In Methods in molecular biology (Clifton, N.J.)
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 .
Holfeld Aleš, Quast Jan-Philipp, Bruderer Roland, Reiter Lukas, de Souza Natalie, Picotti Paola
LiP–Quant, LiP–SMap, Limited proteolysis, Machine learning, Mass spectrometry, Metabolite, Protein interactions, Proteomics, Structural proteomics