Introducing a CATALYST to Accelerate Native Affinity Selection Mass Spectrometry

Area of Science:

• Biochemistry
• Analytical Chemistry
• Computational Biology

Background:

• Multiplexed affinity selection electrospray mass spectrometry (MS) enables simultaneous measurement of ligand pools.
• Higher resolving power is needed for detecting protein-bound ligands, often requiring gas-phase ejection for high mass accuracy.
• Manual analysis of extracted ion chromatograms (EICs) for ligand identification is laborious and time-consuming.

Purpose of the Study:

• To develop an automated software solution for analyzing multiplexed affinity selection MS data.
• To accelerate the identification of protein-binding ligands from large compound libraries.
• To enable both targeted and untargeted analysis of ligand-protein interactions.

Main Methods:

• Development of CATALYST (Computer-Assisted Time Alignment for Ligand Yield and Screening Tool), an open-source software package.
• Implementation of statistical tests to correlate EICs and identify protein-binding ligands.
• Automated data processing for targeted and untargeted affinity selection MS experiments.

Main Results:

• CATALYST performs data analysis in seconds, significantly reducing processing time.
• The software accurately correlates EICs to identify protein-binding ligands.
• Visualizations are generated to aid in the interpretation of results.

Conclusions:

• CATALYST greatly accelerates affinity selection mass spectrometry workflows.
• The software provides a robust and efficient method for identifying potential drug candidates.
• CATALYST democratizes advanced MS data analysis through its open-source availability.