AutoClickChem: Click Chemistry in Silico

Academic researchers and many in industry often lack the financial resources available to scientists working in “big pharma.” High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu

Renal Perfusion and Hemodynamics: Accurate in Vivo Determination at CT with a 10-Fold Decrease in Radiation Dose and HYPR Noise Reduction1

The image quality of the one-tenth dose image, which was severely degraded by quantum noise, could be improved markedly to nearly the same level of the routine dose images by using the highly constrained back-projection-local reconstruction noise-reduction algorithm, without substantial loss of quantitative accuracy

Endothelial progenitor cells restore renal function in chronic experimental renovascular disease

Background—Endothelial progenitor cells (EPC) promote neovascularization and endothelial repair. Renal artery stenosis (RAS) may impair renal function by inducing intra-renal microvascular (MV) injury and remodeling. We investigated whether replenishment with EPC would protect the renal microcirculation in chronic experimental renovascular disease. Methods and results—Single-kidney hemodynamics and function were assessed using multidetector CT in-vivo in pigs with RAS, RAS 4 weeks after intra-renal infusion of autologous EPC, and controls. Renal MV remodeling and angiogenic pathways were investigated ex-vivo using micro- CT, histology, and Western-blotting. EPC increased renal expression of angiogenic factors, stimulated proliferation and maturation of new vessels, and attenuated renal MV remodeling and fibrosis in RAS. Furthermore, EPC normalized the blunted renal MV and filtration function. Conclusions—The current study shows that a single intra-renal infusion of autologous EPC preserved MV architecture and function and decreased MV remodeling in experimental chronic RAS. Likely, restoration of the angiogenic cascade by autologous EPC involved not only generation of new vessels, but also acceleration of their maturation and stabilization. This contributed to preserving the blood supply, hemodynamics, and function of the RAS kidney, supporting EPC as a promising therapeutic intervention for preserving the kidney in renovascular disease