Disentangling conformational states of macromolecules in 3D-EM through likelihood optimization
Disentangling conformational states of macromolecules in 3D-EM through likelihood optimization
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DOI：
10.1038/nmeth992
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发表时间：
2007-01-01
期刊：
影响因子：
48
通讯作者：
Carazo, Jose-Maria
中科院分区：
文献类型：
--
作者：
Scheres, Sjors H. W.;Gao, Haixiao;Carazo, Jose-Maria
尽管三维电子显微镜（3D-EM）允许在不同功能状态下对大分子组件进行结构表征，但无法对结构异质样品的投影进行分类严重限制了其应用。我们提出了一种基于最大似然的分类方法，该方法不依赖于结构变异性的先验知识，并证明了其对两种具有不同类型构象变异性的大分子组合的有效性：大肠杆菌核糖体和类人猿病毒40 （SV40）大t抗原。
Although three-dimensional electron microscopy (3D-EM) permits structural characterization of macromolecular assemblies in distinct functional states, the inability to classify projections from structurally heterogeneous samples has severely limited its application. We present a maximum likelihood-based classification method that does not depend on prior knowledge about the structural variability, and demonstrate its effectiveness for two macromolecular assemblies with different types of conformational variability: the Escherichia coli ribosome and Simian virus 40 (SV40) large T-antigen.