Mass Spectrometry-Based Quantitative Proteomics for Drug-Metabolizing Enzymes

Abstract

Quantification of highly homologous human liver drug-metabolizing enzymes (DMEs) has been a challenging task in drug metabolism and disposition research, due to a lack of specific antibodies and marker substrates. Mass spectrometry (MS) techniques and applications have evolved significantly, striving to achieve absolute and specific quantification of these enzymes. Since the first absolute quantification of cytochrome P450s (CYPs) using the attachment of isotope tags to free thiols (iCAT), MS-based quantification has become much more versatile, cheaper, and easier to use. Today, variations of liquid chromatography-multiple reaction monitoring (LC-MRM)-based targeted proteomics, such as AQUA (absolute quantification) and QconCAT (concatenated signature peptides), have become the gold standards for quantification. These new methods have driven the absolute quantification of DMEs to become a routine laboratory task. Many drug metabolism-related projects require absolute enzyme quantification. For example, precise knowledge of enzyme expression during ontogeny is a necessity to aid pharmacists in planning drug-dosing regimens for patients of different age groups. Additional examples include the need for accurate cellular enzyme expression profiles when establishing new drug-screening cell models and when elucidating molecular mechanisms underlying hypothesized drug-drug interactions. This dissertation demonstrates how an LC-MRM targeted approach contributes to these three areas. First, an ultra-performance liquid chromatography (UPLC)-MRM targeted quantification method was developed and validated, focusing specifically on the quantification of CYP2C and flavin-containing monoxoygenase (FMO) isoforms. Second, the newly developed, as well as existing, UPLC-MRM quantification methods were used to confirm previously reported DME ontogeny patterns and establish patterns for CYP4F and FMO5. Third, targeted proteomic quantification was employed for the absolute quantification of CYPs 1A1, 1A2 and 1B1 in KLE cells and different human tissue microsomes to aid the establishment of CYP1B1-dependent cell models for the screening of anticancer prodrugs. Lastly, CYP4F2-specific targeted quantification was used to confirm the mechanism underlying a potential drug-drug interaction between warfarin and lovastatin. UPLC-MRM-based targeted proteomic techniques have many advantages, but the cost and time required for method development rises linearly with an increase in the number of targeted proteins. An emerging technique utilizing label-free data independent analysis (DIA) with high-resolution mass spectrometry (HDMS) offers the global quantification of hundreds of proteins at a negligible cost; however, there are numerous hurdles when using this technique. We introduced a new sample processing method, quantitative filter-assisted sample preparation (qFASP), which allows full recovery and analysis of clean, digested proteomic peptides. With qFASP and additional optimized procedures, many of the hurdles encountered with DIA quantification were mitigated. Very strong quantitative correlations were observed between the new DIA/ HDMS technique and the well-established targeted proteomics for DME quantification. In summary, this dissertation describes a targeted and an untargeted (DIA) quantitative proteomic method for the multiplexed absolute quantification of human hepatic DMEs and their applications to developmental pharmacology. Quantification coherence achieved between the targeted and the untargeted proteomic methods was made possible by a newly developed qFASP sample preparation protocol, which allowed quantitative and reproducible recovery of peptides after filter-assisted sample cleanup and protein digestion. These methods are expected to enrich our knowledge regarding ontogenetic changes of human DMEs and establish necessary quantitative information to construct predictive physiologically-based pharmacokinetic models.