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Russell DA, Cerny MA. High-throughput cytochrome P450 loss and metabolic intermediate complex assays to aid in designing out of CYP3A inactivation. Methods Enzymol 2023; 690:341-368. [PMID: 37858534 DOI: 10.1016/bs.mie.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023]
Abstract
Time-dependent inactivation (TDI) of cytochrome P450 (CYP) enzymes may result in clinical drug-drug interactions (DDIs). Therefore, designing out of CYP TDI prior to advancing a compound to clinical development is highly desirable. As TDI of CYP3A is a common occurrence in small molecule drug discovery, high-throughput methods are sought to help identify the mechanism of inactivation and enable design strategies to mitigate CYP3A TDI. CYP inactivation via modification or destruction of the prosthetic heme group results in loss of the ability of the enzyme to bind carbon monoxide. Additionally, formation of a tight binding complex with the heme iron, referred to as a metabolic intermediate (MI) complex, also results in enzyme inactivation. The methods described herein provide a high-throughput means of identifying and comparing compounds for their ability to inactivate via destruction/modification of the heme via loss of the ability to bind carbon monooxide, as well as via formation of an MI complex.
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Affiliation(s)
- Drake A Russell
- Department of Medicinal Chemistry, University of Washington, Seattle, WA, United States
| | - Matthew A Cerny
- Pharmacokinetics, Dynamics and Metabolism, Pfizer, Inc., Groton, CT, United States.
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Sugahara G, Ishida Y, Lee JJ, Li M, Tanaka Y, Eoh H, Higuchi Y, Saito T. Long-term cell fate and functional maintenance of human hepatocyte through stepwise culture configuration. FASEB J 2023; 37:e22750. [PMID: 36607308 PMCID: PMC9830592 DOI: 10.1096/fj.202201292rr] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 12/13/2022] [Accepted: 12/20/2022] [Indexed: 01/07/2023]
Abstract
Human hepatocyte culture system represents by far the most physiologically relevant model for our understanding of liver biology and diseases; however, its versatility has been limited due to the rapid and progressive loss of genuine characteristics, indicating the inadequacy of in vitro milieu for fate maintenance. This study, therefore, is designed to define environmental requirements necessary to sustain the homeostasis of terminally differentiated hepatocytes. Our study reveals that the supplementation of dimethyl sulfoxide (DMSO) is indispensable in mitigating fate deterioration and promoting adaptation to the in vitro environment, resulting in the restoration of tight cell-cell contact, cellular architecture, and polarity. The morphological recovery was overall accompanied by the restoration of hepatocyte marker gene expression, highlighting the interdependence between the cellular architecture and the maintenance of cell fate. However, beyond the recovery phase culture, DMSO supplementation is deemed detrimental due to the potent inhibitory effect on a multitude of hepatocyte functionalities while its withdrawal results in the loss of cell fate. In search of DMSO substitute, our screening of organic substances led to the identification of dimethyl sulfone (DMSO2), which supports the long-term maintenance of proper morphology, marker gene expression, and hepatocytic functions. Moreover, hepatocytes maintained DMSO2 exhibited clinically relevant toxicity in response to prolonged exposure to xenobiotics as well as alcohol. These observations suggest that the stepwise culture configuration consisting of the consecutive supplementation of DMSO and DMSO2 confers the microenvironment essential for the fate and functional maintenance of terminally differentiated human hepatocytes.
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Affiliation(s)
- Go Sugahara
- University of Southern California, Keck School of Medicine, Department of Medicine, Division of Gastrointestinal and Liver Diseases, Los Angeles, California, USA.,Research and Development Department, PhoenixBio, Co., Ltd, Kagamiyama, Higashi-Hiroshima, Hiroshima, Japan
| | - Yuji Ishida
- University of Southern California, Keck School of Medicine, Department of Medicine, Division of Gastrointestinal and Liver Diseases, Los Angeles, California, USA.,Research and Development Department, PhoenixBio, Co., Ltd, Kagamiyama, Higashi-Hiroshima, Hiroshima, Japan
| | - Jae Jin Lee
- University of Southern California, Keck School of Medicine, Department of Molecular Microbiology & Immunology, Los Angeles, California, USA
| | - Meng Li
- University of Southern California, Norris Medical Library, Bioinformatics Service Program, Los Angeles, California, USA
| | - Yasuhito Tanaka
- Department of Gastroenterology and Hepatology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Kumamoto, Japan
| | - Hyungjin Eoh
- University of Southern California, Keck School of Medicine, Department of Molecular Microbiology & Immunology, Los Angeles, California, USA
| | - Yusuke Higuchi
- Department of Molecular Medicine, Beckman Research Institute of City of Hope, Duarte, California, USA
| | - Takeshi Saito
- University of Southern California, Keck School of Medicine, Department of Medicine, Division of Gastrointestinal and Liver Diseases, Los Angeles, California, USA.,USC Research Center for Liver Diseases, Los Angeles, California, USA.,Corresponding author: Takeshi Saito, M.D., Ph.D., Associate Professor of Medicine, Molecular Microbiology & Immunology, and Pathology, USC Research Center for Liver Diseases, Division of Gastrointestinal and Liver Diseases, Keck School of Medicine of USC, University of Southern California, 2011 Zonal Avenue, HMR 801A, Los Angeles, CA 90033-9141, Phone: +1-323-442-2260, Fax:+1-323-442-5425,
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Ji B, Xue Y, Xu Y, Liu S, Gough AH, Xie XQ, Wang J. Drug-Drug Interaction Between Oxycodone and Diazepam by a Combined in Silico Pharmacokinetic and Pharmacodynamic Modeling Approach. ACS Chem Neurosci 2021; 12:1777-1790. [PMID: 33950681 PMCID: PMC8374491 DOI: 10.1021/acschemneuro.0c00810] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Opioids and benzodiazepines have complex drug-drug interactions (DDIs), which serve as an important source of adverse drug effects. In this work, we predicted the DDI between oxycodone (OXY) and diazepam (DZP) in the human body by applying in silico pharmacokinetic (PK) and pharmacodynamic (PD) modeling and simulation. First, we studied the PK interaction between OXY and DZP with a physiologically based pharmacokinetic (PBPK) model. Second, we applied molecular modeling techniques including molecular docking, molecular dynamics (MD) simulation, and the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) free energy method to predict the PD-DDI between these two drugs. The PK interaction between OXY and DZP predicted by the PBPK model was not obvious. No significant interaction was observed between the two drugs at normal doses, though very high doses of DZP demonstrated a non-negligible inhibitory effect on OXY metabolism. On the contrary, the molecular modeling study shows that DZP has potential to compete with OXY at the same binding pocket of the active μ-opioid receptor (MOR) and κ-opioid receptor (KOR). MD simulation and MM-PBSA calculation results demonstrated that there is likely a synergetic effect between OXY and DZP binding to opioid receptors, as OXY is likely to target the active MOR while DZP selectively binds to the active KOR. Thus, pharmacokinetics contributes slightly to the DDI between OXY and DZP although an overdose of DZP has been brought to attention. Pharmacodynamics is likely to play a more important role than pharmacokinetics in revealing the mechanism of DDI between OXY and DZP.
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Affiliation(s)
- Beihong Ji
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Ying Xue
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,Department of Pharmacy and Therapeutics, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261
| | - Yuanyuan Xu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Shuhan Liu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Albert H Gough
- Computational and Systems Biology, The University of Pittsburgh, Drug Discovery Institute, 800 Murdoch Building, 3420 Forbes Avenue, Pittsburgh, Pennsylvania, 15260, USA
| | - Xiang Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,To whom correspondence should be addressed: Xiang-Qun Xie: Corresponding author, , School of Pharmacy, University of Pittsburgh; Junmei Wang: Corresponding author, , School of Pharmacy, University of Pittsburgh
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, The University of Pittsburgh, 3501 Terrace St, Pittsburgh, PA 15261,NIH National Center of Excellence for Computational Drug Abuse Research, The University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA.,To whom correspondence should be addressed: Xiang-Qun Xie: Corresponding author, , School of Pharmacy, University of Pittsburgh; Junmei Wang: Corresponding author, , School of Pharmacy, University of Pittsburgh
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Patel R, Barker J, ElShaer A. Pharmaceutical Excipients and Drug Metabolism: A Mini-Review. Int J Mol Sci 2020; 21:E8224. [PMID: 33153099 PMCID: PMC7662502 DOI: 10.3390/ijms21218224] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 10/19/2020] [Accepted: 10/20/2020] [Indexed: 12/17/2022] Open
Abstract
Conclusions from previously reported articles have revealed that many commonly used pharmaceutical excipients, known to be pharmacologically inert, show effects on drug transporters and/or metabolic enzymes. Thus, the pharmacokinetics (absorption, distribution, metabolism and elimination) of active pharmaceutical ingredients are possibly altered because of their transport and metabolism modulation from the incorporated excipients. The aim of this review is to present studies on the interaction of various commonly-used excipients on pre-systemic metabolism by CYP450 enzymes. Excipients such as surfactants, polymers, fatty acids and solvents are discussed. Based on all the reported outcomes, the most potent inhibitors were found to be surfactants and the least effective were organic solvents. However, there are many factors that can influence the inhibition of CYP450, for instance type of excipient, concentration of excipient, type of CYP450 isoenzyme, incubation condition, etc. Such evidence will be very useful in dosage form design, so that the right formulation can be designed to maximize drug bioavailability, especially for poorly bioavailable drugs.
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Affiliation(s)
| | | | - Amr ElShaer
- Drug Discovery, Delivery and Patient Care (DDDPC), School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, Surrey KT1 2EE, UK; (R.P.); (J.B.)
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Ji B, Liu S, Xue Y, He X, Man VH, Xie XQ, Wang J. Prediction of Drug-Drug Interactions Between Opioids and Overdosed Benzodiazepines Using Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation. Drugs R D 2020; 19:297-305. [PMID: 31482303 PMCID: PMC6738369 DOI: 10.1007/s40268-019-00282-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Background Researchers have long been interested in the potential drug–drug interactions (DDIs) between opioids and benzodiazepines. However, much remains unknown concerning the interactions between these two drug classes. The objective of this work is to study the mechanism underlying the DDIs between opioids and benzodiazepines from the perspective of their pharmacokinetic (PK) interactions. A PK interaction occurs when two drugs are metabolized by the same cytochrome P450 enzymes and is one of the most common reasons for DDIs. Methods We quantitatively predicted the DDIs between three opioids (fentanyl, oxycodone and buprenorphine) and four benzodiazepines (alprazolam, diazepam, midazolam and triazolam) using a physiologically based pharmacokinetic (PBPK) modeling approach. A set of PBPK models was first constructed for these common opioids and benzodiazepines using SimCYP software, and the DDIs between them were then explored at various dosages. Results Our simulation results suggested there were no PK interactions between normal doses of opioids and benzodiazepines; but weak interactions can be expected with the combination of opioids and overdosed benzodiazepines. Particular attention should be given to the combination of fentanyl and overdosed alprazolam since a PK interaction can be observed between them. Conclusion Our results appear to indicate that pharmacodynamics may play a more important role than PKs in causing DDIs between opioids and benzodiazepines. This study also demonstrated that molecular modeling can be a very useful tool to mitigate the problem of “missing metabolic reaction parameters” in PK modeling and simulation. Electronic supplementary material The online version of this article (10.1007/s40268-019-00282-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Beihong Ji
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
| | - Shuhan Liu
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
| | - Ying Xue
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
| | - Xibing He
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
| | - Viet Hoang Man
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
| | - Xiang-Qun Xie
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
| | - Junmei Wang
- Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA 15261 USA
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Yamada M, Inoue SI, Sugiyama D, Nishiya Y, Ishizuka T, Watanabe A, Watanabe K, Yamashita S, Watanabe N. Critical Impact of Drug-Drug Interactions via Intestinal CYP3A in the Risk Assessment of Weak Perpetrators Using Physiologically Based Pharmacokinetic Models. Drug Metab Dispos 2020; 48:288-296. [PMID: 31996361 DOI: 10.1124/dmd.119.089599] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Accepted: 01/18/2020] [Indexed: 12/11/2022] Open
Abstract
A great deal of effort has been being made to improve the accuracy of the prediction of drug-drug interactions (DDIs). In this study, we addressed CYP3A-mediated weak DDIs, in which a relatively high false prediction rate was pointed out. We selected 17 orally administered drugs that have been reported to alter area under the curve (AUC) of midazolam, a typical CYP3A substrate, 0.84-1.47 times. For weak CYP3A perpetrators, the predicted AUC ratio mainly depends on intestinal DDIs rather than hepatic DDIs because the drug concentration in the enterocytes is higher. Thus, DDI prediction using simulated concentration-time profiles in each segment of the digestive tract was made by physiologically based pharmacokinetic (PBPK) modeling software GastroPlus. Although mechanistic static models tend to overestimate the risk to ensure the safety of patients, some underestimation is reported about PBPK modeling. Our in vitro studies revealed that 16 out of 17 tested drugs exhibited time-dependent inhibition (TDI) of CYP3A, and the subsequent DDI simulation that ignored these TDIs provided false-negative results. This is considered to be the cause of past underestimation. Inclusion of the DDI parameters of all the known DDI mechanisms, reversible inhibition, TDI, and induction, which have opposite effects on midazolam AUC, to PBPK model was successful in improving predictability of the DDI without increasing false-negative prediction as trade-off. This comprehensive model-based analysis suggests the importance of the intestine in assessing weak DDIs via CYP3A and the usefulness of PBPK in predicting intestinal DDIs. SIGNIFICANCE STATEMENT: Although drug-drug interaction (DDI) prediction has been extensively performed previously, the accuracy of prediction for weak interactions via CYP3A has not been thoroughly investigated. In this study, we simulate DDIs considering drug concentration-time profile in the enterocytes and discuss the importance and the predictability of intestinal DDIs about weak CYP3A perpetrators.
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Affiliation(s)
- Makiko Yamada
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Shin-Ichi Inoue
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Daisuke Sugiyama
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Yumi Nishiya
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Tomoko Ishizuka
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Akiko Watanabe
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Kengo Watanabe
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Shinji Yamashita
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
| | - Nobuaki Watanabe
- Drug Metabolism and Pharmacokinetics Research Laboratories, Daiichi Sankyo Co., Ltd., Tokyo, Japan (M.Y., S.I., D.S., Y.N., T.I., A.W., K.W., N.W.) and Faculty of Pharmaceutical Sciences, Setsunan University, Osaka, Japan (S.Y.)
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van Beusekom CD, van den Heuvel JJ, Koenderink JB, Russel FG, Schrickx JA. Feline hepatic biotransformation of diazepam: Differences between cats and dogs. Res Vet Sci 2015; 103:119-25. [DOI: 10.1016/j.rvsc.2015.09.016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Revised: 07/14/2015] [Accepted: 09/21/2015] [Indexed: 01/31/2023]
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Peng Y, Wu H, Zhang X, Zhang F, Qi H, Zhong Y, Wang Y, Sang H, Wang G, Sun J. A comprehensive assay for nine major cytochrome P450 enzymes activities with 16 probe reactions on human liver microsomes by a single LC/MS/MS run to support reliablein vitroinhibitory drug–drug interaction evaluation. Xenobiotica 2015; 45:961-77. [DOI: 10.3109/00498254.2015.1036954] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Aasa J, Hu Y, Eklund G, Lindgren A, Baranczewski P, Malmquist J, Turek D, Bueters T. Effect of Solvents on the Time-Dependent Inhibition of CYP3A4 and the Biotransformation of AZD3839 in Human Liver Microsomes and Hepatocytes. Drug Metab Dispos 2012; 41:159-69. [DOI: 10.1124/dmd.112.047597] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Zimmerlin A, Trunzer M, Faller B. CYP3A Time-Dependent Inhibition Risk Assessment Validated with 400 Reference Drugs. Drug Metab Dispos 2011; 39:1039-46. [DOI: 10.1124/dmd.110.037911] [Citation(s) in RCA: 69] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Kumar S, Earla R, Jin M, Mitra AK, Kumar A. Effect of ethanol on spectral binding, inhibition, and activity of CYP3A4 with an antiretroviral drug nelfinavir. Biochem Biophys Res Commun 2010; 402:163-7. [PMID: 20937259 DOI: 10.1016/j.bbrc.2010.10.014] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2010] [Accepted: 10/02/2010] [Indexed: 11/25/2022]
Abstract
Cytochrome P450 3A4 (CYP3A4) is the most abundant CYP enzyme in the liver and metabolizes approximately 50% of the drugs, including antiretrovirals. Although CYP3A4 induction by ethanol and impact of CYP3A4 on drug metabolism and toxicity is known, CYP3A4-ethanol physical interaction and its impact on drug binding, inhibition, or metabolism is not known. Therefore, we studied the effect of ethanol on binding and inhibition of CYP3A4 with a representative protease inhibitor, nelfinavir, followed by the effect of alcohol on nelfinavir metabolism. Our initial results showed that methanol, ethanol, isopropanol, isobutanol, and isoamyl alcohol bind in the active site of CYP3A4 and exhibit type I spectra. Among these alcohol compounds, ethanol showed the lowest K(D) (5.9±0.34mM), suggesting its strong binding affinity with CYP3A4. Ethanol (20mM) decreased the K(D) of nelfinavir by >5-fold (0.041±0.007 vs. 0.227±0.038μM). Similarly, 20mM ethanol decreased the IC(50) of nelfinavir by >3-fold (2.6±0.5 vs. 8.3±3.1μM). These results suggest that ethanol facilitates binding of nelfinavir with CYP3A4. Furthermore, we performed nelfinavir metabolism using LCMS. Although ethanol did not alter k(cat), it decreased the K(m) of nelfinavir, suggesting a decrease in catalytic efficiency (k(cat)/K(m)). This is an important finding because alcoholism is prevalent in HIV-1-infected persons and alcohol is shown to decrease the response to antiretroviral therapy.
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Affiliation(s)
- Santosh Kumar
- School of Pharmacy, University of Missouri-Kansas City, 2464 Charlotte Ave., Kansas City, MO 64108, USA.
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