ABSTRACT:Substrates of aldehyde oxidase (AO), for which human clinical pharmacokinetics are reported, were selected and evaluated in pooled mixed-gender cryopreserved human hepatocytes in an effort to quantitatively characterize AO activity. confirmed that the predominant oxidative metabolite was generated by AO, as expected isotope patterns in mass spectra were observed after analysis by high-resolution mass spectrometry. Second, clearance values were efficiently attenuated upon coincubation with hydralazine, an inhibitor of AO. The low exposure after oral doses of BIBX1382 and carbazeran (ϳ5% F) would have been fairly well predicted using simple hepatic extraction (f h ) values derived from cryopreserved hepatocytes. In addition, the estimated hepatic clearance value for O 6 -benzylguanine was within ϳ80% of the observed total clearance in humans after intravenous administration (15 ml ⅐ min ؊1 ⅐ kg ؊1 ), indicating a reasonable level of quantitative activity from this in vitro system. However, a 3.5-fold underprediction of total clearance was observed for zaleplon, despite the 5-oxo metabolite being clearly observed. These data taken together suggest that the use of cryopreserved hepatocytes may be a practical approach for assessing AO-mediated metabolism in discovery and potentially useful for predicting hepatic clearance of AO substrates.

A back-propagation artificial neural network (ANN) was used to create a 10-fold leave-10%-out cross-validated ensemble model of high performance liquid chromatography retention index (HPLC-RI) for a data set of 498 diverse druglike compounds. A 10-fold multiple linear regression (MLR) ensemble model of the same data was developed for comparison. Molecular structure was described using IGroup E-state indices, a novel set of structure-information representation (SIR) descriptors, along with molecular connectivity chi and kappa indices and other SIR descriptors previously reported. The same input descriptors were used to develop models by both learning algorithms. The MLR model yielded marginally acceptable statistics with training correlation r(2) = 0.65, mean absolute error (MAE) = 83 RI units. External validation of 104 compounds not used for model development yielded validation v(2) = 0.49 and MAE = 73 RI units. The distribution of residuals for the fit and validate data sets suggest a nonlinear relationship between retention index and molecular structure as described by the SIR indices. Not surprisingly, the ANN model was significantly more accurate for both training and validation with training set r(2) = 0.93, MAE = 30 RI units and validation v(2) = 0.84, MAE = 41 RI units. For the ANN model, a total of 91% of validation predictions were within 100 RI units of the experimental value.

RATIONALE The determination of the center-of-mass energy at which 50% of a precursor ion decomposes (Ecom50) during collision-induced dissociation (CID) is dependent on the chemical structure of the ion as well as the physical and electrical characteristics of the collision cell. The current study was designed to identify variables influencing Ecom50 values measured on four different mass spectrometers. METHODS Fifteen test compounds were protonated using +ve electrospray ionization and the resulting ions were fragmented across a range of collision energies by CID. Survival yield versus collision energy curves were then used to calculate Ecom50 values for each of these [M+H]+ ions on four different mass spectrometers. In addition, the relative recovery of the [M+H]+ ions of eight compounds ranging in molecular weight from 46 to 854 Da were determined at collision cell RF voltages ranging from 0 to 600 V. RESULTS Ecom50 values determined on the four instruments were highly correlated (r2 values ranged from 0.953 to 0.992). Although these overall correlations were high, we found different maximum ion recoveries depending on collision cell RF voltage. High mass ions had greater recovery at higher collision cell RF voltages, whereas low mass ions had greater recovery at lower collision cell RF voltages as well as a broader range of ion recoveries. CONCLUSIONS Ecom50 values measured on four different instruments correlated surprisingly well given the differences in electrical and physical characteristics of the collision cells. However, our results suggest caution when comparing Ecom50 values or CID spectra between instruments without correcting for the effects of RF voltage on ion transfer efficiency.

MS and HPLC are commonly used for compound characterization and obtaining structural information; in the field of metabonomics, these two analytical techniques are often combined to characterize unknown endogenous or exogenous metabolites present in complex biological samples. Since the structures of a majority of these metabolites are not actually identified, the result of most metabonomic studies is a list of m/z values and retention times. However, without knowing actual structures, the biological significance of these 'features' cannot be determined. The process of identifying the structures of unknown compounds can be time intensive, costly and frequently requires the use of multiple orthogonal analytical techniques - this laborious procedure seems insurmountable for the long lists of unknowns that must be identified for each study. In addition, the limited sample volume and the extremely low concentration of most endogenous analytes frequently make purification and identification by other instrumentation nearly impossible. This review is intended to explore the problems and progress with current tools that are available for MS-based structure identification for both endogenous and exogenous metabolites.

Chymase plays an important and diverse role in the homeostasis of a number of cardiovascular processes. Herein, we describe the identification of potent, selective chymase inhibitors, developed using fragment-based, structure-guided linking and optimization techniques. High-concentration biophysical screening methods followed by high-throughput crystallography identified an oxindole fragment bound to the S1 pocket of the protein exhibiting a novel interaction pattern hitherto not observed in chymase inhibitors. X-ray crystallographic structures were used to guide the elaboration/linking of the fragment, ultimately leading to a potent inhibitor that was >100-fold selective over cathepsin G and that mitigated a number of liabilities associated with poor physicochemical properties of the series it was derived from.

ABSTRACT:The current studies assessed the utility of freshly plated hepatocytes, cryopreserved plated hepatocytes, and cryopreserved plated HepaRG cells for the estimation of inactivation parameters k inact and K I for CYP3A. This was achieved using a subset of CYP3A time-dependent inhibitors (fluoxetine, verapamil, clarithromycin, troleandomycin, and mibefradil) representing a range of potencies.

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