To understand the mechanism of action of a drug and assess its clinical usefulness and viability, it is imperative that its affinity for its putative targets is determined. When coupled to mass spectrometry (MS), energetics-based protein separation (EBPS) techniques, such as a thermal shift assay, have shown great potential to identify the targets of a drug on a proteome scale. Nevertheless, the computational analyses assessing the confidence of drug-target predictions made by these methods have remained tightly tied to the protocol under which the data were produced. To identify drug targets in data sets produced using different EBPS-MS techniques, we have developed a novel flexible Bayesian inference approach named TargetSeeker-MS. We showed that TargetSeeker-MS identifies known and novel drug targets in