Department of Chemistry and School of Pharmacy, University of Wisconsin─Madison, Madison, Wisconsin 53705, United States.
Research Center for Analytical Science and Tianjin Key Laboratory of Biosensing and Molecular Recognition, College of Chemistry, Nankai University, Tianjin 300071, China.
J Am Soc Mass Spectrom. 2022 Jun 1;33(6):944-951. doi: 10.1021/jasms.2c00004. Epub 2022 May 4.
Structural analysis by native ion mobility-mass spectrometry provides a direct means to characterize protein interactions, stability, and other biophysical properties of disease-associated biomolecules. Such information is often extracted from collision-induced unfolding (CIU) experiments, performed by ramping a voltage used to accelerate ions entering a trap cell prior to an ion mobility separator. Traditionally, to simplify data analysis and achieve confident ion identification, precursor ion selection with a quadrupole is performed prior to collisional activation. Only one charge state can be selected at one time, leading to an imbalance between the total time required to survey CIU data across all protein charge states and the resulting structural analysis efficiency. Furthermore, the arbitrary selection of a single charge state can inherently bias CIU analyses. We herein aim to compare two conformation sampling methods for protein gas-phase unfolding: (1) traditional quadrupole selection-based CIU and (2) nontargeted, charge selection-free and shotgun workflow, all ion unfolding (AIU). Additionally, we provide a new data interpretation method that integrates across all charge states to project collisional cross section (CCS) data acquired over a range of activation voltages to produce a single unfolding fingerprint, regardless of charge state distributions. We find that AIU in combination with CCS accumulation across all charges offers an opportunity to maximize protein conformational information with minimal time cost, where additional benefits include (1) an improved signal-to-noise ratios for unfolding fingerprints and (2) a higher tolerance to charge state shifts induced by either operating parameters or other factors that affect protein ionization efficiency.
通过天然离子淌度-质谱分析提供了一种直接的方法来表征与疾病相关的生物分子的蛋白质相互作用、稳定性和其他生物物理特性。这些信息通常是从碰撞诱导解折叠 (CIU) 实验中提取的，该实验通过在离子进入离子迁移率分离器之前逐渐增加用于加速离子的电压来进行。传统上，为了简化数据分析并实现可靠的离子识别，在进行碰撞激活之前，使用四极杆进行前体离子选择。一次只能选择一种电荷状态，导致在调查所有蛋白质电荷状态的 CIU 数据所需的总时间和由此产生的结构分析效率之间存在不平衡。此外，任意选择单一电荷状态可能会固有地偏向 CIU 分析。我们旨在比较两种蛋白质气相展开的构象采样方法：（1）传统的基于四极杆选择的 CIU 和（2）无目标、无电荷选择和 shotgun 工作流程、全离子展开 (AIU)。此外，我们提供了一种新的数据解释方法，该方法可整合所有电荷状态，以预测在一系列激活电压下获得的碰撞截面 (CCS) 数据，从而生成单个展开指纹，而无需考虑电荷状态分布。我们发现，AIU 与所有电荷的 CCS 累积相结合，提供了以最小的时间成本最大化蛋白质构象信息的机会，其额外的好处包括：（1）提高展开指纹的信噪比，以及（2）对由操作参数或影响蛋白质电离效率的其他因素引起的电荷状态变化具有更高的容忍度。
