| Literature DB >> 36178621 |
Aleš Holfeld1, Jan-Philipp Quast1, Roland Bruderer2, Lukas Reiter2, Natalie de Souza1,3, Paola Picotti4.
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 .Entities:
Keywords: LiP–Quant; LiP–SMap; Limited proteolysis; Machine learning; Mass spectrometry; Metabolite; Protein interactions; Proteomics; Structural proteomics
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Year: 2023 PMID: 36178621 DOI: 10.1007/978-1-0716-2624-5_6
Source DB: PubMed Journal: Methods Mol Biol ISSN: 1064-3745