Ion mobility-mass spectrometry of intact protein--ligand complexes for pharmaceutical drug discovery and development.

Mass spectrometry (MS) plays a number of key roles in the discovery and development phases for modern pharmaceutical compounds, ranging from the assessment of protein-ligand binding to biomarker discovery. Historically, however, MS has had a relatively limited role in the drug discovery process in comparison to high-throughput fluorescence and radiometric screens. This picture may be changing, however, as many presumptive protein targets are coupled to human disease pathways through specific protein-protein interactions and protein conformations, rather than enzyme activities. This fact will likely drive the development of high-throughput analytical tools that put a stronger emphasis on the structural information content produced in a screen. Here we summarize recent developments surrounding ion mobility-mass spectrometry (IM-MS), one such MS-based tool that is capable of rapidly measuring changes in protein structure, oligomeric state, and binding stoichiometry from complex mixtures at relatively low concentrations.

Activation state-selective kinase inhibitor assay based on ion mobility-mass spectrometry.

The discovery of activation state dependent kinase inhibitors, which bind specifically to the inactive conformation of the protein, is considered to be a promising pathway to improved cancer treatments. Identifying such inhibitors is challenging, however, because they can have Kd values similar to molecules known to inhibit kinase function by interacting with the active form. Further, while inhibitor induced changes within the kinase tertiary structure are significant, few technologies are able to correctly assign inhibitor binding modes in a high-throughput fashion based exclusively on protein-inhibitor complex formation and changes in local protein structure. We have developed a new assay, using ion mobility-mass spectrometry, capable of both rapidly detecting inhibitor binding and classifying the resultant kinase binding modes. Here, we demonstrate the ability of our approach to classify a broad set of kinase inhibitors, using micrograms of protein, without the need for protein modification or tagging.