Pathway-Dependent Inhibition Of Paclitaxel Hydroxylation By Kinase Inhibitiors And Assessment Of Drug-Drug Interaction Potentials

Objective: Paclitaxel is often used in combination with small molecule kinase inhibitors to enhance antitumor efficacy against various malignancies. However, most of the kinase inhibitors have inhibitory effect on P450 enzymes. In this paper, inhibitory potency of a total of 12 kinase inhibitors against CYP2C8- and CYP3A4-mediated paclitaxel hydroxylation were examined in HLMs. Moreover, the pathway-dependent inhibition of paclitaxel hydroxylation by kinase inhibitors was characterized. Molecular docking simulation and spectral analysis were applied to simulate bindings of inhibitors and P450 enzymes. In addition, prediction of drug-drug interactions was explored using static mathematical models.Methods: A liquid chromatography-tandem mass spectrometry(LC-MS/MS) method was developed for the simultaneous determination of 6α-hydroxypaclitaxel and p-3’-hydroxypaclitaxel in human liver microsomes. The incubation system of paclitaxel metabolism in HLMs was first optimized. Evaluation of the inhibitory potency of kinase inhibitors by monitoring the formation of 6α-hydroxypaclitaxel and p-3’-hydroxypaclitaxel simultaneously, and inhibition potency(Ki) for each metabolic pathway by kinase inhibitors in the reversible inhibition and inactivation parameters(KI and kinact) of CYP3A4 by axitinib were obtained. After incubating axitinib with GSH and NADPH-supplemented HLMs, an axitinib-glutathione adduct was identified using an ACQUITY ultra-performance liquid chromatograph system coupled with a quadruple time-of-flight mass spectrometer with an electrospray ionization source. Molecular docking simulations were performed to examine inhibitor-enzyme binding, and to characterize the binding types between kinase inhibitors and P450 enzymes. Spectral analysis was performed using a UV-visible spectrophotometer. The potential of drug-drug interactions between paclitaxel and kinase inhibitors was examined by predicting AUC changes using mathematical models.Results: Judging from the Ki values, the studied kinase inhibitors displayed a wide range of inhibitory potency, among which nilotinib was the most potent inhibitor against both CYP2C8(Ki = 0.10 μM) and CYP3A4(Ki = 0.28 μM). CYP2C8-mediated paclitaxel hydroxylation was more sensitive to inhibition by axitinib, lapatinib, nilotinib, and sorafenib, whereas CYP3A4-mediated paclitaxel hydroxylation was preferentially inhibited by bosutinib, dasatinib, erlotinib, pazopanib, and sunitinib. Afatinib, gefitinib, and imatinib displayed similar inhibitory potency against these two separate pathways. Moreover, afatinib, erlotinib, gefitinib, lapatinib, and sorafenib showed a modest time-dependent inhibition of CYP2C8-mediated paclitaxel hydroxylation. In contrast, most of the selected kinase inhibitors(except sorafenib) showed strong time-dependent inhibition against CYP3A4-mediated paclitaxel metabolism. The inactivation of CYP3A4 by axitinib displayed characteristic time and concentration dependency. Kinetic analysis revealed that axitinib exhibited a KI of 0.93 μM and kinact of 0.0137 min-1 against CYP3A4-mediated paclitaxel hydroxylation. After incubating axitinib with GSH, an axitinib-glutathione adduct was detected in the presence of NADPH. Nilotinib exhibited much higher binding affinities than sunitinib in both CYP3A4 and CYP2C8 system by forming hydrogen bonds and intermolecular forces. It is of note that the docking scores for CYP3A4 exhibited a moderate correlation with experimental data(r2 = 0.64), but the docking scores of CYP2C8 showed a relatively lower linear correlation(r2 = 0.51). For most of these type II binders, strong inhibition was observed, with a few exceptions such as afatinib for CYP2C8. Interestingly, the strong CYP2C8 inhibitor bosutinib did not show the type II binding spectrum. Comparison of available Ks and Ki values reveals a good correlation for both CYP3A4 and CYP2C8. Prediction of drug-drug interactions using mathemathical models revealed that ignoring the EH is linked to overprediction for several kinase inhibitors. Furthermore, overprediction is also noted when the time-dependent inhibition component of CYP3A4 is incorporated, which is in turn affected by the fm,3A4 of paclitaxel.Conclusion: In the present study, pathway-dependent inhibition(CYP2C8 versus CYP3A4) and time-dependent inhibition(CYP3A4) of paclitaxel metabolism by selected kinase inhibitors were observed. Molecular docking simulations revealed that potent inhibition of CYP2C8 and CYP3A4 by nilotinib can be explained by the strong binding between nilotinib and respective enzymes. In addition, the type II binding to underlying P450 enzymes was evident for the majority of kinase inhibitors. With the consideration of EH of the victim drug paclitaxel, a reasonably accurate prediction of drug-drug interactions between paclitaxel and kinase inhibitors is achieved. It can be anticipated that further investigation on drug interactions caused by enzyme inhibition will lead to safer and effective use of paclitaxel-based combination therapies for the treatment of various cancers in clinical.