Biomolecular Modelling Laboratory, The Francis Crick Institute, London, UK.
Hadean Supercomputing Ltd, London, UK.
Proteins. 2020 Aug;88(8):962-972. doi: 10.1002/prot.25851. Epub 2019 Nov 20.
The formation of specific protein-protein interactions is often a key to a protein's function. During complex formation, each protein component will undergo a change in the conformational state, for some these changes are relatively small and reside primarily at the sidechain level; however, others may display notable backbone adjustments. One of the classic problems in the protein-docking field is to be able to a priori predict the extent of such conformational changes. In this work, we investigated three protocols to find the most suitable input structure conformations for cross-docking, including a robust sampling approach in normal mode space. Counterintuitively, knowledge of the theoretically best combination of normal modes for unbound-bound transitions does not always lead to the best results. We used a novel spatial partitioning library, Aether Engine (see Supplementary Materials), to efficiently search the conformational states of 56 receptor/ligand pairs, including a recent CAPRI target, in a systematic manner and selected diverse conformations as input to our automated docking server, SwarmDock, a server that allows moderate conformational adjustments during the docking process. In essence, here we present a dynamic cross-docking protocol, which when benchmarked against the simpler approach of just docking the unbound components shows a 10% uplift in the quality of the top docking pose.
特定蛋白质-蛋白质相互作用的形成通常是蛋白质功能的关键。在复合物形成过程中,每个蛋白质成分都会经历构象状态的变化,对于一些蛋白质来说,这些变化相对较小,主要存在于侧链水平;然而,其他蛋白质可能会显示出明显的骨架调整。在蛋白质对接领域的一个经典问题是能够先验地预测这种构象变化的程度。在这项工作中,我们研究了三种方案来为交叉对接找到最合适的输入结构构象,包括在正常模式空间中的稳健采样方法。反直觉的是,对于无约束-约束转变的最佳正常模式组合的知识并不总是导致最佳结果。我们使用了一种新的空间分区库,Aether Engine(见补充材料),以高效地搜索 56 个受体/配体对的构象状态,包括最近的 CAPRI 目标,以系统的方式,并选择多样化的构象作为输入到我们的自动化对接服务器 SwarmDock,该服务器允许在对接过程中进行适度的构象调整。从本质上讲,这里我们提出了一种动态交叉对接方案,与仅对接无约束成分的更简单方法相比,该方案在顶级对接构象的质量上提高了 10%。