Deep quantification of substrate turnover defines protease subsite cooperativity

Area of Science:

• Biochemistry
• Enzymology
• Proteomics

Background:

• Protease substrate specificity is crucial for biological functions and applications, but quantitative data is often limited.
• Dipeptidyl Peptidase Four (DPP4) is a key enzyme regulating blood glucose levels, making its specificity a significant research area.

Purpose of the Study:

• To develop a quantitative method, qPISA (quantitative Protease specificity Inference from Substrate Analysis), for profiling protease substrate specificity.
• To apply qPISA to Dipeptidyl Peptidase Four (DPP4) to understand its active pocket interactions and predict activity.

Main Methods:

• Utilized mass spectrometry to quantify over 40,000 peptides from a complex mixture.
• Analyzed quantitative changes in substrate levels to infer protease activity and specificity.
• Developed a sequence motif for quantitative prediction of enzyme activity.

Main Results:

• qPISA successfully profiled DPP4 specificity, revealing cooperative interactions within its active pocket.
• A quantitative sequence motif for DPP4 activity prediction was derived.
• Differentiated DPP4 from its C. elegans orthologue (DPF-3) based on specificity differences.
• Demonstrated qPISA's utility in directing protein engineering for stabilizing GLP-1, a DPP4 substrate.

Conclusions:

• qPISA provides a versatile and quantitative approach for profiling protease and exopeptidase specificity.
• This method offers insights into enzyme mechanisms and aids in biotechnological and clinical applications, including diabetes and obesity treatment.
• qPISA facilitates targeted protein engineering efforts for therapeutic substrates.