Mapping in vivo target interaction profiles of covalent inhibitors using chemical proteomics with label-free quantification.

Autor: van Rooden EJ; Department of Molecular Physiology, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., Florea BI; Department of Bioorganic Synthesis, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., Deng H; Department of Molecular Physiology, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., Baggelaar MP; Department of Molecular Physiology, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., van Esbroeck ACM; Department of Molecular Physiology, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., Zhou J; Department of Molecular Physiology, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., Overkleeft HS; Department of Bioorganic Synthesis, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands., van der Stelt M; Department of Molecular Physiology, Leiden Institute of Chemistry, Leiden University, Leiden, the Netherlands.
Jazyk: angličtina
Zdroj: Nature protocols [Nat Protoc] 2018 Apr; Vol. 13 (4), pp. 752-767. Date of Electronic Publication: 2018 Mar 22.
DOI: 10.1038/nprot.2017.159
Abstrakt: Activity-based protein profiling (ABPP) has emerged as a valuable chemical proteomics method to guide the therapeutic development of covalent drugs by assessing their on-target engagement and off-target activity. We recently used ABPP to determine the serine hydrolase interaction landscape of the experimental drug BIA 10-2474, thereby providing a potential explanation for the adverse side effects observed with this compound. ABPP allows mapping of protein interaction landscapes of inhibitors in cells, tissues and animal models. Whereas our previous protocol described quantification of proteasome activity using stable-isotope labeling, this protocol describes the procedures for identifying the in vivo selectivity profile of covalent inhibitors with label-free quantitative proteomics. The optimization of our protocol for label-free quantification methods results in high proteome coverage and allows the comparison of multiple biological samples. We demonstrate our protocol by assessing the protein interaction landscape of the diacylglycerol lipase inhibitor DH376 in mouse brain, liver, kidney and testes. The stages of the protocol include tissue lysis, probe incubation, target enrichment, sample preparation, liquid chromatography-mass spectrometry (LC-MS) measurement, data processing and analysis. This approach can be used to study target engagement in a native proteome and to identify potential off targets for the inhibitor under investigation. The entire protocol takes at least 4 d, depending on the number of samples.
Databáze: MEDLINE