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 doesn9t 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.

Although the United States and Europe have shifted to the prescription use of oral diclofenac due to several serious incidences of cardiotoxicity, it is one of the most commonly used over‐the‐counter (OTC) pain medicines in major parts of the world. We elucidated the quantitative and tissue‐specific contribution of uridine diphosphate‐glucuronosyltransferases 17 (UGT2B17) in diclofenac metabolism and pharmacokinetics (PK). UGT2B17 is one of most deleted genes in humans with the gene deletion frequency ranging from ~ 20% in White population to 90% in Japanese population. The human intestinal and liver microsomes isolated from the high‐UGT2B17 expressing individuals showed 21‐ and 4‐fold greater rate of diclofenac glucuronide (DG) formation than in the null‐UGT2B17 carriers, respectively. The greater contribution of intestinal UGT2B17 was confirmed by a strong correlation (R = 0.78, P < 0.001) between UGT2B17 abundance and DG formation in individual intestinal microsomes (n = 14). However, because UGT2B17 is a minor UGT isoform in the liver, DG formation rate correlated better with the expression of UGT2B7. The proteomics‐informed physiologically‐based pharmacokinetic (PBPK) model explains the reported higher exposure of diclofenac in women consistent with ~ 3‐fold lower expression of UGT2B17. Similarly, our in silico predictions also corroborate with the reported higher exposure and lower standard clinical dose of diclofenac in Japanese population. Therefore, variable UGT2B17 mediated metabolism of oral diclofenac is a cause of concern, especially in the developing countries where it is still used as an OTC drug. The ontogeny data of UGTs in human hepatocytes can be utilized in developing PBPK models for predicting PK in the pediatric population.

Characterization of accurate compositions and total abundance of homologous drug-metabolizing enzymes, such as UDP glucuronosyltransferases (UGTs), is important for predicting the fractional contribution of individual isoforms involved in the metabolism of a drug for applications in physiologically based pharmacokinetic (PBPK) modeling. Conventional targeted proteomics utilizes surrogate peptides, which often results in high technical and inter-laboratory variability due to peptide-specific digestion efficiency leading to data inconsistencies. To address this problem, we developed a novel universal conserved-plus-surrogate peptide (CPSP) approach for determining the accurate compositions and total or cumulative abundance of homologous UGTs in commercially available pooled human liver microsomes (HLM), human intestinal microsomes (HIM), human kidney microsomes (HKM), and human liver S9 (HLS9) fractions. The relative percent composition of UGT1A and UGT2B isoforms in human liver was 35:5:36:11:13 for UGT1A1:1A3:1A4:1A6:1A9, and 20:32:22:21:5 for UGT2B4:2B7:2B10:2B15:2B17. The human kidney and intestine also show unique compositions of UGT1As and UGT2Bs. The reproducibility of the approach was validated by assessing correlations of UGT compositions between HLM and HLS9 (R2>0.91). The analysis of conserved peptides also provided the absolute abundance for individual UGT isoforms included in this investigation as well as the total abundance (pmol/mg protein) of UGT1As and UGT2Bs across tissues, i.e., 268 and 342 (HLM), 21 and 92 (HIM), 138 and 99 (HKM), respectively. In summary, the CPSP approach could be utilized for applications in the in-vitro to in-vivo extrapolation (IVIVE) of drug metabolism and PBPK modeling. Significance Statement We quantified the absolute compositions and total abundance of UGTs in human liver, intestine, and kidney microsomes using a novel CPSP approach. Unlike the conventional surrogate peptide-based targeted proteomics, the CPSP approach addresses the surrogate peptide-specific variability in the determination of the absolute composition of UGTs. The data presented in this manuscript are applicable for the estimation of the fraction metabolized (f_m) by individual UGTs towards better IVIVE of UGT-mediated drug metabolism in the human liver, intestine, and kidney.