Highly Selective and Potent Human β-Secretase 2 (BACE2) Inhibitors against Type 2 Diabetes: Design,Synthesis, X-ray Structure and Structure–Activity Relationship Studies

Herein we present the design, synthesis, and biological evaluation of potent and highly selective β-secretase 2 (memapsin 1, beta-site amyloid precursor protein cleaving enzyme 2, or BACE 2) inhibitors. BACE2 has been recognized as an exciting new target for type 2 diabetes. The X-ray structure of BACE1 bound to inhibitor 2 a {N³-[(1S,2R)-1-benzyl-2-hydroxy-3-[[(1S,2S)-2-hydroxy-1-(isobutylcarbamoyl)propyl]amino]propyl]-5-[methyl(methylsulfonyl)amino]-N¹-[(1R)-1-phenylpropyl]benzene-1,3-dicarboxamide} containing a hydroxyethylamine isostere was determined. Based on this structure, a computational docking study was performed which led to inhibitor 2 a -bound BACE2 models. These were used to optimize the potency and selectivity of inhibitors. A systematic structure–activity relationship study led to the identification of determinants of the inhibitors’ potency and selectivity toward the BACE2 enzyme. Inhibitors 2 d [N³-[(1S,2R)-1-benzyl-2-hydroxy-3-[[(1S,2S)-2-hydroxy-1-(isobutylcarbamoyl)pentyl]amino]propyl]-N¹-methyl-N¹-[(1R)-1-phenylpropyl]benzene-1,3-dicarboxamide; K_i=0.031 nm , selectivity over BACE1: ≈174 000-fold] and 3 l [N¹-((2S,3R)-3-hydroxy-1-phenyl-4-((3-(trifluoromethyl)benzyl)amino)butan-2-yl)-N³,5-dimethyl-N³-((R)-1-phenylethyl)isophthalamide; K_i=1.6 nm , selectivity over BACE1: >500-fold] displayed outstanding potency and selectivity. Inhibitor 3 l is nonpeptide in nature and may pave the way to the development of a new class of potent and selective BACE2 inhibitors with clinical potential.     

Integrating monitoring networks to obtain estimates of ground-level ozone concentrations --a proof of concept in Tuscany (central Italy)

Prior to 2000 a network of conventional ozone (O3) analysers existed in the Province of Firenze (Tuscany, central Italy). Between 2000 and 2004 the network was extended to incorporate a newly designed bioindicator network of tobacco plants (Nicotiana tabacum Bel W3). The objective was to set-up an integrated monitoring system to obtain estimates of ground-level O3 concentrations over the whole study area (3513 km2) in order to fill data gaps and cover reporting requirements. The existing conventional monitors were purposefully located mainly in urban areas. A total of 45 biomonitoring sites were selected using a systematic design to cover the target area. Two to five additional biomonitoring sites were co-located with conventional O3 analysers for calibration purposes, and five more sites for independent validation of modelled O3 concentrations. Visible Leaf Injury Index (LII) on the tobacco plants was significantly correlated (P: 0.018/0.0014) with a series of O3 exposure variables (mean of weekly 1-hour maxima, M1; mean of 7-hour means, M7; 24-hour mean, M24; and weekly AOT40). LII was found to be a significant predictor of weekly means of the O3 exposure variables with a standard error of estimates between 13.6 and 24.3 microg m(-3) (absolute values). LII was mapped with an ad-hoc spatial model over the study area at a 22 km grid resolution, and mapped values were used to predict O3 concentrations by means of a first order linear model. Results showed that high estimates of O3 (up to 188 microg m(-3) as mean of weekly maxima, M1) occurred more frequently in hilly and mountainous areas, with a spatial pattern changing on an annual basis. Predicted O3 concentrations were not significantly different from the measured concentrations (P: 0.34), although marked differences were observed for individual sites and years. The study provided evidence that integration of monitoring networks using different methods can be a viable option to obtain estimates of O3 concentrations over large areas.