Application of Km and Vmax-Based Prediction Models to Assessing the Influence of CYP2C9 Polymorphisms on Pharmacokinetics
Ryoko TERADA *, Naruebet PHINYODULYACHET, Chioko NAGAO, Kenji MIZUGUCHI
Institute for Protein Research, Osaka University
CYP2C9 is one of the most well-known polymorphic enzymes, exhibiting the second-highest hepatic expression level among the cytochrome P450 (CYP) isoforms in humans. Genetic polymorphisms in CYP2C9 often result in reduced enzymatic activity toward specific substrates, thereby influencing drug metabolism rates and contributing to interindividual variability in drug efficacy and adverse effects. Thus, the ability to predict the impact of CYP2C9 polymorphisms on pharmacokinetics is important for both drug development and clinic practice.
Kusama et al. (2009) proposed a method to evaluate pharmacokinetic changes caused by CYP2C9 variants by calculating the oral clearance ratio between variant and wild-type enzymes using in vitro data. This calculation requires five parameters: Km, Vmax, enzyme expression level, the contribution of CYP2C9 to hepatic clearance in wild-type individuals (fm), and the contribution of the metabolic pathway to total drug clearance (fh). However, experimental data for Km, Vmax, fm, and fh are compound-specific, and such data—especially for variant alleles—are limited in public databases like ChEMBL. Alternatively, Tang et al. (2020) proposed a simplified approach that does not account for physiological factors in vivo. They evaluated the changes between variant and wild-type enzymes by comparing the ratio of intrinsic hepatic clearance (CLint), calculated solely from Km and Vmax values.
Our aim in the present study was to expand the applicability of Tang et al.’s approach of predicting changes in CLint in vitro, by incorporating Km and Vmax values not only from experimental measurements but also from computational predictions. As a preliminary phase, we made a comprehensive dataset of relevant parameters for evaluation purposes. This dataset was then used to reproduce previous studies and to investigate the applicability of the method to new compounds and rare CYP2C9 variants beyond the well-known *2 and *3 alleles.