Abstract
Metabolite–protein interactions regulate diverse cellular processes, prompting the development of methods to investigate the metabolite–protein interactome at a global scale. One such method is our previously developed structural proteomics approach, limited proteolysis–mass spectrometry (LiP–MS), which detects proteome-wide metabolite–protein and drug–protein interactions in native bacterial, yeast, and mammalian systems, and allows identification of binding sites without chemical modification. Here we describe a detailed experimental and analytical workflow for conducting a LiP–MS experiment to detect small molecule–protein interactions, either in a single-dose (LiP–SMap) or a multiple-dose (LiP–Quant) format. LiP–Quant analysis combines the peptide-level resolution of LiP–MS with a machine learning-based framework to prioritize true protein targets of a small molecule of interest. We provide an updated R script for LiP–Quant analysis via a GitHub repository accessible at https://github.com/RolandBruderer/MiMB-LiP-Quant.
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Acknowledgments
This work was supported by the European Research Council (grant agreement no. 866004), the EPIC-XS Consortium (grant agreement no. 823839), a Sinergia grant from the Swiss National Science Foundation (SNSF grant CRSII5_177195), the National Center of Competence in Research AntiResist and the Promedica Stiftung, Chur.
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Holfeld, A., Quast, JP., Bruderer, R., Reiter, L., de Souza, N., Picotti, P. (2023). Limited Proteolysis–Mass Spectrometry to Identify Metabolite–Protein Interactions. In: Skirycz, A., Luzarowski, M., Ewald, J.C. (eds) Cell-Wide Identification of Metabolite-Protein Interactions. Methods in Molecular Biology, vol 2554. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2624-5_6
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DOI: https://doi.org/10.1007/978-1-0716-2624-5_6
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