Proteolysis constitutes a major post-translational modification but specificity and substrate selectivity of numerous proteases have remained elusive. In this review, we highlight how advanced techniques in the areas of proteomics and activity-based probes can be used to investigate i) protease active site specificity; ii) protease in vivo substrates; iii) protease contribution to proteome homeostasis and composition; and iv) detection and localization of active proteases. Peptide libraries together with genetical or biochemical selection have traditionally been used for active site profiling of proteases. These are now complemented by proteome-derived peptide libraries that simultaneously determine prime and non-prime specificity and characterize subsite cooperativity. Cell-contextual discovery of protease substrates is rendered possible by techniques that isolate and quantitate protein termini. Here, a novel approach termed Terminal Amine Isotopic Labeling of Substrates (TAILS) provides an integrated platform for substrate discovery and appropriate statistical evaluation of terminal peptide identification and quantification. Proteolytically generated carboxy-termini can now also be analyzed on a proteome-wide level. Proteolytic regulation of proteome composition is monitored by quantitative proteomic approaches employing stable isotope coding or label free quantification. Activity-based probes specifically recognize active proteases. In proteomic screens, they can be used to detect and quantitate proteolytic activity while their application in cellular histology allows to locate proteolytic activity in situ. Activity-based probes - especially in conjunction with positron emission tomography - are also promising tools to monitor proteolytic activities on an organism-wide basis with a focus on in vivo tumor imaging. Together, this array of methodological possibilities enables unveiling physiological protease substrate repertoires and defining protease function in the cellular- and organism-wide context.
- Substrate profiling