School of Computer Science and Engineering and the Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
Methods Mol Biol. 2020;2112:163-174. doi: 10.1007/978-1-0716-0270-6_12.
Macromolecular complexes play a key role in cellular function. Predicting the structure and dynamics of these complexes is one of the key challenges in structural biology. Docking applications have traditionally been used to predict pairwise interactions between proteins. However, few methods exist for modeling multi-protein assemblies. Here we present two methods, CombDock and DockStar, that can predict multi-protein assemblies starting from subunit structural models. CombDock can assemble subunits without any assumptions about the pairwise interactions between subunits, while DockStar relies on the interaction graph or, alternatively, a homology model or a cryo-electron microscopy (EM) density map of the entire complex. We demonstrate the two methods using RNA polymerase II with 12 subunits and TRiC/CCT chaperonin with 16 subunits.
大分子复合物在细胞功能中起着关键作用。预测这些复合物的结构和动力学是结构生物学的关键挑战之一。对接应用程序传统上用于预测蛋白质之间的成对相互作用。然而,用于建模多蛋白组装的方法很少。在这里,我们提出了两种方法,即 CombDock 和 DockStar,它们可以从亚基结构模型开始预测多蛋白组装。CombDock 可以在不考虑亚基之间的成对相互作用的情况下组装亚基,而 DockStar 则依赖于相互作用图,或者是整个复合物的同源模型或低温电子显微镜 (EM) 密度图。我们使用含有 12 个亚基的 RNA 聚合酶 II 和含有 16 个亚基的 TRiC/CCT 伴侣蛋白来演示这两种方法。