Computational predictions of the site of metabolism of cytochrome P450 2D6 substrates: comparative analysis, molecular docking, bioactivation and toxicological implications.

Abstract:

:Cytochrome P450 2D6 (CYP2D6) is a polymorphic enzyme responsible for metabolizing approximately 25% of all drugs. CYP2D6 is highly expressed in the brain and plays a role as the major CYP in the metabolism of numerous brain-penetrant drugs, including antipsychotics and antidepressants. CYP2D6 activity and inhibition have been associated with numerous undesirable effects in patients, such as bioactivation, drug-associated suicidality and prolongation of the QTc interval. Several in silico tools have been developed in recent years to assist safety assessment scientists in predicting the structural identity of CYP2D6-derived metabolites. The first goal of this study was to perform a comparative evaluation on the ability of four commonly used in silico tools (MetaSite, StarDrop, SMARTCyp and RS-WebPredictor) to correctly predict the CYP2D6-derived site of metabolism (SOM) for 141 compounds, including 10 derived from the Genentech small molecule library. The second goal was to evaluate if a bioactivation prediction model, based on an indicator of chemical reactivity (ELUMO-EHOMO) and electrostatic potential, could correctly predict five representative compounds known to be bioactivated by CYP2D6. Such a model would be of great utility in safety assessment since unforeseen toxicities of CYP2D6 substrates may in part be due to bioactivation mechanisms. The third and final goal was to investigate whether molecular docking, using the crystal structure of human CYP2D6, had the potential to compliment or improve the results obtained from the four SOM in silico programs.

journal_name

Drug Metab Rev

journal_title

Drug metabolism reviews

authors

Ford KA,Ryslik G,Sodhi J,Halladay J,Diaz D,Dambach D,Masuda M

doi

10.3109/03602532.2015.1047026

subject

Has Abstract

pub_date

2015-08-01 00:00:00

pages

291-319

issue

3

eissn

0360-2532

issn

1097-9883

journal_volume

47

pub_type

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