Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06520, USA; School of Computer and Information Technology, Beijng Jiaotong University, Beijing 100044, China.
Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06520, USA.
J Struct Biol. 2014 Mar;185(3):295-302. doi: 10.1016/j.jsb.2014.01.004. Epub 2014 Jan 24.
Random spherically constrained (RSC) single particle reconstruction is a method to obtain structures of membrane proteins embedded in lipid vesicles (liposomes). As in all single-particle cryo-EM methods, structure determination is greatly aided by reliable detection of protein "particles" in micrographs. After fitting and subtraction of the membrane density from a micrograph, normalized cross-correlation (NCC) and estimates of the particle signal amplitude are used to detect particles, using as references the projections of a 3D model. At each pixel position, the NCC is computed with only those references that are allowed by the geometric constraint of the particle's embedding in the spherical vesicle membrane. We describe an efficient algorithm for computing this position-dependent correlation, and demonstrate its application to selection of membrane-protein particles, GluA2 glutamate receptors, which present very different views from different projection directions.
随机球约束（RSC）单颗粒重建是一种获取嵌入脂质体（脂质体）中的膜蛋白结构的方法。与所有单颗粒冷冻电镜方法一样，可靠地检测显微镜照片中的蛋白质“颗粒”极大地有助于结构确定。在从显微照片中拟合和减去膜密度之后，使用归一化互相关（NCC）和颗粒信号幅度的估计值来检测颗粒，使用 3D 模型的投影作为参考。在每个像素位置，仅使用球形囊泡膜中颗粒嵌入的几何约束允许的那些参考来计算 NCC。我们描述了一种用于计算这种位置相关相关性的有效算法，并展示了其在选择膜蛋白颗粒 GluA2 谷氨酸受体中的应用，该受体从不同的投影方向呈现出非常不同的视图。
