Updated publication reference for PubMed record(s): 32690943. Mass spectrometry-based discovery proteomics is an essential tool for the proximal read-out of cellular drug action. Here, we used a robust proteomic workflow to rapidly and systematically profile the proteomes of five cell lines in response to > 50 drugs. We found that aggregating millions of quantitative protein-drug associations substantially improved the mechanism of action (MoA) deconvolution of single compounds. For example, MoA specificity increased after removal of proteins which frequently responded to drugs and the aggregation of proteome changes across multiple cell lines resolved compound effects on proteostasis. These characteristics were further leveraged to demonstrate efficient target identification of protein degraders. Moreover, we followed up on selected proteomic findings and showed that the inhibition of mitochondrial function is an off-target mechanism of the clinical MEK inhibitor PD184352 and that Ceritinib, an FDA approved drug in lung cancer, modulates autophagy. Overall, this study demonstrates that large-scale proteome perturbation profiling can be a useful addition to the drug discovery toolbox.