A matter of taste: The sweetner saccharin (a cyclic sulfimide, see picture) is nearly completely absorbed and eliminated through the urine, and is thus exposed to many different proteins in the body. It binds at nanomolar levels to some carbonic anhydrases and this provokes the question of its inert properties. It is known that the plasma level slowly decreases after oral dosing, and CAVI binding could explain its unpleasant metallic aftertaste.

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a b s t r a c tArabidopsis thaliana L. produces flavonoid pigments, i.e. flavonols, anthocyanidins and proanthocyanidins, from dihydroflavonol substrates. A small family of putative flavonol synthase (FLS) genes had been recognized in Arabidopsis, and functional activity was attributed only to FLS1. Nevertheless, other FLS activities must be present, because A. thaliana fls1 mutants still accumulate significant amounts of flavonols. The recombinant FLSs and leucoanthocyanidin dioxygenase (LDOX) proteins were therefore examined for their enzyme activities, which led to the identification of FLS3 as a second active FLS. This enzyme is therefore likely responsible for the formation of flavonols in the ldox/fls1-2 double mutant. These double mutant and biochemical data demonstrate for the first time that LDOX is capable of catalyzing the in planta formation of flavonols.

The predictive power of four commonly used in silico tools for mutagenicity prediction (DEREK, Toxtree, MC4PC, and Leadscope MA) was evaluated in a comparative manner using a large, high-quality data set, comprising both public and proprietary data (F. Hoffmann-La Roche) from 9,681 compounds tested in the Ames assay. Satisfactory performance statistics were observed on public data (accuracy, 66.4-75.4%; sensitivity, 65.2-85.2%; specificity, 53.1-82.9%), whereas a significant deterioration of sensitivity was observed in the Roche data (accuracy, 73.1-85.5%; sensitivity, 17.4-43.4%; specificity, 77.5-93.9%). As a general tendency, expert systems showed higher sensitivity and lower specificity when compared to QSAR-based tools, which displayed the opposite behavior. Possible reasons for the performance differences between the public and Roche data, relating to the experimentally inactive to active compound ratio and the different coverage of chemical space, are thoroughly discussed. Examples of peculiar chemical classes enriched in false negative or false positive predictions are given, and the results of the combined use of the prediction systems are described.

The multidrug resistance protein 1 (MDR1) is known to limit brain penetration of drugs and play a key role in drug-drug interactions (DDIs). Theoretical cut-offs from regulatory guidelines are used to extrapolate MDR1 interactions from in vitro to in vivo. However, these cut-offs do not account for interlaboratory variability. Our aim was to calibrate our experimental system to allow better in vivo predictions. We selected 166 central nervous system (CNS) and non-CNS drugs to calibrate the MDR1 transport screening assay using Lewis lung cancer porcine kidney 1 epithelial cells overexpressing MDR1 (L-MDR1). A threshold efflux ratio (ER) of 2 was established as one parameter to assess brain penetration in lead optimization. The inhibitory potential of 57 molecules was evaluated using IC 50 values based on the digoxin ER-IC 50 (ER)-or apparent permeability-IC 50 (P app )-in L-MDR1 cells. Published clinical data for 68 DDIs involving digoxin as the victim drug were collected. DDI risk assessments were based on intestinal concentrations ([I 2 ]) as well as unbound [I 1u ] and total plasma [I 1T ] concentrations. A receiver operating characteristic analysis identified an [I 2 ]/IC 50 (ER) of 6.5 as the best predictor of a potential interaction with digoxin in patients. The model was further evaluated with a test set of 11 digoxin DDIs and 16 nondigoxin DDIs, resulting in only one false negative for each test set, no false positives among the digoxin DDIs, and two among the nondigoxin DDIs. Future refinements might include using cerebrospinal fluid to unbound plasma concentration ratios rather than therapeutic class, better estimation of [I 2 ], and dynamic modeling of MDR1-mediated DDIs.