Researchers at the Friedrich Miescher Institute (FMI) have developed an innovative tool that maps how proteases—enzymes that process proteins—interact with their targets. This tool sheds light on the highly selective nature of proteases, which were previously thought to be indiscriminate in their function. This discovery could revolutionize drug development for conditions like diabetes and obesity, paving the way for more stable and precise treatments.
Introducing qPISA: A New Tool for Understanding Protease Specificity
The Grosshans lab at FMI, known for its work on RNA and developmental timing, has developed a technique called qPISA (quantitative Protease specificity Inference from Substrate Analysis). This method offers a deeper understanding of proteases, which are highly selective enzymes. According to study lead author Helge Grosshans, proteases often target only specific proteins, challenging the previous perception of them as general degraders.
Decoding the Patterns: Cleavage Motifs
qPISA allows researchers to identify "cleavage motifs"—specific patterns in proteins that proteases target. Understanding these motifs can help design drugs that either enhance or inhibit protease activity, depending on therapeutic needs. This advancement is particularly relevant for conditions like type 2 diabetes and obesity.
Focusing on DPP4 and Its Role in Diabetes
The researchers applied qPISA to study DPP4, a protease critical for regulating blood sugar. DPP4 works by breaking down GLP-1, a hormone that controls blood sugar levels. Current treatments for type 2 diabetes and obesity either inhibit DPP4 or mimic GLP-1. Using qPISA, the team was able to predict the stability of DPP4’s protein targets. This knowledge enabled them to explore modifications to GLP-1, potentially extending its activity and effectiveness in the body.
Insights from Worm Enzymes: Studying DPF-3
The researchers also examined DPF-3, a related enzyme found in the worm *Caenorhabditis elegans*. Using cryo-electron microscopy, they determined its structure and found similarities with human DPP4. However, qPISA revealed unique specificity patterns in DPF-3, highlighting the complex interactions between proteases and their targets.
A Step Forward in Treatment Development
This work enhances our understanding of protease selectivity, potentially leading to more effective and long-lasting treatments for diabetes and obesity. “Our findings could significantly improve drug design by making treatments more stable and targeted,” Grosshans explains.
The study was conducted in collaboration with Rajani Gudipati from Adam Mickiewicz University in Poland and involved experts in computational biology, proteomics, and protein structure at FMI. The research was supported by the NCCR RNA & Disease initiative.
Original publication:
Rajani Kanth Gudipati, Dimos Gaidatzis, Jan Seebacher, Sandra Muehlhaeusser, Georg Kempf, Simone Cavadini, Daniel Hess, Charlotte Soneson & Helge Grosshans Deep quantification of substrate turnover defines protease subsite cooperativity Molecular Systems Biology (2024) Advance online publication
