Endothelial Cell-Derived Triosephosphate Isomerase Attenuates Insulin Secretion From Pancreatic Beta Cells of Male Rats.

Insulin secretion from pancreatic beta cells is tightly regulated by glucose and paracrine signals within the microenvironment of islets of Langerhans. Extracellular matrix from islet microcapillary endothelial cells (IMEC) affect beta-cell spreading and amplify insulin secretion. This study was aimed at investigating the hypothesis that contact-independent paracrine signals generated from IMEC may also modulate beta-cell insulin secretory functions. For this purpose, conditioned medium (CMp) preparations were prepared from primary cultures of rat IMEC and were used to simulate contact-independent beta cell-endothelial cell communication. Glucose-stimulated insulin secretion (GSIS) assays were then performed on freshly isolated rat islets and the INS-1E insulinoma cell line, followed by fractionation of the CMp, mass spectroscopic identification of the factor, and characterization of the mechanism of action. The IMEC-derived CMp markedly attenuated first- and second-phase GSIS in a time- and dose-dependent manner without altering cellular insulin content and cell viability. Size exclusion fractionation, chromatographic and mass-spectroscopic analyses of the CMp identified the attenuating factor as the enzyme triosephosphate isomerase (TPI). An antibody against TPI abrogated the attenuating activity of the CMp while recombinant human TPI (hTPI) attenuated GSIS from beta cells. This effect was reversed in the presence of tolbutamide in the GSIS assay. In silico docking simulation identified regions on the TPI dimer that were important for potential interactions with the extracellular epitopes of the sulfonylurea receptor in the complex. This study supports the hypothesis that an effective paracrine interaction exists between IMEC and beta cells and modulates glucose-induced insulin secretion via TPI-sulfonylurea receptor-KATP channel (SUR1-Kir6.2) complex attenuating interactions.

Activation of PPARδ: from computer modelling to biological effects.

PPARδ is a ligand-activated receptor that dimerizes with another nuclear receptor of the retinoic acid receptor family. The dimers interact with other co-activator proteins and form active complexes that bind to PPAR response elements and promote transcription of genes involved in lipid metabolism. It appears that various natural fatty acids and their metabolites serve as endogenous activators of PPARδ; however, there is no consensus in the literature on the nature of the prime activators of the receptor. In vitro and cell-based assays of PPARδ activation by fatty acids and their derivatives often produce conflicting results. The search for synthetic and selective PPARδ agonists, which may be pharmacologically useful, is intense. Current rational modelling used to obtain such compounds relies mostly on crystal structures of synthetic PPARδ ligands with the recombinant ligand binding domain (LBD) of the receptor. Here, we introduce an original computational prediction model for ligand binding to PPARδ LBD. The model was built based on EC50 data of 16 ligands with available crystal structures and validated by calculating binding probabilities of 82 different natural and synthetic compounds from the literature. These compounds were independently tested in cell-free and cell-based assays for their capacity to bind or activate PPARδ, leading to prediction accuracy of between 70% and 93% (depending on ligand type). This new computational tool could therefore be used in the search for natural and synthetic agonists of the receptor.