Massively parallel mapping of substrate cleavage sites defines dipeptidyl peptidase four subsite cooperativity
Substrate specificity determines protease functions in physiology and in clinical and biotechnological application, yet quantitative cleavage information is often unavailable, biased, or limited to a small number of events. Here, we develop qPISA (quantitative Protease specificity Inference from Substrate Analysis) to study Dipeptidyl Peptidase Four (DPP4), a key regulator of blood glucose levels. We use mass spectrometry to quantify its effects on >40,000 peptides from a complex, commercially available peptide mixture. By determining substrate turnover instead of focusing on product identification, we can reveal cooperative interactions within DPP4s active pocket and derive a sequence motif that predicts activity quantitatively. qPISA distinguishes DPP4 from the related C. elegans DPF-3 (a DPP8/9 orthologue), and we relate the differences to structural features of the two enzymes. We demonstrate that qPISA can direct protein engineering efforts like stabilization of GLP-1, a key DPP4 substrate used in treatment of diabetes and obesity. Thus, qPISA offers a versatile approach for profiling protease and especially exopeptidase specificity, facilitating insight into enzyme mechanisms and biotechnological and clinical applications.