Ion Mobility-Mass Spectrometry Coupled to Droplet Microfluidics for Rapid Protein Structure Analysis and Drug Discovery

• Published in: Analytical chemistry (Washington) Vol. 94; no. 38; pp. 13084 - 13091
• Main Authors: D’Amico, Cara I., Polasky, Daniel A., Steyer, Daniel J., Ruotolo, Brandon T., Kennedy, Robert T.
• Format: Journal Article
• Language: English
• Published: Washington American Chemical Society 27.09.2022
• Subjects: Algorithms; Analytical chemistry; Binders; Binding; Chemistry; Data acquisition; Data collection; Droplets; Dwell time; Dynamic structural analysis; Fingerprinting; Interpolation; Ionic mobility; Ions; Ligands; Mass spectrometry; Mass spectroscopy; Microfluidics; Mobility; Protein structure; Proteins; Scientific imaging; Spectroscopy; Workflow
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.2c02307

Native mass spectrometry coupled to ion mobility (IM-MS) has become an important tool for the investigation of protein structure and dynamics upon ligand binding. Additionally, collisional activation or collision induced unfolding (CIU) can further probe conformational changes induced by ligand binding; however, larger scale screens have not been implemented due to limitations associated with throughput and sample introduction. In this work we explore the high-throughput capabilities of CIU fingerprinting. Fingerprint collection times were reduced 10-fold over traditional data collections through the use of improved smoothing and interpolation algorithms. Fast-CIU was then coupled to a droplet sample introduction approach using 40 nL droplet sample volumes and 2 s dwell times at each collision voltage. This workflow, which increased throughput by ∼16-fold over conventional nanospray CIU methods, was applied to a 96-compound screen against Sirtuin-5, a protein target of clinical interest. Over 20 novel Sirtuin-5 binders were identified, and it was found that Sirtuin-5 inhibitors will stabilize specific Sirtuin-5 gas-phase conformations. This work demonstrates that droplet-CIU can be implemented as a high-throughput biophysical characterization approach. Future work will focus on improving the throughput of this workflow and on automating data acquisition and analysis.