Time-dependent inactivation of CYP3A4
To investigate the time-dependent inactivation of CYP3A4 by sunitinib,
seven gradient concentrations (0–5 μM) and six time points (0–20 min)
were used. The data were then fitted to a linear regression model, which
reflected the linear relation between ‘ln remaining activity’ and
‘inactivation concentration’ (I ). The negative slope of this
linear relationship reflected the observed inactivation rates
(Kobs) value, which could be plotted against I to
allow the fitting of inactivation kinetic parametersK I and K inact to the
nonlinear least-squares regression based on Eq. 1. using Prism v.6.0
(GraphPad, San Diego, CA, USA).
Molecular
docking simulations
The CYP2J2 crystal structure homology model from the Clustal Omega
webserver (https://www.ebi.ac.uk/Tools/msa/clustalo/) was used to
conduct docking simulations between TKIs and rivaroxaban in SYBYL
(X-1.1) (Ning et al., 2019). The crystal structure of CYP3A4 (PDB: 4D7D)
was from the crystal structures that bound to a known inhibitor. The 3D
structures of the TKIs were subjected to energy minimisation using the
default Tripos force field parameters, and the Gasteiger-Hückel charges
were calculated for each compound. The Surflex-Dock mode was used to
generate binding conformations of TKIs with CYP2J2. The optimal
conformations were determined by their empirical functions ChemScore.
The PyMOL Molecular Graphics System v.16.1.0.15350 (DeLano Scientific
LLC) was used to visualise the docking results.
Quantitative prediction of DDI
risk
Kinetic constants were included in the mechanistic static model to
explore reversible inhibition and time-dependent inactivation. This
static model was previously developed and refined by Fahmi et al.
(Fahmi, Maurer, Kish, Cardenas, Boldt & Nettleton, 2008) and
Isoherranen et al. (Isoherranen, Lutz, Chung, Hachad, Levy &
Ragueneau-Majlessi, 2012) to account for the inhibition of multiple P450
isoforms. In the present study, this model was designed to explore the
contributions of enzyme inhibition in the prediction of DDI risk. The
area under the curve ratio (AUC Ratio/AUCR) in the
presence of a pharmacokinetic DDI was used as the index, as described by
Eq. 2.
Here, A is the time-dependent inactivation of each P450 isoform that was
observed in the liver, as described by Eq. 3.
Here, B is the reversible inhibition of each P450 isoform that was
observed in the liver, as described by Eq. 4. The degradation rates
(Kdeg) of CYP2J2 and CYP3A4 were 0.00026 and 0.00032
min–1, respectively (Cheong et al., 2017), where I
represented the in vivo concentration of inhibitors in healthy and solid
tumour patients. Additionally, the fraction of rivaroxaban metabolised
by CYP2J2 or CYP3A4 was input from our previous study (Zhao et al.,
2021), which were 0.95 for CYP2J2 and 0.025 for CYP3A4.