The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform

Maria L. H. Vlaming - One of the best experts on this subject based on the ideXlab platform.

  • Generation of Bayesian prediction models for OATP-mediated drug–drug interactions based on inhibition screen of OATP1B1, OATP1B1∗15 and OATP1B3
    European Journal of Pharmaceutical Sciences, 2015
    Co-Authors: E. Van De Steeg, J. Venhorst, Harm T. Jansen, I.h.g. Nooijen, J. Degroot, Heleen M. Wortelboer, Maria L. H. Vlaming
    Abstract:

    Human organic anion-transporting polypeptide 1B1 (OATP1B1) and OATP1B3 are important hepatic uptake transporters. Early assessment of OATP1B1/1B3-mediated drug-drug interactions (DDIs) is therefore important for successful drug development. A promising approach for early screening and prediction of DDIs is computational modeling. In this study we aimed to generate a rapid, single Bayesian prediction model for OATP1B1, OATP1B1∗15 and OATP1B3 inhibition. Besides our previously generated HEK-OATP1B1 and HEK-OATP1B1∗15 cells, we now generated and characterized HEK-OATP1B3 cells. Using these cell lines we investigated the inhibitory potential of 640 FDA-approved drugs from a commercial library (10 μM) on the uptake of [3H]-estradiol-17β-d-glucuronide (1 μM) by OATP1B1, OATP1B1∗15, and OATP1B3. Using a cut-off of ≥60% inhibition, 8% and 7% of the 640 drugs were potent OATP1B1 and OATP1B1∗15 inhibitors, respectively. Only 1% of the tested drugs significantly inhibited OATP1B3, which was not sufficient for Bayesian modeling. Modeling of OATP1B1 and OATP1B1∗15 inhibition revealed that presence of conjugated systems and (hetero)cycles with acceptor/donor atoms in- or outside the ring enhance the probability of a molecule binding these transporters. The overall performance of the model for OATP1B1 and OATP1B1∗15 was ≥80%, including evaluation with a true external test set. Our Bayesian classification model thus represents a fast, inexpensive and robust means of assessing potential binding of new chemical entities to OATP1B1 and OATP1B1∗15. As such, this model may be used to rank compounds early in the drug development process, helping to avoid adverse effects in a later stage due to inhibition of OATP1B1 and/or OATP1B1∗15. Chemicals/CAS: abamectin, 71751-41-2; acemetacin, 53164-05-9; atazanavir, 198904-31-3; bromocriptine mesilate, 22260-51-1; clarithromycin, 81103-11-9; clobetasol propionate, 25122-46-7; dihydroergocristine methanesulfonate, 24730-10-7; dipyridamole, 58-32-2; docetaxel, 114977-28-5; estradiol, 50-28-2; Fluindostatin, 93957-54-1; fosinopril, 88889-14-9, 98048-97-6; losartan, 114798-26-4; mifepristone, 84371-65-3; nicardipine, 54527-84-3, 55985-32-5; olmesartan, 144689-63-4; pranlukast, 103177-37-3; pyrantel embonate, 22204-24-6; rapamycin, 53123-88-9; rifampicin, 13292-46-1; rifamycin, 6998-60-3, 14897-39-3, 15105-92-7; salazosulfapyridine, 599-79-1; suramin, 129-46-4, 145-63-1; telmisartan, 144701-48-4; tibolone, 5630-53-5; troglitazone, 97322-87-7

E. Van De Steeg - One of the best experts on this subject based on the ideXlab platform.

  • Generation of Bayesian prediction models for OATP-mediated drug–drug interactions based on inhibition screen of OATP1B1, OATP1B1∗15 and OATP1B3
    European Journal of Pharmaceutical Sciences, 2015
    Co-Authors: E. Van De Steeg, J. Venhorst, Harm T. Jansen, I.h.g. Nooijen, J. Degroot, Heleen M. Wortelboer, Maria L. H. Vlaming
    Abstract:

    Human organic anion-transporting polypeptide 1B1 (OATP1B1) and OATP1B3 are important hepatic uptake transporters. Early assessment of OATP1B1/1B3-mediated drug-drug interactions (DDIs) is therefore important for successful drug development. A promising approach for early screening and prediction of DDIs is computational modeling. In this study we aimed to generate a rapid, single Bayesian prediction model for OATP1B1, OATP1B1∗15 and OATP1B3 inhibition. Besides our previously generated HEK-OATP1B1 and HEK-OATP1B1∗15 cells, we now generated and characterized HEK-OATP1B3 cells. Using these cell lines we investigated the inhibitory potential of 640 FDA-approved drugs from a commercial library (10 μM) on the uptake of [3H]-estradiol-17β-d-glucuronide (1 μM) by OATP1B1, OATP1B1∗15, and OATP1B3. Using a cut-off of ≥60% inhibition, 8% and 7% of the 640 drugs were potent OATP1B1 and OATP1B1∗15 inhibitors, respectively. Only 1% of the tested drugs significantly inhibited OATP1B3, which was not sufficient for Bayesian modeling. Modeling of OATP1B1 and OATP1B1∗15 inhibition revealed that presence of conjugated systems and (hetero)cycles with acceptor/donor atoms in- or outside the ring enhance the probability of a molecule binding these transporters. The overall performance of the model for OATP1B1 and OATP1B1∗15 was ≥80%, including evaluation with a true external test set. Our Bayesian classification model thus represents a fast, inexpensive and robust means of assessing potential binding of new chemical entities to OATP1B1 and OATP1B1∗15. As such, this model may be used to rank compounds early in the drug development process, helping to avoid adverse effects in a later stage due to inhibition of OATP1B1 and/or OATP1B1∗15. Chemicals/CAS: abamectin, 71751-41-2; acemetacin, 53164-05-9; atazanavir, 198904-31-3; bromocriptine mesilate, 22260-51-1; clarithromycin, 81103-11-9; clobetasol propionate, 25122-46-7; dihydroergocristine methanesulfonate, 24730-10-7; dipyridamole, 58-32-2; docetaxel, 114977-28-5; estradiol, 50-28-2; Fluindostatin, 93957-54-1; fosinopril, 88889-14-9, 98048-97-6; losartan, 114798-26-4; mifepristone, 84371-65-3; nicardipine, 54527-84-3, 55985-32-5; olmesartan, 144689-63-4; pranlukast, 103177-37-3; pyrantel embonate, 22204-24-6; rapamycin, 53123-88-9; rifampicin, 13292-46-1; rifamycin, 6998-60-3, 14897-39-3, 15105-92-7; salazosulfapyridine, 599-79-1; suramin, 129-46-4, 145-63-1; telmisartan, 144701-48-4; tibolone, 5630-53-5; troglitazone, 97322-87-7

K P Hanley - One of the best experts on this subject based on the ideXlab platform.

  • HMG-CoA reductase inhibitors perturb fatty acid metabolism and induce peroxisomes in keratinocytes
    Journal of Lipid Research, 1992
    Co-Authors: M L Williams, G K Menon, K P Hanley
    Abstract:

    : Topical lovastatin stimulates epidermal fatty acid synthesis in vivo; therefore, studies were undertaken to examine the effects of HMG-CoA reductase inhibitors on fatty acid metabolism in cultured keratinocytes. When exposed to Fluindostatin or lovastatin for greater than or equal to 24 h, keratinocytes in serum-free media accumulated nile red-fluorescent lipid droplets. By 72 h, the triacylglycerol and phospholipid content were increased 2.5- and 1.3-fold, respectively. Reductase inhibitors (1-10 microM) increased fatty acid synthesis approximately 1.5-fold; increased synthesis was noted only after greater than 15 h exposure and was distributed among phospholipids and triacylglycerols. Oxidation of [14C]palmitate to CO2 was decreased greater than 50% in inhibitor-treated cultures, and label accumulated in triacylglycerols. Inhibitor-treated keratinocytes exhibited increased numbers of peroxisomes, using diaminobenzidene ultracytochemistry. Peroxisomal hyperplasia was also demonstrated by increased catalase activity (1.5- to 2.5-fold), increased dihydroxyacetone phosphate acyltransferase activity (1.4-fold) and increased peroxisomal (KCN-insensitive) fatty acid oxidation (1.4-fold) in inhibitor-treated cultures. Thus HMG-CoA reductase inhibitors increase fatty acid synthesis, induce triacylglycol and phospholipid accumulation, and induce peroxisomes in cultured keratinocytes. Coincubations with either low density lipoproteins or 25-hydroxycholesterol prevented both the peroxisomal hyperplasia and increased fatty acid synthesis, suggesting that these effects of reductase inhibitors may be linked to their effects on the cholesterol biosynthetic pathway.

J J Wright - One of the best experts on this subject based on the ideXlab platform.

  • Selective inhibition of cholesterol synthesis in liver versus extrahepatic tissues by HMG-CoA reductase inhibitors.
    Journal of Lipid Research, 1990
    Co-Authors: Rex A. Parker, R. W. Clark, T L Lanier, R A Grosso, J J Wright
    Abstract:

    Hepatic specificity of inhibitors of 3-hydroxy-3- methylglutaryl coenzyme A (HMG-CoA) reductase may be achieved by efficient first-pass liver extraction resulting in low circulating drug levels, as with lovastatin, or by lower cellular uptake in peripheral tissues, seen with pravastatin. BMY-21950 and its lactone form BMY-22089, new synthetic inhibitors of HMG-CoA reductase, were compared with the major reference agent lovastatin and with the synthetic inhibitor Fluindostatin in several in vitro and in vivo models of potency and tissue selec- tivity. The kinetic mechanism and the potency of BMY-21950 as a competitive inhibitor of isolated HMG-CoA reductase were comparable to the reference agents. The inhibitory potency (cholesterol synthesis assayed by 3H20 or ( ''Clacetate incor- poration) of BMY-21950 in rat hepatocytes (IC5,, = 21 nM) and dog liver slices (IC50 = 23 nM) equalled or exceeded the poten- cies of the reference agents. Hepatic cholesterol synthesis in vivo in rats was effectively inhibited by BMY-21950 and its lactone form BMY-22089 (ED50 = 0.1 mg/kg P.o.), but oral doses (20 mg/kg) that suppressed liver synthesis by 83-95 % inhibited sterol synthesis by only 17-24% in the ileum. In contrast, equivalent doses of lovastatin markedly inhibited cholesterol synthesis in both organs. In tissue slices from rat ileum, cell dis- persions from testes, adrenal, and spleen, and in bovine ocular lens epithelial cells, BMY-21950 inhibited sterol synthesis weakly in vitro with IC50 values 76- and 188-times higher than in hepato- cytes; similar effects were seen for BMY-22089. However, the IC50 ratios (tissue/hepatocyte) for lovastatin and Fluindostatin were near unity in these models. Thus, BMY-21950 and BMY-22089 are the first potent synthetic HMG-CoA reductase inhibitors that possess a very high degree of liver selectivity based upon differential inhibition sensitivities in tissues. This cellular uptake-based property of hepatic specificity of BMY- 21950 and BMY-22089, also manifest in pravastatin, is bio- chemically distinct from the pharmacodynamic-based dispo- sition of lovastatin, which along with Fluindostatin exhibited potent inhibition in all tissues that were exposed to it. -Parker, R. A., R. W. Clark, S-Y. Sit, T. L. Lanier, R. A. Grosso, and J. J. K. Wright. Selective inhibition of cholesterol synthesis in liver versus extrahepatic tissues by HMG-CoA reductase inhibi- tors. J Lipid Res. 1990. 31: 1271-1282. The liver is the primary organ for regulation of total body cholesterol homeostasis in mammalian systems. Hepatic coordination of cholesterol biosynthesis with assembly, secretion, and uptake of plasma lipoproteins depends in part on cellular mechanisms coupling the ac- tivities of the key enzymes of sterol synthesis with the receptors governing lipoprotein clearance (1). Thus an im- portant target for pharmacological regulation of plasma LDL cholesterol is liver 3-hydroxy-3-methylglutaryl coen- zyme A reductase (HMG-CoA reductase), the rate- limiting enzyme in the pathway of cholesterol biosynthesis. The rationale for the use of HMG-CoA reductase inhibi- tors in the treatment of hypercholesterolemia has been convincingly established by the recent clinical successes of lovastatin and its relatives (2). The efficacy, tolerance, and defined mode of action of these naturally derived products of microbial fermentation has led to a continuing search for new inhibitors of the reductase. The recent discussion in the literature regarding the possibility of deleterious side effects of HMG-CoA reduc- tase inhibitors in therapeutic situations (2-4) centers in part upon the degree to which these agents exert their inhibitory influence in extrahepatic tissues. Beyond the requirements of cholesterol for cell membranes, interfer- ence with isoprenoid metabolism has been demonstrated to alter fundamental cellular processes such as S-phase DNA synthesis and progression through the cell cycle (5). Lovastatin at relatively high concentrations decreased the replicative capacity of endothelial cells, smooth muscle cells, and fibroblasts (6). Recently, pravastatin, a hydroxy- lated analogue of lovastatin, was shown to inhibit potently in both ileum and liver in ex vivo studies in rats while ex- Abbreviations: HMG, 3-hydroxy-3-methylglutaryl; LDL, low density lipoprotein; HPLC, high performance liquid chromatography.

Heleen M. Wortelboer - One of the best experts on this subject based on the ideXlab platform.

  • Generation of Bayesian prediction models for OATP-mediated drug–drug interactions based on inhibition screen of OATP1B1, OATP1B1∗15 and OATP1B3
    European Journal of Pharmaceutical Sciences, 2015
    Co-Authors: E. Van De Steeg, J. Venhorst, Harm T. Jansen, I.h.g. Nooijen, J. Degroot, Heleen M. Wortelboer, Maria L. H. Vlaming
    Abstract:

    Human organic anion-transporting polypeptide 1B1 (OATP1B1) and OATP1B3 are important hepatic uptake transporters. Early assessment of OATP1B1/1B3-mediated drug-drug interactions (DDIs) is therefore important for successful drug development. A promising approach for early screening and prediction of DDIs is computational modeling. In this study we aimed to generate a rapid, single Bayesian prediction model for OATP1B1, OATP1B1∗15 and OATP1B3 inhibition. Besides our previously generated HEK-OATP1B1 and HEK-OATP1B1∗15 cells, we now generated and characterized HEK-OATP1B3 cells. Using these cell lines we investigated the inhibitory potential of 640 FDA-approved drugs from a commercial library (10 μM) on the uptake of [3H]-estradiol-17β-d-glucuronide (1 μM) by OATP1B1, OATP1B1∗15, and OATP1B3. Using a cut-off of ≥60% inhibition, 8% and 7% of the 640 drugs were potent OATP1B1 and OATP1B1∗15 inhibitors, respectively. Only 1% of the tested drugs significantly inhibited OATP1B3, which was not sufficient for Bayesian modeling. Modeling of OATP1B1 and OATP1B1∗15 inhibition revealed that presence of conjugated systems and (hetero)cycles with acceptor/donor atoms in- or outside the ring enhance the probability of a molecule binding these transporters. The overall performance of the model for OATP1B1 and OATP1B1∗15 was ≥80%, including evaluation with a true external test set. Our Bayesian classification model thus represents a fast, inexpensive and robust means of assessing potential binding of new chemical entities to OATP1B1 and OATP1B1∗15. As such, this model may be used to rank compounds early in the drug development process, helping to avoid adverse effects in a later stage due to inhibition of OATP1B1 and/or OATP1B1∗15. Chemicals/CAS: abamectin, 71751-41-2; acemetacin, 53164-05-9; atazanavir, 198904-31-3; bromocriptine mesilate, 22260-51-1; clarithromycin, 81103-11-9; clobetasol propionate, 25122-46-7; dihydroergocristine methanesulfonate, 24730-10-7; dipyridamole, 58-32-2; docetaxel, 114977-28-5; estradiol, 50-28-2; Fluindostatin, 93957-54-1; fosinopril, 88889-14-9, 98048-97-6; losartan, 114798-26-4; mifepristone, 84371-65-3; nicardipine, 54527-84-3, 55985-32-5; olmesartan, 144689-63-4; pranlukast, 103177-37-3; pyrantel embonate, 22204-24-6; rapamycin, 53123-88-9; rifampicin, 13292-46-1; rifamycin, 6998-60-3, 14897-39-3, 15105-92-7; salazosulfapyridine, 599-79-1; suramin, 129-46-4, 145-63-1; telmisartan, 144701-48-4; tibolone, 5630-53-5; troglitazone, 97322-87-7