CIUSuite 2: Next-Generation Software for the Analysis of Gas-Phase Protein Unfolding Data
CIUSuite 2: Next-Generation Software for the Analysis of Gas-Phase Protein Unfolding Data
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DOI：
10.1021/acs.analchem.8b05762
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发表时间：
2019-02-19
影响因子：
7.4
通讯作者：
Ruotolo, Brandon T.
中科院分区：
文献类型：
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作者：
Polasky, Daniel A.;Dixit, Sugyan M.;Ruotolo, Brandon T.
离子迁移率质谱（IM-MS）已成为结构生物学工具箱的重要补充，但分离密切相关的蛋白质构象仍然具有挑战性。碰撞诱导去折叠（CIU）已成为一种有价值的技术，用于区分等截面蛋白质和蛋白质复合物离子，通过其不同的去折叠途径在气相中。CIU分析的速度和灵敏度，加上其信息丰富的数据集，导致CIU应用的快速增长，从蛋白质复合物的结构评估到生物治疗药物的表征。尽管信息学工具处理CIU实验产生的复杂数据集的能力滞后，但这种增长仍然存在，导致费力的手动分析仍然司空见惯。在这里，我们介绍了CIUSuite 2，一个软件套件，旨在实现强大的，自动化的分析CIU数据在整个范围内的当前CIU应用程序，并支持实施CIU作为一个真正的高通量技术。CIUSuite 2使用统计拟合和建模方法来可靠地量化CIU数据集内的感兴趣特征，特别是在无法用现有分析工具解释的信号质量差的数据中。通过降低处理CIU数据的信噪比要求，我们能够证明与当前工作流程相比，采集时间减少了2个数量级。CIUSuite 2还提供了第一个用于分类CIU指纹的自动化系统，使下一代配体筛选和结构分析实验能够以高通量方式完成。
Ion mobility-mass spectrometry (IM-MS) has become an important addition to the structural biology toolbox, but separating closely related protein conformations remain challenging. Collision-induced unfolding (CIU) has emerged as a valuable technique for distinguishing iso-cross-sectional protein and protein complex ions through their distinct unfolding pathways in the gas phase. The speed and sensitivity of CIU analyses, coupled with their information-rich data sets, have resulted in the rapid growth of CIU for applications, ranging from the structural assessment of protein complexes to the characterization of biotherapeutics. This growth has occurred despite a lag in the capabilities of informatics tools available to process the complex data sets generated by CIU experiments, resulting in laborious manual analysis remaining commonplace. Here, we present CIUSuite 2, a software suite designed to enable robust, automated analysis of CIU data across the complete range of current CIU applications and to support the implementation of CIU as a true high-throughput technique. CIUSuite 2 uses statistical fitting and modeling methods to reliably quantify features of interest within CIU data sets, particularly in data with poor signal quality that cannot be interpreted with existing analysis tools. By reducing the signal-to-noise requirements for handling CIU data, we are able to demonstrate reductions in acquisition time of up to 2 orders of magnitude over current workflows. CIUSuite 2 also provides the first automated system for classifying CIU fingerprints, enabling the next generation of ligand screening and structural analysis experiments to be accomplished in a high-throughput fashion.