Department of Chemistry, University of Michigan, Ann Arbor, MI, 48109, USA.
J Am Soc Mass Spectrom. 2017 Oct;28(10):1991-2000. doi: 10.1007/s13361-017-1757-1. Epub 2017 Jul 27.
Multiprotein complexes are central to our understanding of cellular biology, as they play critical roles in nearly every biological process. Despite many impressive advances associated with structural characterization techniques, large and highly-dynamic protein complexes are too often refractory to analysis by conventional, high-resolution approaches. To fill this gap, ion mobility-mass spectrometry (IM-MS) methods have emerged as a promising approach for characterizing the structures of challenging assemblies due in large part to the ability of these methods to characterize the composition, connectivity, and topology of large, labile complexes. In this Critical Insight, we present a series of bioinformatics studies aimed at assessing the information content of IM-MS datasets for building models of multiprotein structure. Our computational data highlights the limits of current coarse-graining approaches, and compelled us to develop an improved workflow for multiprotein topology modeling, which we benchmark against a subset of the multiprotein complexes within the PDB. This improved workflow has allowed us to ascertain both the minimal experimental restraint sets required for generation of high-confidence multiprotein topologies, and quantify the ambiguity in models where insufficient IM-MS information is available. We conclude by projecting the future of IM-MS in the context of protein quaternary structure assignment, where we predict that a more complete knowledge of the ultimate information content and ambiguity within such models will undoubtedly lead to applications for a broader array of challenging biomolecular assemblies. Graphical Abstract ᅟ.
多蛋白复合物是我们理解细胞生物学的核心,因为它们在几乎每一个生物过程中都起着关键作用。尽管与结构特征技术相关的许多令人印象深刻的进展,大型和高度动态的蛋白质复合物往往难以通过传统的高分辨率方法进行分析。为了填补这一空白,离子淌度-质谱(IM-MS)方法已经成为一种很有前途的方法,可以用于研究具有挑战性的组装结构,这在很大程度上是因为这些方法能够描述大型、不稳定复合物的组成、连接性和拓扑结构。在这篇重要见解中,我们提出了一系列旨在评估 IM-MS 数据集在构建多蛋白结构模型方面的信息量的生物信息学研究。我们的计算数据突出了当前粗粒化方法的局限性,并促使我们开发了一种改进的多蛋白拓扑建模工作流程,我们将其与 PDB 中多蛋白复合物的子集进行了基准测试。这种改进的工作流程使我们能够确定生成高可信度多蛋白拓扑所需的最小实验约束集,并量化在可用的 IM-MS 信息不足的情况下模型中的歧义。最后,我们通过在蛋白质四级结构分配的背景下预测 IM-MS 的未来,预测到这些模型中最终信息内容和歧义的更完整的知识将无疑导致更广泛的具有挑战性的生物分子组装的应用。