Identification of the human cytochrome P450 enzymes involved in the in vitro biotransformation of lynestrenol and norethindrone

Korhonen, Tuomas; Turpeinen, Miia; Tolonen, Ari; Laine, Kari; Pelkonen, Olavi

doi:10.1016/j.jsbmb.2007.09.025

Cited by 35 publications

(28 citation statements)

References 42 publications

(50 reference statements)

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“…Interestingly, the M02 his mutant was able to form most of the active human relevant metabolites, albeit in different ratios. Recently, Korhonen et al reported the elucidation of human CYPs involved in the metabolism of NET and proposed identities based on high resolution MS in positive ion mode and fragmentation studies with a triple quadrupole MS [44]. Our findings are in accordance with the published results, but due to the additional dimensions of our receptor affinity detection system and the utilization of fast polarity switching in full MS mode, we were able to identify additional metabolites with biological relevance.…”

Section: Preparative Scale Biosynthesis and Nmr Analysissupporting

confidence: 90%

Determination and identification of estrogenic compounds generated with biosynthetic enzymes using hyphenated screening assays, high resolution mass spectrometry and off-line NMR

Vlieger

Kolkman

Ampt

et al. 2010

Journal of Chromatography B

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Section: Preparative Scale Biosynthesis and Nmr Analysissupporting

confidence: 90%

Determination and identification of estrogenic compounds generated with biosynthetic enzymes using hyphenated screening assays, high resolution mass spectrometry and off-line NMR

Vlieger

Kolkman

Ampt

et al. 2010

Journal of Chromatography B

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“…Norethindrone undergoes extensive biotransformation, primarily via reduction, followed by sulfate and glucuronide conjugation [41]. In a single-center, three-period, fixed-sequence study in 20 healthy female volunteers receiving ethinylestradiol plus norethindrone, boceprevir did not affect norethindrone AUC 24 but slightly reduced C max (Table 2) [42].…”

Section: Ethinylestradiol/norethindronementioning

confidence: 93%

Clinical Pharmacology Profile of Boceprevir, a Hepatitis C Virus NS3 Protease Inhibitor: Focus on Drug–Drug Interactions

et al. 2015

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Boceprevir is a potent, orally administered ketoamide inhibitor that targets the active site of the hepatitis C virus (HCV) non-structural (NS) 3 protease. The addition of boceprevir to peginterferon plus ribavirin resulted in higher rates of sustained virologic response (SVR) than for peginterferon plus ribavirin alone in phase III studies in both previously treated and untreated patients with HCV infection. Because boceprevir is metabolized by metabolic routes common to many other drugs, and is an inhibitor of cytochrome P450 (CYP) 3A4/5, there is a high potential for drug-drug interactions when boceprevir is administered with other therapies, particularly when treating patients with chronic HCV infection who are often receiving other medications concomitantly. Boceprevir is no longer widely used in the US or EU due to the introduction of second-generation treatments for HCV infection. However, in many other geographic regions, first-generation protease inhibitors such as boceprevir continue to form an important treatment option for patients with HCV infection. This review summarizes the interactions between boceprevir and other therapeutic agents commonly used in this patient population, indicating dose adjustment requirements where needed. Most drug interactions do not affect boceprevir plasma concentrations to a clinically meaningful extent, and thus efficacy is likely to be maintained when boceprevir is coadministered with the majority of other therapeutics. Overall, the drug-drug interaction profile of boceprevir suggests that this agent is suitable for use in a wide range of HCV-infected patients receiving concomitant therapies.

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“…In addition to these, CYP-activity phenotyped liver preparations are used to reflect the formation of the metabolites, so that metabolite formation correlating with certain CYP isoform activity in the livers suggests high involvement of that particular CYP isoform. A large number of studies for identification of the CYP enzyme responsible for metabolism of some particular compound are reported and some of the most recent ones are cited here [93][94][95][96][97]. Similarly, articles describing the role of analytical techniques in the identification of UDP-glucuronosyltransferase enzyme isoforms responsible for glucuronide conjugation have been published [98][99][100].…”

Section: Hepatic Metabolism Studiesmentioning

confidence: 99%

“…Important issues in quantitative predictions also include the nonspecific binding to in vitro extRahepatic tissues All other tissues in the body apart from the liver, with variable competencies to biotransform drugs future science group Predicting in vivo drug metabolites | Review preparations [112,113] and expression of membrane transporters [114,115]. Moreover, the overall metabolic rate differs in various in vitro models [96]. Therefore, short in vitro incubation times may prevent representative accumulation of late stage products of sequential metabolism.…”

Section: General Prerequisites For In Vitro-in Vivo Extrapolationmentioning

confidence: 99%

From Known Knowns to Known Unknowns: Predicting in Vivo Drug Metabolites

Pelkonen

Tolonen²,

Korjamo³

et al. 2009

Bioanalysis

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'It is better to be useful than perfect'. This review attempts to critically cover and assess the currently available approaches and tools to answer the crucial question: Is it possible (and if it is, to what extent is it possible) to predict in vivo metabolites and their abundances on the basis of in vitro and preclinical animal studies? In preclinical drug development, it is possible to produce metabolite patterns from a candidate drug by virtual means (i.e., in silico models), but these are not yet validated. However, they may be useful to cover the potential range of metabolites. In vitro metabolite patterns and apparent relative abundances are produced by various in vitro systems employing tissue preparations (mainly liver) and in most cases using liquid chromatography-mass spectrometry analytical techniques for tentative identification. The pattern of the metabolites produced depends on the enzyme source; the most comprehensive source of drug-metabolizing enzymes is cultured human hepatocytes, followed by liver homogenate fortified with appropriate cofactors. For specific purposes, such as the identification of metabolizing enzyme(s), recombinant enzymes can be used. Metabolite data from animal in vitro and in vivo experiments, despite known species differences, may help pinpoint metabolites that are not apparently produced in in vitro human systems, or suggest alternative experimental approaches. The range of metabolites detected provides clues regarding the enzymes attacking the molecule under study. We also discuss established approaches to identify the major enzymes. The last question, regarding reliability and robustness of metabolite extrapolations from in vitro to in vivo, both qualitatively and quantitatively, cannot be easily answered. There are a number of examples in the literature suggesting that extrapolations are generally useful, but there are only a few systematic and comprehensive studies to validate in vitro-in vivo extrapolations. In conclusion, extrapolation from preclinical metabolite data to the in vivo situation is certainly useful, but it is not known to what extent.

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Identification of the human cytochrome P450 enzymes involved in the in vitro biotransformation of lynestrenol and norethindrone

Cited by 35 publications

References 42 publications

Determination and identification of estrogenic compounds generated with biosynthetic enzymes using hyphenated screening assays, high resolution mass spectrometry and off-line NMR

Determination and identification of estrogenic compounds generated with biosynthetic enzymes using hyphenated screening assays, high resolution mass spectrometry and off-line NMR

Clinical Pharmacology Profile of Boceprevir, a Hepatitis C Virus NS3 Protease Inhibitor: Focus on Drug–Drug Interactions

From Known Knowns to Known Unknowns: Predicting in Vivo Drug Metabolites

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