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Acoustic Ejection Native Mass Spectrometry for High-Throughput Protein-Ligand Screening.

Aug 2026 · SLAS discovery : advancing life sciences R & D · pp. 100330 · 0 citations
Medicine

TL;DR

AEMS coupled to a high-resolution QTOF mass spectrometer as a high-throughput platform for nMS screening is demonstrated and acoustic ejection nMS is a practical high-throughput screening platform that simultaneously delivers direct molecular information on protein-ligand binding, binding stoichiometry, and protein oligomeric state.

Abstract

Native mass spectrometry (nMS) enables direct analysis of non-covalent protein-ligand interactions, providing information on binding affinity, stoichiometry, and protein oligomeric state. In drug discovery, nMS is widely used for mechanistic protein-ligand characterization and for confirming hits identified by orthogonal biochemical or biophysical assays. However, limited analytical throughput has restricted its use for screening compound libraries for non-covalent protein-ligand binding. Here, we demonstrate acoustic ejection mass spectrometry (AEMS) coupled to a high-resolution QTOF mass spectrometer as a high-throughput platform for nMS screening. SARS-CoV-2 main protease (Mpro) was used as a model system to evaluate the utility of AEMS for high-throughput screening. Well-resolved charge-state envelopes corresponding to the monomeric and dimeric forms of Mpro allowed for simultaneous assessment of ligand binding and protein oligomeric state. Non-covalent binders, including compounds that perturb the monomer-dimer equilibrium, were readily identified directly from native mass spectra. Analysis of a 1536-well screening plate was completed in approximately 1 h with an acquisition time of 2.5 s per well and excellent reproducibility across the plate. These results demonstrate that acoustic ejection nMS is a practical high-throughput screening platform that simultaneously delivers direct molecular information on protein-ligand binding, binding stoichiometry, and protein oligomeric state.

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