Profiling the Serine Hydrolase Superfamily using Activity-based Probes

Importance of the Topic

The serine hydrolase superfamily represents one of the largest and most diverse enzyme groups in eukaryotes, with critical roles in metabolism, signaling, and disease processes. Selective profiling of active serine hydrolases offers insights into enzyme regulation, inhibitor specificity, and functional dynamics in complex biological samples. Activity-based probes targeting the catalytic serine residue enable direct assessment of enzyme activity, overcoming limitations of expression-based approaches that cannot distinguish active from inactive zymogens.

Objectives and Study Overview

This study aimed to develop a global workflow for profiling serine hydrolase activity in mouse brain and liver lysates using fluorophosphonate (FP) probes. Key goals included evaluating inhibitor specificity, mapping active-site serine residues, and increasing the number of identified targets through optimized fragmentation strategies in mass spectrometry.

Methodology and Used Instrumentation

A combination of TAMRA-FP and desthiobiotin-FP probes was applied to label active serine hydrolases. Labeled proteins were visualized via fluorescent gel imaging and Western blotting, and active-site peptides were enriched using streptavidin capture after proteolytic digestion. LC–MS analysis was performed on a NanoLC-2D UPLC system coupled to a Thermo Scientific LTQ Orbitrap XL ETD mass spectrometer. A decision tree-driven method directed peptides to CID or ETD fragmentation based on charge state, enhancing sequence coverage and modification assignment.

Main Results and Discussion

Probe labeling differentiated active enzyme profiles between brain and liver tissues and confirmed inhibitor effects (URB597, CAY10401, AEBSF) on specific hydrolases such as FAAH. Mass spectrometry identified 25 active-site serine peptides across enzyme subclasses, with the CID/ETD decision tree increasing both the number of identifications and confidence in site localization, especially for peptides containing multiple serines.

Benefits and Practical Applications

This activity-based approach allows selective detection and quantification of active serine hydrolases in complex proteomes. It supports drug target validation, off-target profiling, and comparative studies of enzyme regulation in tissue-specific contexts, proving valuable for biochemical research and pharmaceutical development.

Future Trends and Applications

Advances may include integration with quantitative proteomics workflows, real-time activity imaging, and expansion to other enzyme families. Further optimization of probe chemistries and fragmentation algorithms will enhance throughput, sensitivity, and coverage of low-abundance targets.

Conclusion

The combination of FP-based probes and CID/ETD decision tree fragmentation enables comprehensive profiling of the serine hydrolase superfamily, mapping active sites, and analyzing inhibitor interactions in native tissue samples.

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