Age-dependent changes in cytochrome P450 abundance and composition in human liver.

Cytochrome P450 (CYP) superfamily represents the major drug metabolizing enzymes responsible for metabolizing over 65% of therapeutic drugs, including those for pediatric use. CYP-ontogeny based physiologically-based pharmacokinetic (PBPK) models have emerged as useful tools to mechanistically extrapolate adult pharmacokinetic data to children. However, these models integrate physiological differences in pediatric population including age-dependent differences in the abundances of CYP enzymes. Conventionally, developmental changes in CYP enzymes have been reported using protein abundance and activity data from subcellular fractions such as microsomes, which is prone to high technical variability. Similarly, the available pediatric pharmacokinetic data suffer from the lack of specific CYP substrates, especially in younger children. In the present study, we utilized viable hepatocytes from 50 pediatric (age, day 1- 18 yr) and 8 adult human donors and carried out global proteomics-based quantification of all major hepatic CYP enzymes, including orphan enzymes that have not been studied previously. While CYPs 2B6, 3A5, 4A11, 4F3, and 4V2 did not show significant association with age, all other quantified isoforms either increased or decreased with age. CYPs 1A2, 2C8, 2C18, and 2C19 were absent or barely detected in the neonatal group, while CYP3A7 was the highest in this group. The >1-2 yr age-group showed the highest total abundance of all CYP enzymes. The age-dependent differences in CYP enzymes reported in this study can be used to develop ontogeny-based PBPK models, which in turn can help improve pediatric dose-prediction based on adult dosing, leading to safer drug pharmacology in children. Significance Statement We quantified age-dependent differences in the abundances of hepatic CYP enzymes using a large set of viable pediatric and adult hepatocytes using quantitative global proteomics. We report for the first time the ontogeny in the abundance of CYP enzymes in human hepatocytes, especially, orphan CYPs 20A1, 27A1, 51A1, 7B1, and 8B1 and the CYP4 subfamily of enzymes. Our study provides important data about CYP ontogeny that can be used for the better prediction of pediatric pharmacokinetics using physiologically-based pharmacokinetic modeling.

Microcystin-LR activates serine/threonine kinases and alters the phosphoproteome in human HepaRG cells.

Microcystin-LR (MCLR) exposure has been associated with development of hepatocellular carcinoma (HCC). Many of the carcinogenic mechanisms for MCLR have been attributed to the induction of cell survival and proliferation through altered protein phosphorylation pathways by inhibition of protein phosphatases 1 (PP1) and PP2A. The current study determined MCLR effects on the phosphoproteome in human HepaRG cells. Differentiated HepaRG cells were treated with either vehicle or MCLR followed by phosphoproteomic analysis and Western blotting of MAPK-activated proteins. MCLR decreased cell viability at 24 h at doses as low as 0.03 µM. MCLR also caused a dose-dependent increase in phosphorylation of signaling and stress kinases. The number of decreased phosphosites by 0.1 µM MCLR was similar between the 2 h (212) and 24 h (154) timepoints. In contrast, a greater number of phosphosites were increased at 24 h (567) versus the 2 h timepoint (136), indicating the hyperphosphorylation state caused by MCLR-mediated inhibition of PPs is time-dependent. A kinase perturbation analysis predicted that MCLR exposure at both 2 h and 24 h increased the function of aurora kinase B (AURKB), checkpoint kinase 1 (CHEK1), and serum and glucocorticoid-regulated kinase 1 (SGK1). STRING database analysis of the phosphosites altered by MCLR exposure revealed pathways associated with cell proliferation and survival, including ribosomal protein S6 kinase (RSK), and vascular endothelial growth factor receptor (VEGFR2)-mediated vascular permeability. In addition, several cancer-related KEGG pathways were enriched at both 2 h and 24 h timepoints, and multiple cancer-related disease-gene associations were identified at the 24 h timepoint. Many of the kinases and pathways described above play crucial roles in the development of HCC by affecting processes such as invasion and metastasis. Overall, our data indicate that MCLR-mediated changes in protein phosphorylation involve biological pathways related to carcinogenesis that may contribute to the development of HCC.

Developmental Expression of Drug Transporters and Conjugating Enzymes Involved in Enterohepatic Recycling: Implication for Pediatric Drug Dosing.

Around 50% of the drugs used in children have never been tested for safety and efficacy in this vulnerable population. Immature drug elimination pathways can lead to drug toxicity when pediatric doses are determined using empirical methods such as body-surface area or body-weight-normalized adult dosing. In the absence of clinical data, physiologically-based pharmacokinetic (PBPK) modeling has emerged as a useful tool to predict drug pharmacokinetics in children. These models utilize developmental physiological data, including age-dependent differences in the abundance of drug-metabolizing enzymes and transporters (DMET), to mechanistically extrapolate adult pharmacokinetic data to children. The reported abundance data of hepatic DMET proteins in subcellular fractions isolated from frozen tissue are prone to high technical variability. Therefore, we carried out the proteomics-based quantification of hepatic drug transporters and conjugating enzymes in 50 pediatric and 8 adult human hepatocyte samples. Out of the 34 studied proteins, 28 showed a significant increase or decrease with age. While MRP6, OAT7, and SULT1E1 were highest in < 1-year-old samples, the abundance of P-gp and UGT1A4 was negligible in < 1-year-old samples and increased significantly after 1 year of age. Incorporation of the age-dependent abundance data in PBPK models can help improve pediatric dose prediction, leading to safer drug pharmacotherapy in children.

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.

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

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

Age-Dependent Abundance of CYP450 Enzymes Involved in Metronidazole Metabolism: Application to Pediatric PBPK Modeling.

The expression of cytochrome P450 (CYP) enzymes is highly variable and associated with factors, such as age, genotype, sex, and disease states. In this study, quantification of metronidazole metabolizing CYP isoforms (CYP2A6, CYP2E1, CYP3A4, CYP3A5, and CYP3A7) in human liver microsomes from 115 children and 35 adults was performed using a quantitative proteomics method. The data confirmed age-dependent increase in CYP2A6, CYP2E1, and CYP3A4 abundance, whereas, as expected, CYP3A7 abundance showed postnatal decrease with age. In particular, the fold difference (neonatal to adulthood levels) in the protein abundance of CYP2A6, CYP2E1, and CYP3A4 was 14, 11, and 20, respectively. In contrast, protein abundance of CYP3A7 was > 125-fold higher in the liver microsomes of neonates than of adults. The abundance of CYP2A6 and CYP3A5 was associated with genotypes, rs4803381 and rs776746, respectively. A proteomics-informed physiologically based pharmacokinetic (PBPK) model was developed to describe the pharmacokinetics of metronidazole and its primary metabolite, 2-hydroxymethylmetronidazole. The model revealed an increase in the metabolite-to-parent ratio with age and showed a strong correlation between CYP2A6 abundance and metabolite formation (r2 = 0.75). Notably, the estimated contribution of CYP3A7 was ~ 75% in metronidazole clearance in neonates. These data suggest that variability in CYP2A6 and CYP3A7 in younger children poses the risk of variable pharmacokinetics of metronidazole and its active metabolite with a potential impact on drug efficacy and safety. No sex-dependent difference was observed in the protein abundance of the studied CYPs. The successful integration of hepatic CYP ontogeny data derived from a large liver bank into the pediatric PBPK model of metronidazole can be extended to other drugs metabolized by the studied CYPs.

Transcriptomic comparison of in vitro models of the human placenta.

Studying the human placenta through in vitro cell culture methods is necessary due to limited access and amenability of human placental tissue to certain experimental methods as well as distinct anatomical and physiological differences between animal and human placentas. Selecting an in vitro culture model of the human placenta is challenging due to representation of different trophoblast cell types with distinct biological roles and limited comparative studies that define key characteristics of these models. Therefore, the aim of this research was to create a comprehensive transcriptomic comparison of common in vitro models of the human placenta compared to bulk placental tissue from the CANDLE and GAPPS cohorts (N=1083). We performed differential gene expression analysis on publicly available RNA sequencing data from 6 common in vitro models of the human placenta (HTR-8/SVneo, BeWo, JEG-3, JAR, Primary Trophoblasts, and Villous Explants) and compared to CANDLE and GAPPS bulk placental tissue or cytotrophoblast, syncytiotrophoblast, and extravillous trophoblast cell types derived from bulk placental tissue. All in vitro placental models had a substantial number of differentially expressed genes (DEGs, FDR<0.01) compared to the CANDLE and GAPPS placentas (Average DEGs=10,873), and the individual trophoblast cell types (Average DEGs=5,346), indicating that there are vast differences in gene expression compared to bulk and cell-type specific human placental tissue. Hierarchical clustering identified 53 gene clusters with distinct expression profiles across placental models, with 22 clusters enriched for specific KEGG pathways, 7 clusters enriched for high-expression placental genes, and 7 clusters enriched for absorption, distribution, metabolism, and excretion genes. In vitro placental models were classified by fetal sex based on expression of Y-chromosome genes that identified HTR-8/SVneo cells as being of female origin, while JEG-3, JAR, and BeWo cells are of male origin. Overall, none of the models were a close approximation of the transcriptome of bulk human placental tissue, highlighting the challenges with model selection. To enable researchers to select appropriate models, we have compiled data on differential gene expression, clustering, and fetal sex into an accessible web application: "Comparative Transcriptomic Placental Model Atlas (CTPMA)" which can be utilized by researchers to make informed decisions about their selection of in vitro placental models.

Effects of alcohol consumption and tobacco smoking on the composition of the ensemble of drug metabolizing enzymes and transporters in human liver.

We examined the effect of alcohol consumption and smoking on the abundance of drug-metabolizing enzymes and transporters (DMET) in human liver microsomes (HLM) isolated from liver tissues of 94 donors. Global proteomics analysis was performed and DMET protein levels were analyzed in relation to alcohol consumption levels, smoking history, and sex using non-parametric tests (p-value ≤ 0.05; cutoff of 1.25-fold change, FC). The examination of the alcohol-induced changes was further enforced by correlational analysis, where we used arbitrary alcohol consumption grade (ACG) scaling from 0 to 4 to establish a set of protein markers. We elaborated a provisional index of alcohol exposure (PIAE) based on a combination of relative abundances of four proteins (ER chaperone HSPA5, protein disulfide isomerases PDIA3 and P4HB, and cocaine esterase CES2) best correlating with ACG. The PIAE index was then used to find its correlations with the abundances of DMET proteins. Our results demonstrate considerable alcohol-induced changes in composition of the pool of cytochrome P450 enzymes in HLM. We observed significantly increased abundances of CYP2E1, CYP2B6, CYP2J2, and NADPH-cytochrome P450 reductase. In contrast, CYP1A2, CYP2C8, CYP2C9, CYP4A11, and cytochrome b5 protein levels were downregulated. Significant alteration in abundances of UDP-glucuronosyltransferase (UGT) were also detected, comprising of elevated UGT1A6, UGT1A9, and UGT2A1, and reduced UGT1A3, UGT1A4, UGT2B7, UGT2B10, and UGT2B15 levels. Important alcohol-induced changes were also observed in the expression of non-CYP and non-UGT DMET. Additionally, tobacco smoke was associated with elevated CYP1A2, UGT1A6, UGT2A1, and UGT2B4 and decreased FMO3, FMO4, and FMO5 levels.

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook.

Over the past 20 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. A symposium at the 25th North American ISSX meeting, in Boston, in September 2023, was held to explore current and emerging applications of quantitative proteomics in translational pharmacology and strategies for improved integration into model-informed drug development based on practical experience of each of the presenters. A summary of the talks and discussions is presented in this perspective alongside future outlooks that were outlined for future meetings. Significance Statement This perspective explores current and emerging applications of quantitative proteomics in translational pharmacology and precision medicine, and outlines outlooks for improved integration into model-informed drug development.

Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism.

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

Sex and the Kidney Drug-Metabolizing Enzymes and Transporters: Are Preclinical Drug Disposition Data Translatable to Humans?

Cross-species differences in drug transport and metabolism are linked to poor translation of preclinical pharmacokinetic and toxicology data to humans, often resulting in the failure of new chemical entities (NCEs) during clinical drug development. Specifically, inaccurate prediction of renal clearance and renal accumulation of NCEs due to differential abundance of enzymes and transporters in kidneys can lead to differences in pharmacokinetics and toxicity between experimental animals and humans. We carried out liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based protein quantification of 78 membrane drug-metabolizing enzymes and transporters (DMETs) in the kidney membrane fractions of humans, rats, and mice for characterization of cross-species and sex-dependent differences. In general, majority of DMET proteins were higher in rodents than in humans. Significant cross-species differences were observed in 30 out of 33 membrane DMET proteins quantified in all three species. Although no significant sex-dependent differences were observed in humans, the abundance of 28 and 46 membrane proteins showed significant sex dependence in rats and mice, respectively. These cross-species and sex-dependent quantitative abundance data are valuable for gaining a mechanistic understanding of drug renal disposition and accumulation. Further, these data can also be integrated into systems pharmacology tools, such as physiologically based pharmacokinetic models, to enhance the interpretation of preclinical pharmacokinetic and toxicological data.

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 critical for scaling in vitro and animal data to humans for accurate prediction and interpretation of drug clearance and toxicity. Targeted DMET proteomics which 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 doesn't 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 (SC-TPA), which was applied to quantify 54 DMETs for characterization of i) differential tissue DMET abundance in the human liver, kidney, and intestine, and ii) interindividual variability of DMET proteins in individual intestinal samples (n=13). UGT2B7, MGST1, MGST2, MGST3, CES2, and MRP2 were expressed in all three tissues, whereas, as expected CYP3A4, CYP3A5, CYP2C9, CYP4F2, UGT1A1, UGT2B17, CES1, FMO5, MRP3, and P-gp 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 (IVIVE) of drug absorption and disposition and can be used to enhance the accuracy of physiologically based pharmacokinetic (PBPK) prediction of systemic and tissue concentration of drugs. Significance Statement We quantified the abundance and compositions of drug-metabolizing enzymes and transporters (DMETs) in pooled human liver, intestine, and kidney microsomes using an optimized sequence coverage-informed total protein approach. The quantification of DMETs revealed quantitative differences in their levels in the liver, intestine, and kidney. Further, the analysis of individual intestine samples confirmed high variability in the levels of CYP3A4, CYP3A5, UGT2B17, CES2, and MGST2. These data are applicable for the prediction of first-pass metabolism and tissue-specific drug clearance.

Cytochrome P450 Family 4F2 and 4F11 Haplotype Mapping and Association with Hepatic Gene Expression and Vitamin K Hydroxylation Activity.

This study evaluated the underlying mechanistic links between genetic variability in vitamin K metabolic pathway genes (CYP4F2 and CYP4F11) and phylloquinone hydroxylation activity using genotype- and haplotype-based approaches. Specifically, we characterized genetic variability in the CYP4F2/CYP4F11 locus and compared common single allele genotypes and common haplotypes as predictors of hepatic gene expression, enzyme abundance, and phylloquinone (VK1) ω-hydroxylation kinetics. We measured CYP4F2 and CYP4F11 mRNA levels, CYP4F2 and CYP4F11 protein abundances, and the VK1 concentration-dependent ω-hydroxylation rate in matched human liver nucleic acid and microsome samples, utilizing a novel in vitro population modeling approach. Results indicate that accounting for the CYP4F2*3 allele alone is sufficient to capture most of the genetic-derived variability in the observed phenotypes. Additionally, our findings highlight the important contribution that CYP4F11 makes toward vitamin K metabolism in the human liver.

Global Proteomics Analysis of Lysophosphatidic Acid Signaling in PC-3 Human Prostate Cancer Cells: Role of CCN1.

Cysteine-rich angiogenic factor 61 (CCN1/Cyr61) is a matricellular protein that is induced and secreted in response to growth factors. Our previous work showed that 18:1-lysophosphatidic acid (LPA), which activates the G protein-coupled receptor LPAR1, induces CCN1 between 2-4 h in PC-3 human prostate cancer cells in a manner than enhances cell-substrate adhesion. While the time course of induction suggests that CCN1 contributes to intermediate events in LPA action, the roles of CCN1 in LPA-mediated signal transduction have not been fully elucidated. This study utilized a comprehensive global proteomics approach to identify proteins up- or down-regulated in response to treatment of PC-3 cells with LPA for three hours, during the time of peak CCN1 levels. In addition, the effects of siRNA-mediated CCN1 knockdown on LPA responses were analyzed. The results show that, in addition to CCN1, LPA increased the levels of multiple proteins. Proteins up-regulated by LPA included metastasis-associated in colon cancer protein 1 (MACC1) and thrombospondin-1 (TSP1/THBS1); both MACC1 and TSP1 regulated cancer cell adhesion and motility. LPA down-regulated thioredoxin interacting protein (TXNIP). CCN1 knockdown suppressed the LPA-induced up-regulation of 30 proteins; these included MACC1 and TSP1, as confirmed by immunoblotting. Gene ontology and STRING analyses revealed multiple pathways impacted by LPA and CCN1. These results indicate that CCN1 contributes to LPA signaling cascades that occur during the intermediate phase after the initial stimulus. The study provides a rationale for the development of interventions to disrupt the LPA-CCN1 axis.

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 Šfrom feature 1, and (3) an aromatic ring ∼5-7 Šfrom 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.

Effect of Cimetidine on Metformin Pharmacokinetics and Endogenous Metabolite Levels in Rats.

Tubular secretion is a primary mechanism along with glomerular filtration for renal elimination of drugs and toxicants into urine. Organic cation transporters (OCTs) and multidrug and toxic extrusion (MATE) transporters facilitate the active secretion of cationic substrates, including drugs such as metformin and endogenous cations. We hypothesized that administration of cimetidine, an Oct/Mate inhibitor, will result in increased plasma levels and decreased renal clearance of metformin and endogenous Oct/Mate substrates in rats. A paired rat pharmacokinetic study was carried out in which metformin (5 mg/kg, intravenous) was administered as an exogenous substrate of Oct/Mate transporters to six Sprague-Dawley rats with and without cimetidine (100 mg/kg, intraperitoneal). When co-administered with cimetidine, metformin area under the curve increased significantly by 3.2-fold, and its renal clearance reduced significantly by 73%. Untargeted metabolomics was performed to investigate the effect of cimetidine on endogenous metabolome in the blood and urine samples. Over 8,000 features (metabolites) were detected in the blood, which were shortlisted using optimized criteria, i.e., a significant increase (P value < 0.05) in metabolite peak intensity in the cimetidine-treated group, reproducible retention time, and quality of chromatogram peak. The metabolite hits were classified into three groups that can potentially distinguish inhibition of i) extra-renal uptake transport or catabolism, ii) renal Octs, and iii) renal efflux transporters or metabolite formation. The metabolomics approach identified novel putative endogenous substrates of cationic transporters that could be tested as potential biomarkers to predict Oct/Mate transporter mediated drug-drug interactions in the preclinical stages. SIGNIFICANCE STATEMENT: Endogenous substrates of renal transporters in animal models could be used as potential biomarkers to predict renal drug-drug interactions in early drug development. Here we demonstrated that cimetidine, an inhibitor of organic cation transporters (Oct/Mate), could alter the pharmacokinetics of metformin and endogenous cationic substrates in rats. Several putative endogenous metabolites of Oct/Mate transporters were identified using metabolomics approach, which could be tested as potential transporter biomarkers to predict renal drug-drug interaction of Oct/Mate substrates.

Characterization of Gla proteoforms and non-Gla peptides of gamma carboxylated proteins: Application to quantification of prothrombin proteoforms in human plasma.

Gamma (γ) carboxylation is an essential post-translational modification in vitamin K-dependent proteins (VKDPs), involved in maintaining critical biological homeostasis. Alterations in the abundance or activity of these proteins have pharmacological and pathological consequences. Importantly, low levels of fully γ-carboxylated clotting factors increase plasma des-γ-carboxy precursors resulting in little or no biological activity. Therefore, it is important to characterize the levels of γ-carboxylation that reflect the active state of these proteins. The conventional enzyme-linked immunosorbent assay for protein induced by vitamin K absence or antagonist II (PIVKA-II) quantification uses an antibody that is not applicable to distinguish different γ-carboxylation states. Liquid chromatography-mass spectrometry (LC-MS) approaches have been utilized to distinguish different γ-carboxylated proteoforms, however, these attempts were impeded by poor sensitivity due to spontaneous neutral loss of CO2 and simultaneous cleavage of the backbone bond in the collision cell. In this study, we utilized an alkaline mobile phase in combination with polarity switching (positive and negative ionization modes) to simultaneously identify and quantify γ-carboxylated VKDPs. The method was applied to compare Gla proteomics of prothrombin (FII) in 10 µL plasma samples of healthy control and warfarin-treated adults. We also identified surrogate non-Gla peptides for seven other VKDPs to quantify total (active plus inactive) protein levels. The total protein approach (TPA) was used to quantify absolute levels of the VKDPs in human plasma.

Effect of probenecid on blood levels and renal elimination of furosemide and endogenous compounds in rats: Discovery of putative organic anion transporter biomarkers.

Transporter-mediated drug-drug interactions (DDIs) are assessed using probe drugs and in vitro and in vivo models during drug development. The utility of endogenous metabolites as transporter biomarkers is emerging for prediction of DDIs during early phases of clinical trials. Endogenous metabolites such as pyridoxic acid and kynurenic acid have shown potential to predict DDIs mediated by organic anion transporters (OAT1 and OAT3). However, these metabolites have not been assessed in rats as potential transporter biomarkers. We carried out a rat pharmacokinetic DDI study using probenecid and furosemide as OAT inhibitor and substrate, respectively. Probenecid administration led to a 3.8-fold increase in the blood concentrations and a 3-fold decrease in renal clearance of furosemide. High inter-individual and intra-day variability in pyridoxic acid and kynurenic acid, and no or moderate effect of probenecid administration on these metabolites suggest their limited utility for prediction of Oat-mediated DDI in rats. Therefore, rat blood and urine samples were further analysed using untargeted metabolomics. Twenty-one m/z features (out of >8000 detected features) were identified as putative biomarkers of rat Oat1 and Oat3 using a robust biomarker qualification approach. These m/z features belong to metabolic pathways such as fatty acid analogues, peptides, prostaglandin analogues, bile acid derivatives, flavonoids, phytoconstituents, and steroids, and can be used as a panel to decrease variability caused by processes other than Oats. When validated, these putative biomarkers will be useful in predicting DDIs caused by Oats in rats.

Analysis of the interplay of physiological response to food intake and drug properties in food-drug interactions.

The effect of food on oral drug absorption is determined by the complex interplay among gut physiological factors and drug properties. The currently used dissolution testing and classification systems (biopharmaceutics classification system, BCS or biopharmaceutics drug disposition classification system, BDDCS) do not account for dynamic changes in gastrointestinal physiology caused by food intake. This study aimed to identify key drug properties that influence food effect (FE) using supervised machine learning approaches. The analysis showed that drugs with high logP, dose number, and extraction ratio have a higher probability of positive FE, while drugs with low permeability and high efflux saturation index have a greater likelihood of negative FE. Weakly acidic drugs also showed a greater probability of positive FE, particularly at pKa >4.3. The importance of drug properties in predicting FE was ranked as logP, dose number, extraction ratio, pKa, and permeability. The accuracy of FE prediction using the models was compared with BCS and extended clearance classification system (ECCS). Overall, the likelihood or magnitude of FE depends on physiological changes to food intake such as altered bile acid secretion rate, intestinal metabolism, transport kinetics, and gastric emptying time, which should be considered along with drug properties (e.g., solubility, logP, and ionization) in predicting FE of orally administered drugs.