Justin D. Lutz

Expression and functional characterization of cytochrome P450 26A1, a retinoic acid hydroxylase

Retinoic acid (RA) is a critical signaling molecule that performs multiple functions required to maintain cellular viability. It is also used in the treatment of some cancers. Enzymes in the CYP26 family are thought to be responsible for the elimination of RA, and CYP26A1 appears to serve the most critical functions in this family. In spite of its importance, CYP26A1 has neither been heterologously expressed nor characterized kinetically. We expressed the rCYP26A1 in baculovirus-infected insect cells and purified the hexahistidine tagged protein to homogeneity. Heme incorporation was determined by carbon monoxide difference spectrum and a type 1 spectrum was observed with RA binding to CYP26A1. We found that RA is a tight binding ligand of CYP26A1 with low nM binding affinity. CYP26A1 oxidized RA efficiently (depletion K(m) 9.4+/-3.3nM and V(max) 11.3+/-4.3pmolesmin(-1)pmoleP450(-1)) when supplemented with P450 oxidoreductase and NADPH but was independent of cytochrome b5. 4-Hydroxy-RA (4-OH-RA) was the major metabolite produced by rCYP26A1 but two other primary products were also formed. 4-OH-RA was further metabolized by CYP26A1 to more polar metabolites and this sequential metabolism of RA occurred in part without 4-OH-RA leaving the active site of CYP26A1. The high efficiency of CYP26A1 in eliminating both RA and its potentially active metabolites supports the major role of this enzyme in regulating RA clearance in vivo. These results provide a biochemical framework for CYP26A1 function and offer insight into the role of CYP26A1 as a drug target as well as in fetal development and cell cycle regulation.

Comparison of the function and expression of CYP26A1 and CYP26B1, the two retinoic acid hydroxylases

All-trans-retinoic acid (atRA) is an important signaling molecule in all chordates. The cytochrome P450 enzymes CYP26 are believed to partially regulate cellular concentrations of atRA via oxidative metabolism and hence affect retinoid homeostasis and signaling. CYP26A1 and CYP26B1 are atRA hydroxylases that catalyze formation of similar metabolites in cell systems. However, they have only 40% sequence similarity suggesting differences between the two enzymes. The aim of this study was to determine whether CYP26A1 and CYP26B1 have similar catalytic activity, form different metabolites from atRA and are expressed in different tissues in adults. The mRNA expression of CYP26A1 and CYP26B1 correlated between human tissues except for human cerebellum in which CYP26B1 was the predominant CYP26 and liver in which CYP26A1 dominated. Quantification of CYP26A1 and CYP26B1 protein in human tissues was in agreement with the mRNA expression and showed correlation between the two isoforms. Qualitatively, recombinant CYP26A1 and CYP26B1 formed the same primary and sequential metabolites from atRA. Quantitatively, CYP26B1 had a lower K(m) (19nM) and V(max) (0.8 pmol/min/pmol) than CYP26A1 (K(m)=50 nM and V(max)=10 pmol/min/pmol) for formation of 4-OH-RA. The major atRA metabolites 4-OH-RA, 18-OH-RA and 4-oxo-RA were all substrates of CYP26A1 and CYP26B1, and CYP26A1 had a 2-10-fold higher catalytic activity towards all substrates tested. This study shows that CYP26A1 and CYP26B1 are qualitatively similar RA hydroxylases with overlapping expression profiles. CYP26A1 has higher catalytic activity than CYP26B1 and seems to be responsible for metabolism of atRA in tissues that function as a barrier for atRA exposure.

A Specific Inhibitor of PfCDPK4 Blocks Malaria Transmission: Chemical-genetic Validation

Malaria parasites are transmitted by mosquitoes, and blocking parasite transmission is critical in reducing or eliminating malaria in endemic regions. Here, we report the pharmacological characterization of a new class of malaria transmission-blocking compounds that acts via the inhibition of Plasmodia CDPK4 enzyme. We demonstrate that these compounds achieved selectivity over mammalian kinases by capitalizing on a small serine gatekeeper residue in the active site of the Plasmodium CDPK4 enzyme. To directly confirm the mechanism of action of these compounds, we generated P. falciparum parasites that express a drug-resistant methionine gatekeeper (S147 M) CDPK4 mutant. Mutant parasites showed a shift in exflagellation EC50 relative to the wild-type strains in the presence of compound 1294, providing chemical-genetic evidence that CDPK4 is the target of the compound. Pharmacokinetic analyses suggest that coformulation of this transmission-blocking agent with asexual stage antimalarials such as artemisinin combination therapy (ACT) is a promising option for drug delivery that may reduce transmission of malaria including drug-resistant strains. Ongoing studies include refining the compounds to improve efficacy and toxicological properties for efficient blocking of malaria transmission.

Inhibition of CYP2C19 and CYP3A4 by Omeprazole Metabolites and their Contribution to Drug-Drug Interactions

The aim of this study was to evaluate the contribution of metabolites to drug-drug interactions (DDI) using the inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites as a model. Of the metabolites identified in vivo, 5-hydroxyomeprazole, 5′-O-desmethylomeprazole, omeprazole sulfone, and carboxyomeprazole had a metabolite to parent area under the plasma concentration–time curve (AUCm/AUCp) ratio ≥ 0.25 when either total or unbound concentrations were measured after a single 20-mg dose of omeprazole in a cocktail. All of the metabolites inhibited CYP2C19 and CYP3A4 reversibly. In addition omeprazole, omeprazole sulfone, and 5′-O-desmethylomeprazole were time dependent inhibitors (TDI) of CYP2C19, whereas omeprazole and 5′-O-desmethylomeprazole were found to be TDIs of CYP3A4. The in vitro inhibition constants and in vivo plasma concentrations were used to evaluate whether characterization of the metabolites affected DDI risk assessment. Identifying omeprazole as a TDI of both CYP2C19 and CYP3A4 was the most important factor in DDI risk assessment. Consideration of reversible inhibition by omeprazole and its metabolites would not identify DDI risk with CYP3A4, and with CYP2C19, reversible inhibition values would only identify DDI risk if the metabolites were included in the assessment. On the basis of inactivation data, CYP2C19 and CYP3A4 inhibition by omeprazole would be sufficient to identify risk, but metabolites were predicted to contribute 30–63% to the in vivo hepatic interactions. Therefore, consideration of metabolites may be important in quantitative predictions of in vivo DDIs. The results of this study show that, although metabolites contribute to in vivo DDIs, their relative abundance in circulation or logP values do not predict their contribution to in vivo DDI risk.

Fluoxetine and norfluoxetine mediated complex drug-drug interactions: in vitro to in vivo correlation of effects on CYP2D6, CYP2C19 and CYP3A4

Fluoxetine and its circulating metabolite norfluoxetine comprise a complex multiple‐inhibitor system that causes reversible or time‐dependent inhibition of the cytochrome P450 (CYP) family members CYP2D6, CYP3A4, and CYP2C19 in vitro. Although significant inhibition of all three enzymes in vivo was predicted, the areas under the concentration–time curve (AUCs) for midazolam and lovastatin were unaffected by 2‐week dosing of fluoxetine, whereas the AUCs of dextromethorphan and omeprazole were increased by 27‐ and 7.1‐fold, respectively. This observed discrepancy between in vitro risk assessment and in vivo drug–drug interaction (DDI) profile was rationalized by time‐varying dynamic pharmacokinetic models that incorporated circulating concentrations of fluoxetine and norfluoxetine enantiomers, mutual inhibitor–inhibitor interactions, and CYP3A4 induction. The dynamic models predicted all DDIs with less than twofold error. This study demonstrates that complex DDIs that involve multiple mechanisms, pathways, and inhibitors with their metabolites can be predicted and rationalized via characterization of all the inhibitory species in vitro.

Prediction of relative in vivo metabolite exposure from in vitro data using two model drugs: dextromethorphan and omeprazole

Metabolites can have pharmacological or toxicological effects, inhibit metabolic enzymes, and be used as probes of drug-drug interactions or specific cytochrome P450 (P450) phenotypes. Thus, better understanding and prediction methods are needed to characterize metabolite exposures in vivo. This study aimed to test whether in vitro data could be used to predict and rationalize in vivo metabolite exposures using two model drugs and P450 probes: dextromethorphan and omeprazole with their primary metabolites dextrorphan, 5-hydroxyomeprazole (5OH-omeprazole), and omeprazole sulfone. Relative metabolite exposures were predicted using metabolite formation and elimination clearances. For dextrorphan, the formation clearances of dextrorphan glucuronide and 3-hydroxymorphinan from dextrorphan in human liver microsomes were used to predict metabolite (dextrorphan) clearance. For 5OH-omeprazole and omeprazole sulfone, the depletion rates of the metabolites in human hepatocytes were used to predict metabolite clearance. Dextrorphan/dextromethorphan in vivo metabolite/parent area under the plasma concentration versus time curve ratio (AUCm/AUCp) was overpredicted by 2.1-fold, whereas 5OH-omeprazole/omeprazole and omeprazole sulfone/omeprazole were predicted within 0.75- and 1.1-fold, respectively. The effect of inhibition or induction of the metabolites formation and elimination on the AUCm/AUCp ratio was simulated. The simulations showed that unless metabolite clearance pathways are characterized, interpretation of the metabolic ratios is exceedingly difficult. This study shows that relative in vivo metabolite exposure can be predicted from in vitro data and characterization of secondary metabolism of probe metabolites is critical for interpretation of phenotypic data.

Rationalization and prediction of in vivo metabolite exposures: the role of metabolite kinetics, clearance predictions and in vitro parameters.

Importance of the field: Due to growing concerns over toxic or active metabolites, significant efforts have been focused on qualitative identification of potential in vivo metabolites from in vitro data. However, limited tools are available to quantitatively predict their human exposures. Areas covered in this review: Theory of clearance predictions and metabolite kinetics is reviewed together with supporting experimental data. In vitro and in vivo data of known circulating metabolites and their parent drugs were collected and the predictions of in vivo exposures of the metabolites were evaluated. What the reader will gain: The theory and data reviewed will be useful in early identification of human metabolites that will circulate at significant levels in vivo and help in designing in vivo studies that focus on characterization of metabolites. It will also assist in rationalization of metabolite-to-parent ratios used as markers of specific enzyme activity. Take home message: The relative importance of a metabolite in comparison to the parent compound as well as other metabolites in vivo can only be predicted using the metabolites in vitro formation and elimination clearances, and the in vivo disposition of a metabolite can only be rationalized when the elimination pathways of that metabolite are known.

Importance of multi-P450 inhibition in drug-drug interactions: evaluation of incidence, inhibition magnitude and prediction from in vitro data

Drugs that are mainly cleared by a single enzyme are considered more sensitive to drug-drug interactions (DDIs) than drugs cleared by multiple pathways. However, whether this is true when a drug cleared by multiple pathways is coadministered with an inhibitor of multiple P450 enzymes (multi-P450 inhibition) is not known. Mathematically, simultaneous equipotent inhibition of two elimination pathways that each contribute half of the drug clearance is equal to equipotent inhibition of a single pathway that clears the drug. However, simultaneous strong or moderate inhibition of two pathways by a single inhibitor is perceived as an unlikely scenario. The aim of this study was (i) to identify P450 inhibitors currently in clinical use that can inhibit more than one clearance pathway of an object drug in vivo and (ii) to evaluate the magnitude and predictability of DDIs caused by these multi-P450 inhibitors. Multi-P450 inhibitors were identified using the Metabolism and Transport Drug Interaction Database. A total of 38 multi-P450 inhibitors, defined as inhibitors that increased the AUC or decreased the clearance of probes of two or more P450s, were identified. Seventeen (45%) multi-P450 inhibitors were strong inhibitors of at least one P450, and an additional 12 (32%) were moderate inhibitors of one or more P450s. Only one inhibitor (fluvoxamine) was a strong inhibitor of more than one enzyme. Fifteen of the multi-P450 inhibitors also inhibit drug transporters in vivo, but such data are lacking on many of the inhibitors. Inhibition of multiple P450 enzymes by a single inhibitor resulted in significant (>2-fold) clinical DDIs with drugs that are cleared by multiple pathways such as imipramine and diazepam, while strong P450 inhibitors resulted in only weak DDIs with these object drugs. The magnitude of the DDIs between multi-P450 inhibitors and diazepam, imipramine, and omeprazole could be predicted using in vitro data with similar accuracy as probe substrate studies with the same inhibitors. The results of this study suggest that inhibition of multiple clearance pathways in vivo is clinically relevant, and the risk of DDIs with object drugs may be best evaluated in studies using multi-P450 inhibitors.

Stereospecific Metabolism of Itraconazole by CYP3A4: Dioxolane Ring Scission of Azole Antifungals

Itraconazole (ITZ) is a mixture of four cis-stereoisomers that inhibit CYP3A4 potently and coordinate CYP3A4 heme via the triazole nitrogen. However, (2R,4S,2′R)-ITZ and (2R,4S,2′S)-ITZ also undergo stereoselective sequential metabolism by CYP3A4 at a site distant from the triazole ring to 3′-OH-ITZ, keto-ITZ, and N-desalkyl-ITZ. This stereoselective metabolism demonstrates specific interactions of ITZ within the CYP3A4 active site. To further investigate this process, the binding and metabolism of the four trans-ITZ stereoisomers by CYP3A4 were characterized. All four trans-ITZ stereoisomers were tight binding inhibitors of CYP3A4-mediated midazolam hydroxylation (IC50 16–26 nM), and each gave a type II spectrum upon binding to CYP3A4. However, instead of formation of 3′-OH-ITZ, they were oxidized at the dioxolane ring, leading to ring scission and formation of two new metabolites of ITZ. These two metabolites were also formed from the four cis-ITZ stereoisomers, although not as efficiently. The catalytic rates of dioxolane ring scission were similar to the dissociation rates of ITZ stereoisomers from CYP3A4, suggesting that the heme iron is reduced while the triazole moiety coordinates to it and no dissociation of ITZ is necessary before catalysis. The triazole containing metabolite [1-(2,4-dichlorophenyl)-2-(1H-1,2,4-triazol-1-yl)ethanone] also inhibited CYP3A4 (IC50 >15 μM) and showed type II binding with CYP3A4. The dioxolane ring scission appears to be clinically relevant because this metabolite was detected in urine samples from subjects that had been administered the mixture of cis-ITZ isomers. These data suggest that the dioxolane ring scission is a metabolic pathway for drugs that contain this moiety.

Stereoselective Inhibition of CYP2C19 and CYP3A4 by Fluoxetine and its Metabolite: Implications For Risk Assessment of Multiple Time-dependent Inhibitor Systems

Recent guidance on drug-drug interaction (DDI) testing recommends evaluation of circulating metabolites. However, there is little consensus on how to quantitatively predict and/or assess the risk of in vivo DDIs by multiple time-dependent inhibitors (TDIs) including metabolites from in vitro data. Fluoxetine was chosen as the model drug to evaluate the role of TDI metabolites in DDI prediction because it is a TDI of both CYP3A4 and CYP2C19 with a circulating N-dealkylated inhibitory metabolite, norfluoxetine. In pooled human liver microsomes, both enantiomers of fluoxetine and norfluoxetine were TDIs of CYP2C19, (S)-norfluoxetine was the most potent inhibitor with time-dependent inhibition affinity constant (KI) of 7 μM, and apparent maximum time-dependent inhibition rate (kinact,app) of 0.059 min−1. Only (S)-fluoxetine and (R)-norfluoxetine were TDIs of CYP3A4, with (R)-norfluoxetine being the most potent (KI = 8 μM, and kinact,app = 0.011 min−1). Based on in-vitro-to-in-vivo predictions, (S)-norfluoxetine plays the most important role in in vivo CYP2C19 DDIs, whereas (R)-norfluoxetine is most important in CYP3A4 DDIs. Comparison of two multiple TDI prediction models demonstrated significant differences between them in in-vitro-to-in-vitro predictions but not in in-vitro-to-in-vivo predictions. Inclusion of all four inhibitors predicted an in vivo decrease in CYP2C19 (95%) and CYP3A4 (60–62%) activity. The results of this study suggest that adequate worst-case risk assessment for in vivo DDIs by multiple TDI systems can be achieved by incorporating time-dependent inhibition by both parent and metabolite via simple addition of the in vivo time-dependent inhibition rate/cytochrome P450 degradation rate constant (λ/kdeg) values, but quantitative DDI predictions will require a more thorough understanding of TDI mechanisms.