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Pharmaceuticals
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Cytochrome P450 Enzymes in Drug Metabolism
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Cytochrome P450 Enzymes in Drug Metabolism

A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Pharmacology".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 3923

Special Issue Editors

Prof. Dr. Anderson R. M. De Oliveira

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Guest Editor
Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-901, SP, Brazil
Interests: in vitro metabolism studies; enantiomers; pesticides; chiral drugs; drug–drug interaction
Prof. Dr. Natalia V. De Moraes

E-Mail Website
Guest Editor
Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL, USA
Interests: special populations; pharmacometrics; quantitative pharmacology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pharmacokinetics comprises the dynamic processes of absorption, distribution, metabolism, and excretion. In drug development, metabolism assays are essential to predict drug elimination and drug–drug interactions and to understand pharmacokinetic variability related to genetic polymorphisms. The comprehension of the metabolism of xenobiotics (drugs, toxicants, drugs of abuse) is essential in risk assessment to identify the metabolic pathways and enzymes, to estimate the exposure level in the body, to predict efficacy and safety outcomes, and ultimately to support decision-making related to both human and environmental health. The metabolism of xenobiotics can occur in successive steps with the participation of several enzymes classically divided into phase I and phase II metabolism. Phase I metabolism comprises oxidation, reduction, and hydrolysis reactions mediated primarily by cytochrome P450 (CYP450) enzymes. These enzymes are predominantly found in the smooth endoplasmic reticulum of hepatocytes, although they may also be present in other tissues, such as the lung, kidney, gastrointestinal tract, nasal mucosa, skin and brain. Variability in drug metabolism can be explained by genetic variation, diseases, age-related functions and extrinsic factors (diet, alcohol, drugs) resulting in drug-induced toxicity or even the failure in pharmacological treatment. This special collection aims to bring together several aspects related to the metabolism of xenobiotics by CYP450 enzymes from in vitro, in vivo and modeling and simulation studies. Determination of enzymatic parameters, inhibition and phenotyping studies, pharmacokinetics and pharmacometrics approaches, such as PBPK modeling, are welcome.

Prof. Dr. Anderson R. M. De Oliveira
Prof. Dr. Natalia V. De Moraes
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Pharmaceuticals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • in vitro metabolism
  • pharmacokinetics
  • drugs
  • pesticides
  • CYP450
  • drug-drug interactions
  • CYP450 inhibition
  • CYP biomarkers
  • CYP gene-drug interactions
  • PBPK modeling

Published Papers (2 papers)

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Research

15 pages, 3083 KiB  
Article
CYP2C19 Contributes to THP-1-Cell-Derived M2 Macrophage Polarization by Producing 11,12- and 14,15-Epoxyeicosatrienoic Acid, Agonists of the PPARγ Receptor
by Hee Young Cho, Sangzin Ahn, Yong-Soon Cho, Su-Kil Seo, Dong Hyun Kim, Jae-Gook Shin and Su-Jun Lee
Pharmaceuticals 2023, 16(4), 593; https://doi.org/10.3390/ph16040593 - 15 Apr 2023
Viewed by 1589
Abstract
Although the functional roles of M1 and M2 macrophages in the immune response and drug resistance are important, the expression and role of cytochrome P450s (CYPs) in these cells remain largely unknown. Differential expression of the 12 most common CYPs (CYP1A1, 1A2, 1B1, [...] Read more.
Although the functional roles of M1 and M2 macrophages in the immune response and drug resistance are important, the expression and role of cytochrome P450s (CYPs) in these cells remain largely unknown. Differential expression of the 12 most common CYPs (CYP1A1, 1A2, 1B1, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 2J2, 3A4, and 3A5) were screened in THP-1-cell-derived M1 and M2 macrophages using reverse transcription PCR. CYP2C19 was highly expressed in THP-1-cell-derived M2 macrophages, but it was negligibly expressed in THP-1-cell-derived M1 macrophages at the mRNA and protein levels as analyzed by reverse transcription quantitative PCR and Western blot, respectively. CYP2C19 enzyme activity was also very high in THP-1-cell-derived M2 compared to M1 macrophages (> 99%, p < 0.01), which was verified using inhibitors of CYP2C19 activity. Endogenous levels of the CYP2C19 metabolites 11,12-epoxyeicosatrienoic acid (11,12-EET) and 14,15-EET were reduced by 40% and 50% in cells treated with the CYP2C19 inhibitor and by 50% and 60% in the culture medium, respectively. Both 11,12-EET and 14,15-EET were identified as PPARγ agonists in an in vitro assay. When THP-1-cell-derived M2 cells were treated with CYP2C19 inhibitors, 11,12- and 14,15-EETs were significantly reduced, and in parallel with the reduction of these CYP2C19 metabolites, the expression of M2 cell marker genes was also significantly decreased (p < 0.01). Therefore, it was suggested that CYP2C19 may contribute to M2 cell polarization by producing PPARγ agonists. Further studies are needed to understand the endogenous role of CYP2C19 in M2 macrophages with respect to immunologic function and cell polarization. Full article
(This article belongs to the Special Issue Cytochrome P450 Enzymes in Drug Metabolism)
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15 pages, 778 KiB  
Article
Prospective Prediction of Dapaconazole Clinical Drug–Drug Interactions Using an In Vitro to In Vivo Extrapolation Equation and PBPK Modeling
by Natalícia de Jesus Antunes, Fernanda de Lima Moreira, Karin Kipper, Lewis Couchman, Daniel Temponi Lebre, Atholl Johnston and Gilberto De Nucci
Pharmaceuticals 2023, 16(1), 28; https://doi.org/10.3390/ph16010028 - 26 Dec 2022
Cited by 1 | Viewed by 1776
Abstract
This study predicted dapaconazole clinical drug–drug interactions (DDIs) over the main Cytochrome P450 (CYP) isoenzymes using static (in vitro to in vivo extrapolation equation, IVIVE) and dynamic (PBPK model) approaches. The in vitro inhibition of main CYP450 isoenzymes by dapaconazole in a human [...] Read more.
This study predicted dapaconazole clinical drug–drug interactions (DDIs) over the main Cytochrome P450 (CYP) isoenzymes using static (in vitro to in vivo extrapolation equation, IVIVE) and dynamic (PBPK model) approaches. The in vitro inhibition of main CYP450 isoenzymes by dapaconazole in a human liver microsome incubation medium was evaluated. A dapaconazole PBPK model (Simcyp version 20) in dogs was developed and qualified using observed data and was scaled up for humans. Static and dynamic models to predict DDIs following current FDA guidelines were applied. The in vitro dapaconazole inhibition was observed for all isoforms investigated, including CYP1A2 (IC50 of 3.68 µM), CYP2A6 (20.7 µM), 2C8 (104.1 µM), 2C9 (0.22 µM), 2C19 (0.05 µM), 2D6 (0.87 µM), and 3A4 (0.008–0.03 µM). The dynamic (PBPK) and static DDI mechanistic model-based analyses suggest that dapaconazole is a weak inhibitor (AUCR > 1.25 and <2) of CYP1A2 and CYP2C9, a moderate inhibitor (AUCR > 2 and <5) of CYP2C8 and CYP2D6, and a strong inhibitor (AUCR ≥ 5) of CYP2C19 and CYP3A, considering a clinical scenario. The results presented may be a useful guide for future in vivo and clinical dapaconazole studies. Full article
(This article belongs to the Special Issue Cytochrome P450 Enzymes in Drug Metabolism)
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