Advancing Collision-Induced Affinity Selection Mass Spectrometry for Quantitative Ligand Analysis in Complex Mixtures
Xinru Xue1, Ronald J Quinn1, Bernd H A Rehm1,2
1Institute for Biomedicine and Glycomics, Griffith University, Southport, 4215 Gold Coast, Queensland, Australia.
Analytical Chemistry
|March 3, 2026
Summary
Collision-Induced Affinity Selection MS (CIAS-MS) offers enhanced detection and affinity ranking of protein-ligand interactions. This optimized platform accurately ranks ligands even in complex biological samples.
Area of Science:
- Biophysical Chemistry
- Analytical Chemistry
- Proteomics
Background:
- Native mass spectrometry (MS) allows studying protein-ligand interactions in solution.
- Collision-Induced Affinity Selection MS (CIAS-MS) enhances ligand detection and complex dissociation analysis.
- Existing methods face limitations in complex biological backgrounds.
Purpose of the Study:
- To optimize the CIAS-MS platform for improved ligand binding detection and affinity ranking.
- To integrate positive and negative ion modes for broader ligand detection.
- To introduce a robust parameter for quantitative affinity ranking.
Main Methods:
- Utilized optimized Collision-Induced Affinity Selection MS (CIAS-MS) platform.
- Integrated positive and negative ion modes for comprehensive ligand analysis.
- Introduced the collision-induced dissociation (CID) slope for affinity ranking.
Main Results:
- The dual ion mode approach broadened the detection of diverse ligands.
- The CID slope parameter accurately ranked ligand affinities in solution-phase.
- CIAS-MS demonstrated robustness in complex mixtures and bacterial lysates.
Conclusions:
- Optimized CIAS-MS provides robust detection and accurate affinity ranking of protein-ligand interactions.
- The CID slope is a reliable metric for affinity order, even in challenging samples.
- CIAS-MS is a scalable platform for high-throughput ligand discovery and proteome-wide studies.
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