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

Abstract

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.