemical shifts of the side-chain carbon atoms for identification of the amino acid type. Shorter mixing time experiments provide mostly one-and two-bond correlations, for example, N [i+ 1]–CO [i]–CA [i] and N [i]–CA [i]–CO [i]/CB [i] in NCOCX and NCACX experiments, while longer mixing times establish shifts of the entire carbon side chain, and provide additional inter-residue correlations for assignment validation.