Loss of diacylglycerol kinase ε causes thrombotic microangiopathy by impairing endothelial VEGFA signaling

Loss of function of the lipid kinase diacylglycerol kinase ε (DGKε), encoded by the gene DGKE, causes a form of atypical hemolytic uremic syndrome that is not related to abnormalities of the alternative pathway of the complement, by mechanisms that are not understood. By generating a potentially novel endothelial specific Dgke-knockout mouse, we demonstrate that loss of Dgke in the endothelium results in impaired signaling downstream of VEGFR2 due to cellular shortage of phosphatidylinositol 4,5-biphosphate. Mechanistically, we found that, in the absence of DGKε in the endothelium, Akt fails to be activated upon VEGFR2 stimulation, resulting in defective induction of the enzyme cyclooxygenase 2 and production of prostaglandin E2 (PGE2). Treating the endothelial specific Dgke-knockout mice with a stable PGE2 analog was sufficient to reverse the clinical manifestations of thrombotic microangiopathy and proteinuria, possibly by suppressing the expression of matrix metalloproteinase 2 through PGE2-dependent upregulation of the chemokine receptor CXCR4. Our study reveals a complex array of autocrine signaling events downstream of VEGFR2 that are mediated by PGE2, that control endothelial activation and thrombogenic state, and that result in abnormalities of the glomerular filtration barrier

Tailor-made computational protocols for precise characterization of small biological building blocks using QM and MM approaches

Computational modeling involving Quantum Mechanics (QM) and Molecular Mechanics (MM) calculations are widely utilized to unveil the atomic-molecular properties that underpin their inherent characteristic features. The choice over the either of the QM and MM methods or a multiscale composite approach is driven by the target property of interest, and of course, the molecular size. Often, tailor-made schemes need to be devised to match the specific study purpose. Herein, we provide a perspective of these approaches addressing their effectiveness in terms of the delicate balance between the accuracy and computational feasibility. We focus on representative examples to highlight how different approaches can be fruitfully exploited for modeling the conformational landscape, and possibly, the spectroscopic behavior of biochemical molecules, especially amino acids building blocks