Quantification of Accurate Composition and Total Abundance of Homologous Proteins by Conserved-Plus-Surrogate Peptide Approach: Quantification of UDP Glucuronosyltransferases in Human Tissues

Advancing understanding of human variability through toxicokinetic modeling, in vitro-in vivo extrapolation, and new approach methodologies

The merging of physiology and toxicokinetics, or pharmacokinetics, with computational modeling to characterize dosimetry has led to major advances for both the chemical and pharmaceutical research arenas. Driven by the mutual need to estimate internal exposures where in vivo data generation was simply not possible, the application of toxicokinetic modeling has grown exponentially in the past 30 years. In toxicology the need has been the derivation of quantitative estimates of toxicokinetic and toxicodynamic variability to evaluate the suitability of the tenfold uncertainty factor employed in risk assessment decision-making. Consideration of a host of physiologic, ontogenetic, genetic, and exposure factors are all required for comprehensive characterization. Fortunately, the underlying framework of physiologically based toxicokinetic models can accommodate these inputs, in addition to being amenable to capturing time-varying dynamics. Meanwhile, international interest in advancing new approach methodologies has fueled the generation of in vitro toxicity and toxicokinetic data that can be applied in in vitro-in vivo extrapolation approaches to provide human-specific risk-based information for historically data-poor chemicals. This review will provide a brief introduction to the structure and evolution of toxicokinetic and physiologically based toxicokinetic models as they advanced to incorporate variability and a wide range of complex exposure scenarios. This will be followed by a state of the science update describing current and emerging experimental and modeling strategies for population and life-stage variability, including the increasing application of in vitro-in vivo extrapolation with physiologically based toxicokinetic models in pharmaceutical and chemical safety research. The review will conclude with case study examples demonstrating novel applications of physiologically based toxicokinetic modeling and an update on its applications for regulatory decision-making. Physiologically based toxicokinetic modeling provides a sound framework for variability evaluation in chemical risk assessment.

Differential Tissue Abundance of Membrane-Bound Drug Metabolizing Enzymes and Transporter Proteins by Global Proteomics

Protein abundance data of drug-metabolizing enzymes and transporters (DMETs) are useful for scaling in vitro and animal data to humans for accurate prediction and interpretation of drug clearance and toxicity. Targeted DMET proteomics that relies on synthetic stable isotope-labeled surrogate peptides as calibrators is routinely used for the quantification of selected proteins; however, the technique is limited to the quantification of a small number of proteins. Although the global proteomics-based total protein approach (TPA) is emerging as a better alternative for large-scale protein quantification, the conventional TPA does not consider differential sequence coverage by identifying unique peptides across proteins. Here, we optimized the TPA approach by correcting protein abundance data by the sequence coverage, which was applied to quantify 54 DMETs for characterization of 1) differential tissue DMET abundance in the human liver, kidney, and intestine, and 2) interindividual variability of DMET proteins in individual intestinal samples (n = 13). Uridine diphosphate-glucuronosyltransferase 2B7 (UGT2B7), microsomal glutathione S-transferases (MGST1, MGST2, and MGST3) carboxylesterase 2 (CES2), and multidrug resistance-associated protein 2 (MRP2) were expressed in all three tissues, whereas, as expected, four cytochrome P450s (CYP3A4, CYP3A5, CYP2C9, and CYP4F2), UGT1A1, UGT2B17, CES1, flavin-containing monooxygenase 5, MRP3, and P-glycoprotein were present in the liver and intestine. The top three DMET proteins in individual tissues were: CES1>CYP2E1>UGT2B7 (liver), CES2>UGT2B17>CYP3A4 (intestine), and MGST1>UGT1A6>MGST2 (kidney). CYP3A4, CYP3A5, UGT2B17, CES2, and MGST2 showed high interindividual variability in the intestine. These data are relevant for enhancing in vitro to in vivo extrapolation of drug absorption and disposition and can be used to enhance the accuracy of physiologically based pharmacokinetic prediction of systemic and tissue concentration of drugs. SIGNIFICANCE STATEMENT: This study quantified the abundance and compositions of drug-metabolizing enzymes and transporters in pooled human liver, intestine, and kidney microsomes as well as individual intestinal microsomes using an optimized global proteomics approach. The data revealed large intertissue differences in the abundance of these proteins and high intestinal interindividual variability in the levels of cytochrome P450s (e.g., CYP3A4 and CYP3A5), uridine diphosphate-glucuronosyltransferase 2B17, carboxylesterase 2, and microsomal glutathione S-transferase 2. These data are applicable for the prediction of first-pass metabolism and tissue-specific drug clearance.

Identification of the Biotransformation Pathways of a Potential Oral Male Contraceptive, 11β-Methyl-19-Nortestosterone (11β-MNT) and Its Prodrugs: An In Vitro Study Highlights the Contribution of Polymorphic Intestinal UGT2B17

11β-Methyl-19-nortestosterone dodecylcarbonate (11β-MNTDC) is a prodrug of 11β-MNT and is being considered as a promising male oral contraceptive candidate in clinical development. However, the oral administration of 11β-MNTDC exhibits an ~200-fold lower serum concentration of 11β-MNT compared to 11β-MNTDC, resulting in the poor bioavailability of 11β-MNT. To elucidate the role of the first-pass metabolism of 11β-MNT in its poor bioavailability, we determined the biotransformation products of 11β-MNT and its prodrugs in human in vitro models. 11β-MNT and its two prodrugs 11β-MNTDC and 11β-MNT undecanoate (11β-MNTU) were incubated in cryopreserved human hepatocytes (HHs) and subjected to liquid chromatography-high resolution tandem mass spectrometry analysis, which identified ten 11β-MNT biotransformation products with dehydrogenated and glucuronidation (11β-MNTG) metabolites being the major metabolites. However, 11β-MNTG formation is highly variable and prevalent in human intestinal S9 fractions. A reaction phenotyping study of 11β-MNT using thirteen recombinant UDP-glucuronosyltransferase (UGT) enzymes confirmed the major role of UGT2B17 in 11β-MNTG formation. This was further supported by a strong correlation (R2 > 0.78) between 11β-MNTG and UGT2B17 abundance in human intestinal microsomes, human liver microsomes, and HH systems. These results suggest that 11β-MNT and its prodrugs are rapidly metabolized to 11β-MNTG by the highly polymorphic intestinal UGT2B17, which may explain the poor and variable bioavailability of the drug.

Comparison of Relative Activity versus Relative Expression Factors (RAF versus REF) in Predicting Glucuronidation Mediated Drug Clearance Using Recombinant UGTs

PURPOSE

Predicting the quantitative fraction of glucuronidation (fgluc) by individual UDP-glucuronosyltransferase enzymes (UGTs) is challenging due to the lack of selective inhibitors and inconsistent activity of recombinant UGT systems (rUGTs). Our study compares the relative expression versus activity factors (REF versus RAF) to predict fgluc based on rUGT data to human liver and intestinal microsomes (HLM and HIM).

METHODS

REF scalars were derived from a previous in-house proteomics study for eleven UGT enzymes (UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT1A10, UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17), whereas RAF was calculated by measuring activities in rUGTs to microsomes of selective UGT probe substrates. Protein-normalized activity factor (pnAF) values were generated after correcting activity of individual UGTs to their corresponding protein abundance. The utility of REF and RAF in predicting fgluc was assessed for three UGT substrates-diclofenac, vorinostat, and raltegravir.

RESULTS

The REF values ranged from 0.02 to 1.75, RAF based on activity obtained in rUGTs to HLM/HIM were from 0.1 to 274. pnAF values were ~ 5 to 80-fold, except for UGT2B4 and UGT2B15, where pnAF was ~ 180 and > 1000, respectively. The results revealed confounding effect of differential specific activities (per pmol) of rUGTs in fgluc prediction.

CONCLUSION

The data suggest that the activity of UGT enzymes was significantly lower when compared to their activity in microsomes at the same absolute protein amount (pmol). Collectively, results of this study demonstrate poor and variable specific activity of different rUGTs (per pmol protein), as determined by pnAF values, which should be considered in fgluc scaling.

Characterization of the glucuronidating pathway of pectolinarigenin, the major active constituent of the Chinese medicine Daji, in humans and its influence on biological activities

ETHNOPHARMACOLOGICAL RELEVANCE

The Chinese medicine Daji (the aerial part of Cirsium japonicum DC.) and its charred product (Cirsii Japonici Herba Carbonisata) have been widely used as hemostatic agents or diuretic agents to prepare a variety of Chinese herbal formula. Pectolinarigenin (PEC), one of the most abundant constituents in both Daji and its charred product, has been considered as the key effective substance responsible for the major pharmacological activities of Daji, including hemostasis, hepatoprotective, anti-tumor and anti-osteoporosis effects. However, the major metabolic pathways of PEC in humans and the influence of PEC metabolism on its biological activities are poorly understood.

AIM OF THE STUDY

To characterize the main metabolic pathway(s) and key enzymes of PEC in human biological systems, as well as to reveal the influence of PEC metabolism on its biological activities.

MATERIALS AND METHODS

The metabolic stability assays of PEC were investigated in human liver microsomes (HLM). The O-glucuronide of PEC was biosynthesized and characterized by nuclear magnetic resonance (NMR) spectroscopy. The key enzymes responsible for O-glucuronidation of PEC in humans were assigned by performing UGT reaction phenotyping, chemical inhibition and enzymatic kinetic assays. The agonist effects of PEC and its O-glucuronide on nuclear factor erythroid2-related factor 2 (Nrf2), Peroxisome proliferator activated receptors (PPARα and PPARβ) were tested at the cellular level.

RESULTS

PEC could be readily metabolized to form a mono-O-glucuronide in both human liver microsome (HLM) and human intestinal microsome (HIM). The mono-O-glucuronide was bio-synthesized by mouse liver S9 and its structure was fully characterized as PEC-7-O-β-D-glucuronide (PEC-O-7-G). UGT1A1, UGT1A3 and UGT1A9 are key enzymes responsible for PEC-7-O-glucuronidation in HLM, while UGT1A1, UGT1A9 and 1A10 may play key roles in this reaction in HIM. Biological tests revealed that PEC displayed strong agonist effects on Nrf2, PPARα and PPARβ, whereas PEC-7-O-glucuronide showed relatively weak Nrf2 agonist effect and very weak PPAR agonist effects, indicating that PEC-7-O-glucuronidation strongly weaken its agonist effects on Nrf2 and PPAR.

CONCLUSIONS

Our results demonstrate that 7-O-glucuronidation is the major metabolic pathway of PEC in human tissues, while UGT1A1, 1A3 and 1A9 are key contributing enzymes responsible for PEC-7-O-glucuronidation in human liver. It is also found that PEC 7-O-glucuronidation significantly weakens the Nrf2 and PPAR agonist effects. All these findings are very helpful for the pharmacologists to deep understand the metabolic rates of PEC in humans.

Promiscuity and Quantitative Contribution of UGT2B17 in Drug and Steroid Metabolism Determined by Experimental and Computational Approaches

Uridine 5'-diphospho-glulcuronosyltransferase 2B17 (UGT2B17) is important in the metabolism of steroids and orally administered drugs due to its high interindividual variability. However, the structural basis governing the substrate selectivity or inhibition of UGT2B17 remains poorly understood. This study investigated 76 FDA-approved drugs and 20 steroids known to undergo glucuronidation for their metabolism by UGT2B17. Specifically, we assessed the substrate selectivity for UGT2B17 over other UGT enzymes using recombinant human UGT2B17 (rUGT2B17), human intestinal microsomes, and human liver microsomes. The quantitative contribution of intestinal UGT2B17 in the glucuronidation of these compounds was characterized using intestinal microsomes isolated from UGT2B17 expressors and nonexpressors. In addition, a structure-based pharmacophore model for UGT2B17 substrates was built and validated using the studied pool of substrates and nonsubstrates. The results show that UGT2B17 could metabolize 23 out of 96 compounds from various chemical classes, including alcohols and carboxylic acids, particularly in the intestine. Interestingly, amines were less susceptible to UGT2B17 metabolism, though they could inhibit the enzyme. Three main pharmacophoric features of UGT2B17 substrates include (1) the presence of an accessible -OH or -COOH group near His35 residue, (2) a hydrophobic functional group at ∼4.5-5 Å from feature 1, and (3) an aromatic ring ∼5-7 Å from feature 2. Most of the studied compounds inhibited UGT2B17 activity irrespective of their substrate potential, indicating the possibility of multiple mechanisms. These data suggest that UGT2B17 is promiscuous in substrate selectivity and inhibition and has a high potential to produce significant variability in the absorption and disposition of orally administered drugs.

Quantitative Characterization of Clinically Relevant Drug-Metabolizing Enzymes and Transporters in Rat Liver and Intestinal Segments for Applications in PBPK Modeling

Rats are extensively used as a preclinical model for assessing drug pharmacokinetics (PK) and tissue distribution; however, successful translation of the rat data requires information on the differences in drug metabolism and transport mechanisms between rats and humans. To partly fill this knowledge gap, we quantified clinically relevant drug-metabolizing enzymes and transporters (DMETs) in the liver and different intestinal segments of Sprague-Dawley rats. The levels of DMET proteins in rats were quantified using the global proteomics-based total protein approach (TPA) and targeted proteomics. The abundance of the major DMET proteins was largely comparable using quantitative global and targeted proteomics. However, global proteomics-based TPA was able to detect and quantify a comprehensive list of 66 DMET proteins in the liver and 37 DMET proteins in the intestinal segments of SD rats without the need for peptide standards. Cytochrome P450 (Cyp) and UDP-glycosyltransferase (Ugt) enzymes were mainly detected in the liver with the abundance ranging from 8 to 6502 and 74 to 2558 pmol/g tissue. P-gp abundance was higher in the intestine (124.1 pmol/g) as compared to that in the liver (26.6 pmol/g) using the targeted analysis. Breast cancer resistance protein (Bcrp) was most abundant in the intestinal segments, whereas organic anion transporting polypeptides (Oatp) 1a1, 1a4, 1b2, and 2a1 and multidrug resistance proteins (Mrp) 2 and 6 were predominantly detected in the liver. To demonstrate the utility of these data, we modeled digoxin PK by integrating protein abundance of P-gp and Cyp3a2 into a physiologically based PK (PBPK) model constructed using PK-Sim software. The model was able to reliably predict the systemic as well as tissue concentrations of digoxin in rats. These findings suggest that proteomics-informed PBPK models in preclinical species can allow mechanistic PK predictions in animal models including tissue drug concentrations.