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.
Comparing Selected-Ion Collision Induced Unfolding with All Ion Unfolding Methods for Comprehensive Protein Conformational Characterization.
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作者:Phetsanthad Ashley, Li Gongyu, Jeon Chae Kyung, Ruotolo Brandon T, Li Lingjun
| 期刊: | Journal of the American Society for Mass Spectrometry | 影响因子: | 2.700 |
| 时间: | 2022 | 起止号: | 2022 Jun 1; 33(6):944-951 |
| doi: | 10.1021/jasms.2c00004 | ||
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