1. TargetSeeker-MS: A Computational Method for Drug Target Discovery using Protein Separation Coupled to Mass Spectrometry
- Author
-
Salvador Martínez-Bartolomé, Mathieu Lavallée-Adam, Low W, James J. Moresco, Pinto Afm, Alexander R. Pelletier, Michael Petrascheck, Yates, and Jolene K. Diedrich
- Subjects
Drug ,0303 health sciences ,Thermal shift assay ,Chemistry ,media_common.quotation_subject ,Drug target ,Computational biology ,Proteomics ,Mass spectrometry ,3. Good health ,03 medical and health sciences ,0302 clinical medicine ,Protein purification ,Proteome ,030217 neurology & neurosurgery ,030304 developmental biology ,media_common - Abstract
When coupled to mass spectrometry (MS), energetics-based protein separation (EBPS) techniques, such as 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 rudimentary and significantly differ depending on the protocol used to produce the data. To identify drug targets in datasets produced using different EBPS-MS techniques, we have developed a novel flexible computational approach named TargetSeeker-MS. We showed that TargetSeeker-MS reproducibly identifies known and novel drug targets inC. elegansand HEK293 samples that were treated with the fungicide benomyl and processed using two different EBPS techniques. We also validated a novel benomyl target in vitro. TargetSeeker-MS, which is available online, allows for the confident identification of targets of a drug on a proteome scale, thereby facilitating the evaluation of its clinical viability.
- Published
- 2019