Metabolic Activation and Major Protein Target of a 1-Benzyl-3-carboxyazetidine Sphingosine-1-phosphate-1 Receptor Agonist

1-{4-[(4-Phenyl-5-trifluoromethyl-2-thienyl)­methoxy]­benzyl}­azetidine-3-carboxylic acid (MRL-A) is a potent sphingosine-1-phosphate-1 receptor agonist, with potential application as an immunosuppressant in organ transplantation or for the treatment of autoimmune diseases. When administered orally to rats, radiolabeled MRL-A was found to undergo metabolism to several reactive intermediates, and in this study, we have investigated its potential for protein modification in vivo and in vitro. MRL-A irreversibly modified liver and kidney proteins in vivo, in a dose- and time-dependent manner. The binding was found to occur selectively to microsomal and mitochondrial subcellular fractions. Following a nonspecific proteolytic digestion of liver and kidney proteins, a single major amino acid adduct was observed. This adduct was characterized with LC/MS/UV and NMR spectroscopy and was found to be the product of an unprecedented metabolic activation of the azetidine moiety leading to the formation of a ring-opened α,β-unsaturated imine conjugated to the ε-amino group of a lysine residue. The formation of this adduct was not inhibited when rats were pretreated with 1-aminobenzotriazole, indicating that P450 enzymes were not involved in the metabolic activation of MRL-A. Rather, our findings suggested that MRL-A underwent bioactivation via a β-oxidation pathway. Several other minor adducts were identified from protein hydrolysates and included lysine, serine, and cysteine conjugates of MRL-A. These minor adducts were also detected in microsomal incubations fortified with the cofactors for acyl-CoA synthesis and in hepatocytes. Trypsin digestion of crude liver homogenates from rats treated with radiolabeled MRL-A led to the identification of a single radioactive peptide. Its sequence, determined by LC/MS analysis, revealed that the target of the major reactive species of MRL-A in vivo is Lys676 of long chain acyl-CoA synthetase-1 (ACSL1). This lysine residue has been found to be critical for ACSL1 activity, and its modification has the potential to lead to biological consequences such as cardiac hypertrophy or thermogenesis dysregulation

Variability in P-Glycoprotein Inhibitory Potency (IC 50

A P-glycoprotein (P-gp) IC50 working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC 50 determinations. Each laboratory followed its in-house protocol to determine in vitro IC50 values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells-Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLCPK1- MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC50 values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC50 values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC50 values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratiobased equation generally resulted in severalfold lower IC 50 values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC50 values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC 50 determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided. © 2013 by The American Society for Pharmacology

Variability in P-Glycoprotein Inhibitory Potency (IC50) Using Various in Vitro Experimental Systems: Implications for Universal Digoxin Drug- Drug Interaction Risk Assessment Decision Criterias

A P-glycoprotein (P-gp) IC(50) working group was established with 23 participating pharmaceutical and contract research laboratories and one academic institution to assess interlaboratory variability in P-gp IC(50) determinations. Each laboratory followed its in-house protocol to determine in vitro IC(50) values for 16 inhibitors using four different test systems: human colon adenocarcinoma cells (Caco-2; eleven laboratories), Madin-Darby canine kidney cells transfected with MDR1 cDNA (MDCKII-MDR1; six laboratories), and Lilly Laboratories Cells—Porcine Kidney Nr. 1 cells transfected with MDR1 cDNA (LLC-PK(1)-MDR1; four laboratories), and membrane vesicles containing human P-glycoprotein (P-gp; five laboratories). For cell models, various equations to calculate remaining transport activity (e.g., efflux ratio, unidirectional flux, net-secretory-flux) were also evaluated. The difference in IC(50) values for each of the inhibitors across all test systems and equations ranged from a minimum of 20- and 24-fold between lowest and highest IC(50) values for sertraline and isradipine, to a maximum of 407- and 796-fold for telmisartan and verapamil, respectively. For telmisartan and verapamil, variability was greatly influenced by data from one laboratory in each case. Excluding these two data sets brings the range in IC(50) values for telmisartan and verapamil down to 69- and 159-fold. The efflux ratio-based equation generally resulted in severalfold lower IC(50) values compared with unidirectional or net-secretory-flux equations. Statistical analysis indicated that variability in IC(50) values was mainly due to interlaboratory variability, rather than an implicit systematic difference between test systems. Potential reasons for variability are discussed and the simplest, most robust experimental design for P-gp IC(50) determination proposed. The impact of these findings on drug-drug interaction risk assessment is discussed in the companion article (Ellens et al., 2013) and recommendations are provided