scholarly journals In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9

2016 ◽  
Vol 17 (6) ◽  
pp. 914 ◽  
Author(s):  
Serena Nembri ◽  
Francesca Grisoni ◽  
Viviana Consonni ◽  
Roberto Todeschini
Keyword(s):  
Cytochrome P450 ◽  
Drug Interaction ◽  
In Silico ◽  
In Silico Prediction

In Silico Prediction of Cytochrome P450-Mediated Site of Metabolism (SOM)

2013 ◽  
Vol 20 (3) ◽  
pp. 279-289
Author(s):  
Xian Liu ◽  
Qiancheng Shen ◽  
Jing Li ◽  
Shanshan Li ◽  
Cheng Luo ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
In Silico ◽  
In Silico Prediction

scholarly journals In vitro and in silico Approaches to Study Cytochrome P450-Mediated Interactions

2017 ◽  
Vol 20 (1) ◽  
pp. 319 ◽  
Author(s):  
Boon Hooi Tan ◽  
Yan Pan ◽  
Amelia Nathania Dong ◽  
Chin Eng Ong
Keyword(s):  
Cytochrome P450 ◽  
Drug Interaction ◽  
Drug Metabolism ◽  
In Silico ◽  
High Throughput Screening ◽  
Rational Design ◽  
Pharmacokinetic Variability ◽  
Drug Drug Interaction ◽  
In Silico Methods

In vitro and in silico models of drug metabolism are utilized regularly in the drug research and development as tools for assessing pharmacokinetic variability and drug-drug interaction risk. The use of in vitro and in silico predictive approaches offers advantages including guiding rational design of clinical drug-drug interaction studies, minimization of human risk in the clinical trials, as well as cost and time savings due to lesser attrition during compound development process. This article gives a review of some of the current in vitro and in silico methods used to characterize cytochrome P450(CYP)-mediated drug metabolism for estimating pharmacokinetic variability and the magnitude of drug-drug interactions. Examples demonstrating the predictive applicability of specific in vitro and in silico approaches are described. Commonly encountered confounding factors and sources of bias and error in these approaches are presented. With the advent of technological advancement in high throughput screening and computer power, the in vitro and in silico methods are becoming more efficient and reliable and will continue to contribute to the process of drug discovery, development and ultimately safer and more effective pharmacotherapy. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.

Identification and in silico prediction of metabolites of tebufenozide derivatives by major human cytochrome P450 isoforms

2020 ◽  
Vol 28 (9) ◽  
pp. 115429
Author(s):  
Hiroaki Edamatsu ◽  
Masataka Yagawa ◽  
Shinichi Ikushiro ◽  
Toshiyuki Sakaki ◽  
Yoshiaki Nakagawa ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
In Silico ◽  
In Silico Prediction ◽  
Human Cytochrome ◽  
Cytochrome P450 Isoforms

In Silico Prediction of Cytochrome P450-Mediated Drug Metabolism

2011 ◽  
Vol 14 (5) ◽  
pp. 388-395 ◽  
Author(s):  
Tao Zhang ◽  
Qi Chen ◽  
Li Li ◽  
Limin Angela Liu ◽  
Dong-Qing Wei
Keyword(s):  
Cytochrome P450 ◽  
Drug Metabolism ◽  
In Silico ◽  
In Silico Prediction

scholarly journals Multidrug Resistance Reversal Effects of Aminated Thioxanthones and Interaction with Cytochrome P450 3A4

2011 ◽  
Vol 15 (1) ◽  
pp. 31 ◽  
Author(s):  
Andreia Palmeira ◽  
Maria Emília Sousa ◽  
Miguel X Fernandes ◽  
Madalena M. Pinto ◽  
M. Helena Vasconcelos
Keyword(s):  
Cytochrome P450 ◽  
Multidrug Resistance ◽  
In Silico ◽  
Mammalian Cells ◽  
Leukemia Cell ◽  
Membrane Vesicles ◽  
Cytochrome P450 3A4 ◽  
Cancer Resistance ◽  
In Silico Prediction

Purpose. Aminated thioxanthones have recently been described as dual-acting agents: growth inhibitors of leukemia cell lines and P-glycoprotein (P-gp) inhibitors. To evaluate the selectivity profile of thioxanthones as inhibitors of multidrug resistance (MDR), their interaction with other ABC transporters, which were found to have a strong correlation with multidrug resistance, such as multidrug resistant proteins 1 (MRP1), 2 (MRP2) and 3 (MRP3) and breast cancer resistance protein (BCRP) was also evaluated. The interaction of thioxanthones with cytochrome P450 3A4 (CYP3A4) together with the prediction of their binding conformations and metabolism sites was also investigated. Methods. The UIC2 monoclonal antibody-labelling assay was performed using P-gp overexpressing leukemia cells, K562Dox, incubated with eight thioxanthonic derivatives, in order to confirm their P-gp inhibitory activity. A colorimetric-based ATPase assay using membrane vesicles from mammalian cells overexpressing a selected human ABC transporter protein (P-gp, MRP1, MRP2, MRP3, or BCRP) was performed. To verify if some of the thioxanthonic derivatives were substrates or inhibitors of CYP3A4, a luciferin-based luminescence assay was performed. Finally, the in silico prediction of the most probable metabolism sites and docking studies of thioxanthones on CYP3A4 binding site were investigated. Results. Thioxanthones interacted not only with P-gp but also with MRP and BCRP transporters. These compounds also interfere with CYP3A4 activity in vitro, in accordance with the in silico prediction. Conclusion. Thioxanthonic derivatives are multi-target compounds. A better characterization of the interactions of these compounds with classical resistance mechanisms may possibly identify improved treatment applications. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.

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