4.8 Article

CIUSuite: A Quantitative Analysis Package for Collision Induced Unfolding Measurements of Gas-Phase Protein Ions

期刊

ANALYTICAL CHEMISTRY
卷 87, 期 22, 页码 11516-11522

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.5b03292

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资金

  1. National Science Foundation (CAREER) [1253384]
  2. University of Michigan Department of Chemistry
  3. University of Michigan Rackham Graduate School
  4. Rackham Merit Fellowship
  5. Direct For Mathematical & Physical Scien [1253384] Funding Source: National Science Foundation
  6. Division Of Chemistry [1253384] Funding Source: National Science Foundation

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Ion mobility-mass spectrometry (IM-MS) is a technology of growing importance for structural biology, providing complementary 3D structure information for biomolecules within samples that are difficult to analyze using conventional analytical tools through the near-simultaneous acquisition of ion collision cross sections (CCSs) and masses. Despite recent advances in IM-MS instrumentation, the resolution of closely related protein conformations remains challenging. Collision induced unfolding (CIU) has been demonstrated as a useful tool for resolving isocrossectional protein ions, as they often follow distinct unfolding pathways when subjected to collisional heating in the gas phase. CIU has been used for a variety of applications, from differentiating binding modes of activation state-selective kinase inhibitors to characterizing the domain structure of multidomain proteins. With the growing utilization of CIU as a tool for structural biology, significant challenges have emerged in data analysis and interpretation, specifically the normalization and comparison of CIU data sets. Here, we present CIUSuite, a suite of software modules designed for the rapid processing, analysis, comparison, and classification of CIU data. We demonstrate these tools as part of a series of workflows for applications in comparative structural biology, biotherapeutic analysis, and high throughput screening of kinase inhibitors. These examples illustrate both the potential for CIU in general protein analysis as well as a demonstration of best practices in the interpretation of CIU data.

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