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Deep quantification of substrate turnover defines protease subsite cooperativity

ABSTRACT: 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 >40,000 peptides from a complex, commercially available peptide mixture. By analyzing changes in substrate levels quantitatively instead of focusing on qualitative product identification through a binary classifier, we can reveal cooperative interactions within DPP4's 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.

SUBMITTER: Rajani, Kanth Gudipati

PROVIDER: S-SCDT-10_1038-S44320-024-00071-4 | biostudies-other |

REPOSITORIES: biostudies-other

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Deep quantification of substrate turnover definesprotease subsite cooperativity. Working title: Massively parallel mapping of dipeptidyl peptidase cleavage sites reveals substrate motifs

Project description:Proteases play a crucial role in processing or breaking down proteins. They exhibit varying levels of substrate specificity that determine their physiological or pharmacological functions. However, this specificity is not well-understood. To address this, we have developed hiMAPS (high-throughput mapping of protease cleavage sites), a mass spectrometry-based method that can survey tens of thousands of distinct peptides. By applying this approach to human DPP4 and C. elegans DPF-3, two prolyl peptidases from the Dipeptidyl Peptidase IV (DPPIV) family, we have derived quantitative models that confirm a strong preference for Pro and Ala in the penultimate (P1) position from the N-terminus, but also reveal differences in the relative preferences for other residues. The hiMAPS approach can be applied to other exoproteases using various cheap sources of highly diverse peptides. Additionally, we have observed that these proteases tolerate and accept substrates containing Thr and Ser at P1 position.

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SARS-CoV 3CL protease cleaves its C-terminal autoprocessing site by novel subsite cooperativity.

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