TargetSeeker-MS: A Bayesian Inference Approach for Drug–Target Discovery Using Protein Fractionation Coupled to Mass Spectrometry

• DOI: 10.1021/jasms.4c00269
• Publication Date: 2025-03-11T17:43:16Z
• Authors: Mathieu Lavallée-...; Alexander Pelletier; Jolene K. Diedrich; Antonio F. M. Pinto; Salvador Martínez...; Michael Petrascheck; James J. Moresco; John R. Yates

To understand the mechanism of action a drug and assess its clinical usefulness viability, it is imperative that affinity for putative targets determined. When coupled to mass spectrometry (MS), energetics-based protein separation (EBPS) techniques, such as thermal shift assay, have shown great potential identify on proteome scale. Nevertheless, computational analyses assessing confidence drug–target predictions made by these methods remained tightly tied protocol under which data were produced. in sets produced using different EBPS-MS we developed novel flexible Bayesian inference approach named TargetSeeker-MS. We showed TargetSeeker-MS identifies known Caenorhabditis elegans HEK 293 samples treated with fungicide benomyl. also demonstrated TargetSeeker-MS' identifications are reproducible C. processed two EBPS techniques (thermal assay differential precipitation proteins, DiffPOP). In addition, validated benomyl target measuring altered enzymatic activity upon treatment vitro. TargetSeeker-MS, available web server (https://targetseeker.scripps.edu/), allows rapid, versatile, confident identification scale, thereby providing better understanding mechanisms facilitating evaluation viability.