Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA.
Bioinformatics. 2012 Dec 15;28(24):3282-9. doi: 10.1093/bioinformatics/bts628. Epub 2012 Oct 23.
Structural characterization of protein interactions is necessary for understanding and modulating biological processes. On one hand, X-ray crystallography or NMR spectroscopy provide atomic resolution structures but the data collection process is typically long and the success rate is low. On the other hand, computational methods for modeling assembly structures from individual components frequently suffer from high false-positive rate, rarely resulting in a unique solution.
Here, we present a combined approach that computationally integrates data from a variety of fast and accessible experimental techniques for rapid and accurate structure determination of protein-protein complexes. The integrative method uses atomistic models of two interacting proteins and one or more datasets from five accessible experimental techniques: a small-angle X-ray scattering (SAXS) profile, 2D class average images from negative-stain electron microscopy micrographs (EM), a 3D density map from single-particle negative-stain EM, residue type content of the protein-protein interface from NMR spectroscopy and chemical cross-linking detected by mass spectrometry. The method is tested on a docking benchmark consisting of 176 known complex structures and simulated experimental data. The near-native model is the top scoring one for up to 61% of benchmark cases depending on the included experimental datasets; in comparison to 10% for standard computational docking. We also collected SAXS, 2D class average images and 3D density map from negative-stain EM to model the PCSK9 antigen-J16 Fab antibody complex, followed by validation of the model by a subsequently available X-ray crystallographic structure.
蛋白质相互作用的结构特征对于理解和调节生物过程是必要的。一方面,X 射线晶体学或 NMR 光谱学提供了原子分辨率的结构,但数据收集过程通常很长,成功率很低。另一方面,用于从单个组件建模组装结构的计算方法通常存在高假阳性率,很少能得到唯一的解决方案。
在这里,我们提出了一种综合方法,该方法计算地整合了来自各种快速和易于获取的实验技术的数据,用于快速准确地确定蛋白质-蛋白质复合物的结构。该综合方法使用两个相互作用的蛋白质的原子模型和来自五种易于获取的实验技术的一个或多个数据集:小角度 X 射线散射(SAXS)谱、负染色电子显微镜照片(EM)的二维类平均图像、来自单粒子负染色 EM 的三维密度图、来自 NMR 光谱的蛋白质-蛋白质界面的残基类型含量和通过质谱检测到的化学交联。该方法在由 176 个已知复合物结构和模拟实验数据组成的对接基准测试中进行了测试。根据所包含的实验数据集,近天然模型在多达 61%的基准案例中得分最高;而标准计算对接的比例为 10%。我们还收集了 SAXS、2D 类平均图像和负染色 EM 的 3D 密度图,以构建 PCSK9 抗原-J16 Fab 抗体复合物的模型,然后通过随后获得的 X 射线晶体结构验证该模型。