« Bacterial protease uses distinct thermodynamic signatures for substrate recognition »
Nature – Scientific Reports 7, article number: 2848 (2017)
Scientific Publication – published online on nature.com the
Link to the publication: doi:10.1038/s41598-017-03220-y
Authors
Gustavo Arruda Bezerra, Yuko Ohara-Nemoto, Irina Cornaciu, Sofiya Fedosyuk, Guillaume Hoffmann, Adam Round, José A. Márquez, Takayuki K. Nemoto & Kristina Djinović-Carugo
Arinax equipment quoted in the article
CrystalDirect® Automatic Crystal Harvester is quoted in this scientific publication. The CrystalDirect® is installed in the EMBL HTXLab (France, Grenoble) and works with a Cartesian PixSys robot (Cartesian Technologies, Irvine, USA) and a RockImager system (Formulatrix Inc., Bedford, USA).
Abstract
Porphyromonas gingivalis and Porphyromonas endodontalis are important bacteria related to periodontitis, the most common chronic inflammatory disease in humans worldwide. Its comorbidity with systemic diseases, such as type 2 diabetes, oral cancers and cardiovascular diseases, continues to generate considerable interest.
Surprisingly, these two microorganisms do not ferment carbohydrates; rather they use proteinaceous substrates as carbon and energy sources. However, the underlying biochemical mechanisms of their energy metabolism remain unknown. Here, we show that dipeptidyl peptidase 11 (DPP11), a central metabolic enzyme in these bacteria, undergoes a conformational change upon peptide binding to distinguish substrates from end products. It binds substrates through an entropy-driven process and end products in an enthalpy-driven fashion. We show that increase in protein conformational entropy is the main-driving force for substrate binding via the unfolding of specific regions of the enzyme (“entropy reservoirs”).
The relationship between our structural and thermodynamics data yields a distinct model for protein-protein interactions where protein conformational entropy modulates the binding free-energy. Further, our findings provide a framework for the structure-based design of specific DPP11 inhibitors.
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