SVM classification and CoMSIA modeling of UGT1A6 interacting molecules.

The human UDP-glucuronosyltransferase 1A6 (UGT1A6) plays important roles in elimination of many xenobiotics, including drugs. We have experimentally assessed inhibitory properties of 46 compounds toward UGT1A6 catalyzing the glucuronidation of 1-naphthol and built models for predicting compounds interactions with the enzyme. The tested compounds were divided into a training set (n = 31; evaluated by 10-fold cross-validation) and an external test set (n = 15), both of which yielded similar accuracies (80-81%) and Matthews correlation coefficients (0.61-0.63) when classified using support vector machines. Comparative molecular similarity index analysis (CoMSIA) modeling was conducted for nine methods of compound alignment. The most predictive CoMSIA model was analyzed in the light of a homology modeled UGT1A6 structure, with leave-one-out cross-validation, yielding a q² of 0.62 and r² of 0.91 on the training set and a r²(pred) of 0.82 on the test set. The CoMSIA contour plots highlighted the importance of H-bond donors and electrostatic field interactions, accounting for 28% and 25% contribution of the model, respectively.

Highly variable pH effects on the interaction of diclofenac and indomethacin with human UDP-glucuronosyltransferases.

In vitro glucuronidation assays of diclofenac and indomethacin at pH 7.4 are biased by the instability of the glucuronides due to acyl migration. The extent of this acyl migration may be reduced significantly by performing the glucuronidation reaction at pH 6.0. Testing the human UDP-glucuronosyltransferases (UGTs) of subfamilies 1A, 2A and 2B at pH 7.4 revealed that UGT1A10, UGT2B7 and UGT2B17 are the most active enzymes in diclofenac glucuronidation, while the highest indomethacin glucuronidation rates (corrected for relative expression levels) were exhibited by UGT2A1, UGT1A10 and UGT2B7. Interestingly, lowering the reaction pH to 6.0 increased the activity of many UGTs, particularly UGT1A10, toward both drugs, even if the rate of 4-methylumbelliferone glucuronidation by UGT1A10 at pH 6.0 was significantly lower than at pH 7.4. On the other hand, UGT2B15 lost activity upon lowering the reaction pH to 6.0. UGT1A6 does not glucuronidate diclofenac and indomethacin. Nevertheless, both drugs inhibit the 1-naphthol glucuronidation activity of UGT1A6 and their inhibition was stimulated by lowering the reaction pH, yielding significantly lower IC(50) values at pH 6.0 than at pH 7.4. In conclusion, glucuronidation reactions pH affects their outcome in variable ways and could increase the toxicity of drugs that carry a carboxylic acid.

Fluorescence-based high-throughput screening assay for drug interactions with UGT1A6.

The increasing awareness and the rising importance of UDP-glucuronosyltransferases (UGTs) in the pharmacokinetics of drugs have evoked a need to develop more powerful tools for studying the role of UGTs in the metabolism of drug candidates. To this end, we have developed a fluorescent high-throughput screening assay for screening potential inhibitors and/or substrates for recombinant human UGTs-here, for the UGT1A6. The assay is based on the increase in fluorescence intensity when 1-naphthol is glucuronidated. The formation of the highly fluorescent product, 1-naphthylglucuronide, is followed at excitation wavelengths of 295 and 300 nm with fixed emission (335 nm) in real time directly from the reaction mixture. A probe concentration of 5 µM with 2.5 µg of total protein in phosphate buffer at pH 7.4 with 5% dimethyl sulfoxide resulted in optimal linearity and acceptable signal separation (signal-to-base, 3.0) for the probe reaction. The interactions of test compounds with the enzyme are detected as lower rate of 1-naphthylglucuronide formation and thus lower rate of fluorescence increase. The success of the assay was first demonstrated with the known UGT1A6 substrates 4-hydroxyindole and scopoletin (Z' factor ≥0.5) and later with nonsteroidal anti-inflammatory drugs and salicylate derivatives. Diclofenac, 5-methylsalicylic acid, 5-bromosalicylic acid, 5-chlorosalicylic acid, and 5-fluorosalicylic acid decreased the probe glucuronidation rate at 500 µM by >50%. Further, the results gained with the high-throughput screening assay correlated well with the results obtained, in parallel, with the reference high-performance liquid chromatography method.

Feasibility evaluation of 3 automated cellular drug screening assays on a robotic workstation.

This study presents the implementation and optimization of 3 cell-based assays on a TECAN Genesis workstation-the Caspase-Glo 3/7 and sulforhodamine B (SRB) screening assays and the mechanistic Caco-2 permeability protocol-and evaluates their feasibility for automation. During implementation, the dispensing speed to add drug solutions and fixative trichloroacetic acid and the aspiration speed to remove the supernatant immediately after fixation were optimized. Decontamination steps for cleaning the tips and pipetting tubing were also added. The automated Caspase-Glo 3/7 screen was successfully optimized with Caco-2 cells (Z' 0.7, signal-to-base ratio [S/B] 1.7) but not with DU-145 cells. In contrast, the automated SRB screen was successfully optimized with the DU-145 cells (Z' 0.8, S/B 2.4) but not with the Caco-2 cells (Z' -0.8, S/B 1.4). The automated bidirectional Caco-2 permeability experiments separated successfully low- and high-permeability compounds (Z' 0.8, S/B 84.2) and passive drug permeation from efflux-mediated transport (Z' 0.5, S/B 8.6). Of the assays, the homogeneous Caspase-Glo 3/7 assay benefits the most from automation, but also the heterogeneous SRB assay and Caco-2 permeability experiments gain advantages from automation.

Drug release phenomena within a hydrophobic starch acetate matrix: FTIR mapping of tablets after in vitro dissolution testing.

The aim of this study was to assess the utility of Fourier transform infrared mapping to study the drug release phenomena within a hydrophobic matrix tablet. Starch acetate with a degree of substitution (2.7) was used as a hydrophobic matrix former. Anhydrous caffeine and riboflavin sodium phosphate were used as water soluble model drugs. The USP (XXVIII) paddle-method was selected as an in vitro dissolution test. Mapping of the diluted tablets' cross-section was performed by attenuated total reflection mode. Fourier transform infrared mapping can distinguish drug particles from the bulk matrix and it can be considered as a valuable method for obtaining both quantitative and qualitative information on drug release processes. The physicochemical properties of the drug compound strongly contribute to its release behavior when the USP paddle in vitro dissolution test is used. Mapping of the riboflavin product revealed a more homogenous matrix distribution due to its smaller particle size. Consequently, its dissolution release profile was more uniform than caffeine which possessed a wider particle size distribution and lower solubility. Mapping showed that caffeine became localized in the lower part of the tablet unlike riboflavin. The hydrodynamic conditions during the in vitro release test might contribute to this differentiation.

Predicting the drug concentration in starch acetate matrix tablets from ATR-FTIR spectra using multi-way methods.

The amounts of drug and excipient were predicted from ATR-FTIR spectra using two multi-way modelling techniques, parallel factor analysis (PARAFAC) and multi-linear partial least squares (N-PLS). Data matrices consisted of dissolved and undissolved parallel samples having different drug content and spectra, which were collected at axially cut surface of the flat-faced matrix tablets. Spectra were recorded comprehensively at different points on the axially cut surface of the tablet. The sample drug concentrations varied between 2 and 16% v/v. The multi-way methods together with ATR-FTIR spectra seemed to represent an applicable method for the determination of drug and excipient distribution in a tablet during the release process. The N-PLS calibration method was more robust for accurate quantification of the amount of components in the sample whereas the PARAFAC model provided approximate relative amounts of components.