Abstract
Ion mobility-mass spectrometry (IM-MS) has become a technology deployed across a wide range of structural biology applications despite the challenges in characterizing closely related protein structures. Collision-induced unfolding (CIU) has emerged as a valuable technique for distinguishing closely related, iso-cross-sectional protein and protein complex ions through their distinct unfolding pathways in the gas phase. With the speed and sensitivity of CIU analyses, there has been a rapid growth of CIU-based assays, especially regarding biomolecular targets that remain challenging to assess and characterize with other structural biology tools. With information-rich CIU data, many software tools have been developed to automate laborious data analysis. However, with the recent development of new IM-MS technologies, such as cyclic IM-MS, CIU continues to evolve, necessitating improved data analysis tools to keep pace with new technologies and facilitating the automation of various data processing tasks. Here, we present CIUSuite 3, a software package that contains updated algorithms that support various IM-MS platforms and supports the automation of various data analysis tasks such as peak detection, multidimensional classification, and collision cross section (CCS) calibration. CIUSuite 3 uses local maxima searches along with peak width and prominence filters to detect peaks to automate CIU data extraction. To support both the primary CIU (CIU1) and secondary CIU (CIU2) experiments enabled by cyclic IM-MS, two-dimensional data preprocessing is deployed, which allows multidimensional classification. Our data suggest that additional dimensions in classification improve the overall accuracy of class assignments. CIUSuite 3 also supports CCS calibration for both traveling wave and drift tube IM-MS, and we demonstrate the accuracy of a new single-field CCS calibration method designed for drift tube IM-MS leveraging calibrant CIU data. Overall, CIUSuite 3 is positioned to support current and next-generation IM-MS and CIU assay development deployed in an automated format.
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