Prediction of cytochrome P450 3A inhibition by verapamil enantiomers and their metabolites.
Prediction of cytochrome P450 3A inhibition by verapamil enantiomers and their metabolites.
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DOI：
10.1124/dmd.32.2.259
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发表时间：
2004-02
期刊：
影响因子：
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通讯作者：
Ying-hong Wang;David R. Jones;S. Hall
中科院分区：
文献类型：
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作者：
Ying-hong Wang;David R. Jones;S. Hall
维拉帕米对CYP3A活性的抑制导致许多药物与CYP3A底物的相互作用，但其抑制机制尚不清楚。本研究表明维拉帕米对映体及其主要代谢物[诺维拉帕米和n-脱盐维拉帕米（D617）]通过混合的人肝微粒体和cdna表达的CYP3A4 (+b5)，以时间和浓度依赖性的方式抑制CYP3A。用cdna表达的CYP3A4 （+b5）获得的失活动力学参数kinact和KI值分别为：r -维拉帕米0.39 min（-1）和6.46 microM， s -维拉帕米0.64 min（-1）和2.97 microM,(+/-)-诺维拉帕米1.12 min（-1）和5.89 microM, D617 0.07 min（-1）和7.93 microM。根据kinact与KI的比值，维拉帕米对映体及其代谢产物的失活效力依次为：S-norverapamil>S-verapamil>R-norverapamil>R-verapamil>D617。通过双光束分光光度法，我们证实了与CYP3A形成代谢中间复合物是所有化合物失活的机制。s -维拉帕米的体外未结合分数为0.84，r -维拉帕米为0.68,(+/-)-诺维拉帕米为0.84。基于机制的药代动力学模型预测，反复口服维拉帕米后，被肝脏CYP3A完全消除（fm=1）的CYP3A底物的口服曲线下面积（AUC）增加1.6- 2.2倍。对于咪达唑仑（fm=0.9），一种经历广泛肠壁代谢的药物，预计口服AUC增加3.2- 4.5倍。预测结果与体内药物相互作用数据具有良好的相关性，表明该模型适用于预测基于机制的抑制剂的药物相互作用。
Verapamil inhibition of CYP3A activity results in many drug-drug interactions with CYP3A substrates, but the mechanism of inhibition is unclear. The present study showed that verapamil enantiomers and their major metabolites [norverapamil and N-desalkylverapamil (D617)] inhibited CYP3A in a time- and concentration-dependent manner by using pooled human liver microsomes and the cDNA-expressed CYP3A4 (+b5). The values of the inactivation kinetic parameters kinact and KI obtained with the cDNA-expressed CYP3A4 (+b5) were 0.39 min(-1) and 6.46 microM for R-verapamil, 0.64 min(-1) and 2.97 microM for S-verapamil, 1.12 min(-1) and 5.89 microM for (+/-)-norverapamil, and 0.07 min(-1) and 7.93 microM for D617. Based on the ratio of kinact and KI, the inactivation potency of verapamil enantiomers and their metabolites was in the following order: S-norverapamil>S-verapamil>R-norverapamil>R-verapamil>D617. Using dual beam spectrophotometry, we confirmed that metabolic intermediate complex formation with CYP3A was the mechanism of inactivation for all compounds. The in vitro unbound fraction was 0.84 for S-verapamil, 0.68 for R-verapamil, and 0.84 for (+/-)-norverapamil. A mechanism-based pharmacokinetic model predicted that the oral area under the curve (AUC) of a CYP3A substrate that is eliminated completely (fm=1) by the hepatic CYP3A increased 1.6- to 2.2-fold after repeated oral administration of verapamil. For midazolam (fm=0.9), a drug that undergoes extensive intestinal wall metabolism, the predicted increase in oral AUC was 3.2- to 4.5-fold. The predicted results correlate well with the in vivo drug interaction data, suggesting that the model is suitable for predicting drug interactions by mechanism-based inhibitors.