Human Cytochromes P450 and Their Role in Metabolism-Based Drug-Drug Interactions

2001 ◽  
pp. 86-119 ◽  
2016 ◽  
Vol 17 (7) ◽  
pp. 681-691 ◽  
Author(s):  
Ruirui Yang ◽  
Zhiqiang Luo ◽  
Yang Liu ◽  
Mohan Sun ◽  
Ling Zheng ◽  
...  

Pharmaceutics ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 538
Author(s):  
Alexander V. Dmitriev ◽  
Anastassia V. Rudik ◽  
Dmitry A. Karasev ◽  
Pavel V. Pogodin ◽  
Alexey A. Lagunin ◽  
...  

Drug–drug interactions (DDIs) can cause drug toxicities, reduced pharmacological effects, and adverse drug reactions. Studies aiming to determine the possible DDIs for an investigational drug are part of the drug discovery and development process and include an assessment of the DDIs potential mediated by inhibition or induction of the most important drug-metabolizing cytochrome P450 isoforms. Our study was dedicated to creating a computer model for prediction of the DDIs mediated by the seven most important P450 cytochromes: CYP1A2, CYP2B6, CYP2C19, CYP2C8, CYP2C9, CYP2D6, and CYP3A4. For the creation of structure–activity relationship (SAR) models that predict metabolism-mediated DDIs for pairs of molecules, we applied the Prediction of Activity Spectra for Substances (PASS) software and Pairs of Substances Multilevel Neighborhoods of Atoms (PoSMNA) descriptors calculated based on structural formulas. About 2500 records on DDIs mediated by these cytochromes were used as a training set. Prediction can be carried out both for known drugs and for new, not-yet-synthesized substances. The average accuracy of the prediction of DDIs mediated by various isoforms of cytochrome P450 estimated by leave-one-out cross-validation (LOO CV) procedures was about 0.92. The SAR models created are publicly available as a web resource and provide predictions of DDIs mediated by the most important cytochromes P450.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Marta Vázquez ◽  
Natalia Guevara ◽  
Cecilia Maldonado ◽  
Paulo Cáceres Guido ◽  
Paula Schaiquevich

Choosing an appropriate treatment for chronic pain remains problematic, and despite the available medication for its treatment, still, many patients complain about pain and appeal to the use of cannabis derivatives for pain control. However, few data have been provided to clinicians about the pharmacokinetic drug-drug interactions of cannabinoids with other concomitant administered medications. Therefore, the aim of this brief review is to assess the interactions between cannabinoids and pain medication through drug transporters (ATP-binding cassette superfamily members) and/or metabolizing enzymes (cytochromes P450 and glucuronyl transferases).


Blood ◽  
2011 ◽  
Vol 117 (8) ◽  
pp. e75-e87 ◽  
Author(s):  
Amina Haouala ◽  
Nicolas Widmer ◽  
Michel A. Duchosal ◽  
Michael Montemurro ◽  
Thierry Buclin ◽  
...  

Abstract Several cancer treatments are shifting from traditional, time-limited, nonspecific cytotoxic chemotherapy cycles to continuous oral treatment with specific protein-targeted therapies. In this line, imatinib mesylate, a selective tyrosine kinases inhibitor (TKI), has excellent efficacy in the treatment of chronic myeloid leukemia. It has opened the way to the development of additional TKIs against chronic myeloid leukemia, including nilotinib and dasatinib. TKIs are prescribed for prolonged periods, often in patients with comorbidities. Therefore, they are regularly co-administered along with treatments at risk of drug-drug interactions. This aspect has been partially addressed so far, calling for a comprehensive review of the published data. We review here the available evidence and pharmacologic mechanisms of interactions between imatinib, dasatinib, and nilotinib and widely prescribed co-medications, including known inhibitors or inducers of cytochromes P450 or drug transporters. Information is mostly available for imatinib mesylate, well introduced in clinical practice. Several pharmacokinetic aspects yet remain insufficiently investigated for these drugs. Regular updates will be mandatory and so is the prospective reporting of unexpected clinical observations.


2006 ◽  
Vol 35 (2) ◽  
pp. 194-200 ◽  
Author(s):  
Xiaochao Ma ◽  
Yatrik Shah ◽  
Connie Cheung ◽  
Grace L. Guo ◽  
Lionel Feigenbaum ◽  
...  

2008 ◽  
Vol 153 (S1) ◽  
pp. S82-S89 ◽  
Author(s):  
J-D Maréchal ◽  
C A Kemp ◽  
G C K Roberts ◽  
M J I Paine ◽  
C R Wolf ◽  
...  

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