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.