ABSTRACT:Predicting major clearance pathways of drugs is important in understanding their pharmacokinetic properties in clinical use, such as drug-drug interactions and genetic polymorphisms, and their subsequent pharmacological/toxicological effects. In this study, we established an in silico classification method to predict the major clearance pathways of drugs by identifying the boundaries of physicochemical parameters in empirical decisions for each clearance pathway. It requires only four physicochemical parameters [charge, molecular weight (MW), lipophilicity (log D), and protein unbound fraction in plasma (f up )] that were predicted from their molecular structures without performing any benchwork experiments. The training dataset consisted of 141 approved drugs whose major clearance pathways were determined to be metabolism by CYP3A4, CYP2C9, and CYP2D6, hepatic uptake by OATPs, or renal excretion in an unchanged form. After grouping by charge, each drug was plotted in a three-dimensional space according to three axes of MW, log D, and f up . Then, rectangular boxes for each clearance pathway were drawn mathematically under the criterion of "maximizing F value (harmonic mean of precision and recall) with minimum volume," yielding to a precision of 88%, which was confirmed through two types of validation: leave-one-out method and validation using a new dataset. With further modification toward multiple pathways and/or other pathways, not only would this in silico classification system be useful for industrial scientists at the early stage of drug development, which can lead to the selection of candidate compounds with optimal pharmacokinetic properties, but also for regulators in evaluating new drugs and giving regulatory requirements that are pharmacokinetically reasonable.Once a drug enters the human body, it undergoes detoxification by the complementary functions of a wide variety of metabolic enzymes and transporters, resulting in numerous clearance pathways such as urinary elimination through glomerular filtration and renal tubular excretion, passive diffusion into the liver followed by hepatic metabolism by cytochrome P450 (P450) enzymes to an inactive metabolite, or hepatic uptake by transporters followed by excretion into the bile and then into the feces. The major clearance pathway of drugs is one of the most important pharmacokinetic features relevant for its clinical use. Understanding the major clearance pathways would enable prediction of the changes in the systemic exposure of a drug caused by drug-drug interactions or genetic polymorphisms of enzymes and transporters. Some drugs have been withdrawn from the market owing to fatal side effects that often occurred by drug-drug interactions of their major clearance pathways, such as cerivastatin and its interaction with gemfibrozil (Shitara et al., 2004). The withdrawals might have been avoided by clarifying their major clearance pathways in the human body and by recognizing the severity of drug interactions, leading to better decision-making b...

Ct-OATP1B3 is capable of transporting its substrates into cancer cells. Its mRNA expression is regulated by DNA methylation-dependent gene silencing involving MBD2.

Tissue-specific expression of transporters is tightly linked with their physiological functions through the regulation of the membrane transport of their substrates. We hypothesized that epigenetic regulation underlies the tissue-specific expression of mouse liver-specific transporters (Oatp1b2/ Slco1b2, Ntcp/Slc10a1, Bsep/Abcb11, and Abcg5/g8). We examined their DNA methylation and histone modification profiles near the transcriptional start site (TSS) in the liver, kidney, and cerebrum. Genome-wide DNA methylation profiling with tissue-dependent differentially methylated region profiling with restriction tag-mediated amplification and subsequent bisulfite genomic sequencing demonstrated that the CpG dinucleotides around the TSS of Oatp1b2 (from Ϫ515 to ϩ149 CpGs), Ntcp (from Ϫ481 to ϩ495 CpGs), Bsep (from Ϫ339 to ϩ282 CpGs), and Abcg5/g8 (from Ϫ161 to ϩ5 CpGs for Abcg5, i.e., from Ϫ213 to Ϫ48 CpGs for Abcg8) were hypomethylated in the liver and hypermethylated in the kidney and cerebrum. The opposite pattern was observed for Pept2/ Slc15a2 (from Ϫ638 to ϩ4 CpGs), which was expressed in the kidney and cerebrum but not in the liver. These DNA methylation profiles are consistent with the tissue distribution of these transporters. A chromatin immunoprecipitation assay demonstrated that the histone H3 associated with Oatp1b2, Ntcp, Bsep, and Abcg5/g8 promoters was hyperacetylated in the liver but was acetylated very little in the kidney and cerebrum, whereas the upstream region of Pept2 was hyperacetylated only in the kidney and cerebrum. These results suggest the involvement of epigenetic systems in the tissue-specific expression of mouse transporters Oatp1b2, Ntcp, Bsep, Abcg5/ g8, and Pept2.During the past two decades, extensive research has sought to uncover the molecular characteristics of transporters to explain their physiological and pathological functions. These transporters comprise more than 300 genes that are now classified into the solute carrier (SLC) and ATP-binding cassette (ABC) transporter superfamilies. Transporters show tissue-specific expression patterns that have critical implications for the physiological function of certain tissues (Borst and Elferink, 2002;Kusuhara and Sugiyama, 2002;Hediger et al., 2004; Stefkova et al., 2004;Shitara et al., 2006).Liver tissue is one of the most important tissues in terms of the physiological turnover of endogenous compounds, such as bile acids and sterols, and the clearance of exogenous substances, including clinically used drugs. Several transporters are closely related to the hepatobiliary transport of these compounds. SLC-type transporters mediate the hepatic uptake of bile acids and xenobiotic organic anions, and ABC transporters then contribute to the biliary efflux of bile acids, sterols, and xenobiotic compounds and their metabolites (Faber et al., 2003;Chandra and Brouwer, 2004). Numerous reports suggest the involvement of liver-enriched transcription factors, such as hepatocyte nuclear factors (HNFs) 1, 3, and 4, and proteins of the CCAA...

DNA methylation-dependent gene silencing is one of the most characterized mechanisms in epigenetic regulation of gene expression. This process is thought to influence the ability of hepatocyte nuclear factor 1 (HNF1) to transactivate organic anion transporter expression in the liver and kidney. To evaluate this further we profiled 282 mouse solute carrier transporters by examining regions near their transcription start sites for tissue-dependent differentially methylated regions (T-DMR) using restriction tag-mediated amplification to determine T-DMR disparity between the liver and kidney. Forty-two of these were associated with T-DMR tags hypomethylated in the kidney but hypermethylated in the liver. Computational analysis found a canonical HNF1-binding motif within 1 kbp of the promoter region of 13 carriers including the amino acid transporters Slc6a19, Slc6a20, Slc7a8 and Slc7a9; all expressed predominantly in the kidney. Bisulfite genomic sequencing found that CpG dinucleotides neighboring the T-DMR tags were hypomethylated in the kidney compared with the liver. The Hnf1alpha promoter region itself contained a T-DMR hypomethylated in the liver and kidney but hypermethylated in the cerebrum, consistent with the tissue distribution of Hnf1alpha. Taken together, our results show a central role of DNA methylation in the kidney-specific expression of amino acid transporters thus determining both the tissue distribution of their master regulator, Hnf1alpha, and its interaction with downstream genes.