Predicting intrinsic clearance for drugs and drug candidates metabolized by aldehyde oxidase

Large Computational Survey of Intrinsic Reactivity of Aromatic Carbon Atoms with Respect to a Model Aldehyde Oxidase

Aldehyde oxidase (AOX) and other related molybdenum-containing enzymes are known to oxidize the C-H bonds of aromatic rings. This process contributes to the metabolism of pharmaceutical compounds and, therefore, is of vital importance to drug pharmacokinetics. The present work describes an automated computational workflow and its use for the prediction of intrinsic reactivity of small aromatic molecules toward a minimal model of the active site of AOX. The workflow is based on quantum chemical transition state searches for the underlying single-step oxidation reaction, where the automated protocol includes identification of unique aromatic C-H bonds, creation of three-dimensional reactant and product complex geometries via a templating approach, search for a transition state, and validation of reaction end points. Conformational search on the reactants, products, and the transition states is performed. The automated procedure has been validated on previously reported transition state barriers and was used to evaluate the intrinsic reactivity of nearly three hundred heterocycles commonly found in approved drug molecules. The intrinsic reactivity of more than 1000 individual aromatic carbon sites is reported. Stereochemical and conformational aspects of the oxidation reaction, which have not been discussed in previous studies, are shown to play important roles in accurate modeling of the oxidation reaction. Observations on structural trends that determine the reactivity are provided and rationalized.

Predicting Regioselectivity of AO, CYP, FMO, and UGT Metabolism Using Quantum Mechanical Simulations and Machine Learning

Unexpected metabolism in modification and conjugation phases can lead to the failure of many late-stage drug candidates or even withdrawal of approved drugs. Thus, it is critical to predict the sites of metabolism (SoM) for enzymes, which interact with drug-like molecules, in the early stages of the research. This study presents methods for predicting the isoform-specific metabolism for human AOs, FMOs, and UGTs and general CYP metabolism for preclinical species. The models use semi-empirical quantum mechanical simulations, validated using experimentally obtained data and DFT calculations, to estimate the reactivity of each SoM in the context of the whole molecule. Ligand-based models, trained and tested using high-quality regioselectivity data, combine the reactivity of the potential SoM with the orientation and steric effects of the binding pockets of the different enzyme isoforms. The resulting models achieve κ values of up to 0.94 and AUC of up to 0.92.

Non-cytochrome P450 enzymes involved in the oxidative metabolism of xenobiotics: Focus on the regulation of gene expression and enzyme activity

Oxidative metabolism is one of the major biotransformation reactions that regulates the exposure of xenobiotics and their metabolites in the circulatory system and local tissues and organs, and influences their efficacy and toxicity. Although cytochrome (CY)P450s play critical roles in the oxidative reaction, extensive CYP450-independent oxidative metabolism also occurs in some xenobiotics, such as aldehyde oxidase, xanthine oxidoreductase, flavin-containing monooxygenase, monoamine oxidase, alcohol dehydrogenase, or aldehyde dehydrogenase-dependent oxidative metabolism. Drugs form a large portion of xenobiotics and are the primary target of this review. The common reaction mechanisms and roles of non-CYP450 enzymes in metabolism, factors affecting the expression and activity of non-CYP450 enzymes in terms of inhibition, induction, regulation, and species differences in pharmaceutical research and development have been summarized. These non-CYP450 enzymes are detoxifying enzymes, although sometimes they mediate severe toxicity. Synthetic or natural chemicals serve as inhibitors for these non-CYP450 enzymes. However, pharmacokinetic-based drug interactions through these inhibitors have rarely been reported in vivo. Although multiple mechanisms participate in the basal expression and regulation of non-CYP450 enzymes, only a limited number of inducers upregulate their expression. Therefore, these enzymes are considered non-inducible or less inducible. Overall, this review focuses on the potential xenobiotic factors that contribute to variations in gene expression levels and the activities of non-CYP450 enzymes.

A comprehensive review of in silico approaches for the prediction and modulation of aldehyde oxidase-mediated drug metabolism: The current features, challenges and future perspectives

The importance of aldehyde oxidase (AOX) in drug metabolism necessitates the development and application of the in silico rational drug design methods as an integral part of drug discovery projects for the early prediction and modulation of AOX-mediated metabolism. The current study represents an up-to-date and thorough review of in silico studies of AOX-mediated metabolism and modulation methods. In addition, the challenges and the knowledge gap that should be covered have been discussed. The importance of aldehyde oxidase (AOX) in drug metabolism is a hot topic in drug discovery. Different strategies are available for the modulation of the AOX-mediated metabolism of drugs. Application of the rational drug design methods as an integral part of drug discovery projects is necessary for the early prediction of AOX-mediated metabolism. The current study represents a comprehensive review of AOX molecular structure, AOX-mediated reactions, AOX substrates, AOX inhibition, approaches to modify AOX-mediated metabolism, prediction of AOX metabolism/substrates/inhibitors, and the AOX related structure-activity relationship (SAR) studies. Furthermore, an up-to-date and thorough review of in silico studies of AOX metabolism has been carried out. In addition, the challenges and the knowledge gap that should be covered in the scientific literature have been discussed in the current review.

Predicting liver cytosol stability of small molecules

Over the last few decades, chemists have become skilled at designing compounds that avoid cytochrome P (CYP) 450 mediated metabolism. Typical screening assays are performed in liver microsomal fractions and it is possible to overlook the contribution of cytosolic enzymes until much later in the drug discovery process. Few data exist on cytosolic enzyme-mediated metabolism and no reliable tools are available to chemists to help design away from such liabilities. In this study, we screened 1450 compounds for liver cytosol-mediated metabolic stability and extracted transformation rules that might help medicinal chemists in optimizing compounds with these liabilities. In vitro half-life data were collected by performing in-house experiments in mouse (CD-1 male) and human (mixed gender) cytosol fractions. Matched molecular pairs analysis was performed in conjunction with qualitative-structure activity relationship modeling to identify chemical structure transformations affecting cytosolic stability. The transformation rules were prospectively validated on the test set. In addition, selected rules were validated on a diverse chemical library and the resulting pairs were experimentally tested to confirm whether the identified transformations could be generalized. The validation results, comprising nearly 250 library compounds and corresponding half-life data, are made publicly available. The datasets were also used to generate in silico classification models, based on different molecular descriptors and machine learning methods, to predict cytosol-mediated liabilities. To the best of our knowledge, this is the first systematic in silico effort to address cytosolic enzyme-mediated liabilities.

Metabolism by Aldehyde Oxidase: Drug Design and Complementary Approaches to Challenges in Drug Discovery

Aldehyde oxidase (AO) catalyzes oxidations of azaheterocycles and aldehydes, amide hydrolysis, and diverse reductions. AO substrates are rare among marketed drugs, and many candidates failed due to poor pharmacokinetics, interspecies differences, and adverse effects. As most issues arise from complex and poorly understood AO biology, an effective solution is to stop or decrease AO metabolism. This perspective focuses on rational drug design approaches to modulate AO-mediated metabolism in drug discovery. AO biological aspects are also covered, as they are complementary to chemical design and important when selecting the experimental system for risk assessment. The authors' recommendation is an early consideration of AO-mediated metabolism supported by computational and in vitro experimental methods but not an automatic avoidance of AO structural flags, many of which are versatile and valuable building blocks. Preferably, consideration of AO-mediated metabolism should be part of the multiparametric drug optimization process, with the goal to improve overall drug-like properties.

Scaffold-hopping as a strategy to address metabolic liabilities of aromatic compounds

Understanding and minimizing oxidative metabolism of aromatic compounds is a key hurdle in lead optimization. Metabolic processes not only clear compounds from the body, but they can also transform parent compounds into reactive metabolites. One particularly useful strategy when addressing metabolically labile or oxidation-prone structures is scaffold-hopping. Replacement of an aromatic system with a more electron-deficient ring system can often increase robustness towards cytochrome P450-mediated oxidation while conserving the structural requirements of the pharmacophore. The most common example of this substitution strategy, replacement of a phenyl ring with a pyridyl substituent, is prevalent throughout the literature; however scaffold-hopping encompasses a much wider scope of heterocycle replacement. This review will showcase recent examples where different scaffold-hopping approaches were used to reduce metabolic clearance or block the formation of reactive metabolites. Additionally, we will highlight considerations that should be made to garner the most benefit from a scaffold-hopping strategy for lead optimization.

Aldehyde oxidase and its role as a drug metabolizing enzyme

Aldehyde oxidase (AO) is a cytosolic enzyme that belongs to the family of structurally related molybdoflavoproteins like xanthine oxidase (XO). The enzyme is characterized by broad substrate specificity and marked species differences. It catalyzes the oxidation of aromatic and aliphatic aldehydes and various heteroaromatic rings as well as reduction of several functional groups. The references to AO and its role in metabolism date back to the 1950s, but the importance of this enzyme in the metabolism of drugs has emerged in the past fifteen years. Several reviews on the role of AO in drug metabolism have been published in the past decade indicative of the growing interest in the enzyme and its influence in drug metabolism. Here, we present a comprehensive monograph of AO as a drug metabolizing enzyme with emphasis on marketed drugs as well as other xenobiotics, as substrates and inhibitors. Although the number of drugs that are primarily metabolized by AO are few, the impact of AO on drug development has been extensive. We also discuss the effect of AO on the systemic exposure and clearance these clinical candidates. The review provides a comprehensive analysis of drug discovery compounds involving AO with the focus on developmental candidates that were reported in the past five years with regards to pharmacokinetics and toxicity. While there is only one known report of AO-mediated clinically relevant drug-drug interaction (DDI), a detailed description of inhibitors and inducers of AO known to date has been presented here and the potential risks associated with DDI. The increasing recognition of the importance of AO has led to significant progress in predicting the site of AO-mediated metabolism using computational methods. Additionally, marked species difference in expression of AO makes it is difficult to predict human clearance with high confidence. The progress made towards developing in vivo, in vitro and in silico approaches for predicting AO metabolism and estimating human clearance of compounds that are metabolized by AO have also been discussed.

Fast Methods for Prediction of Aldehyde Oxidase-Mediated Site-of-Metabolism

Aldehyde Oxidase (AO) is an enzyme involved in the metabolism of aldehydes and N-containing heterocyclic compounds. Many drug compounds contain heterocyclic moieties, and AO metabolism has lead to failure of several late-stage drug candidates. Therefore, it is important to take AO-mediated metabolism into account early in the drug discovery process, and thus, to have fast and reliable models to predict the site of metabolism (SOM). We have collected a dataset of 78 substrates of human AO with a total of 89 SOMs and 347 non-SOMs and determined atomic descriptors for each compound. The descriptors comprise NMR shielding and ESP charges from density functional theory (DFT), NMR chemical shift from ChemBioDraw, and Gasteiger charges from RDKit. Additionally, atomic accessibility was considered using 2D-SASA and relative span descriptors from SMARTCyp. Finally, stability of the product, the metabolite, was determined with DFT and also used as a descriptor. All descriptors have AUC larger than 0.75. In particular, descriptors related to the chemical shielding and chemical shift (AUC = 0.96) and ESP charges (AUC = 0.96) proved to be good descriptors. We recommend two simple methods to identify the SOM for a given molecule: 1) use ChemBioDraw to calculate the chemical shift or 2) calculate ESP charges or chemical shift using DFT. The first approach is fast but somewhat difficult to automate, while the second is more time-consuming, but can easily be automated. The two methods predict correctly 93% and 91%, respectively, of the 89 experimentally observed SOMs.

Time Course of Aldehyde Oxidase and Why It Is Nonlinear

Many promising drug candidates metabolized by aldehyde oxidase (AOX) fail during clinical trial owing to underestimation of their clearance. AOX is species-specific, which makes traditional allometric studies a poor choice for estimating human clearance. Other studies have suggested using half-life calculated by measuring substrate depletion to measure clearance. In this study, we proposed using numerical fitting to enzymatic pathways other than Michaelis-Menten (MM) to avoid missing the initial high turnover rate of product formation. Here, product formation over a 240-minute time course of six AOX substrates-O⁶-benzylguanine, N-(2-dimethylamino)ethyl)acridine-4-carboxamide, zaleplon, phthalazine, BIBX1382 [N8-(3-Chloro-4-fluorophenyl)-N2-(1-methyl-4-piperidinyl)-pyrimido[5,4-d]pyrimidine-2,8-diamine dihydrochloride], and zoniporide-have been provided to illustrate enzyme deactivation over time to help better understand why MM kinetics sometimes leads to underestimation of rate constants. Based on the data provided in this article, the total velocity for substrates becomes slower than the initial velocity by 3.1-, 6.5-, 2.9-, 32.2-, 2.7-, and 0.2-fold, respectively, in human expressed purified enzyme, whereas the K _m remains constant. Also, our studies on the role of reactive oxygen species (ROS), such as superoxide and hydrogen peroxide, show that ROS did not significantly alter the change in enzyme activity over time. Providing a new electron acceptor, 5-nitroquinoline, did, however, alter the change in rate over time for mumerous compounds. The data also illustrate the difficulties in using substrate disappearance to estimate intrinsic clearance.

Quantitative Prediction of Human Hepatic Clearance for P450 and Non-P450 Substrates from In Vivo Monkey Pharmacokinetics Study and In Vitro Metabolic Stability Tests Using Hepatocytes

Accurate prediction of human pharmacokinetics for drugs remains challenging, especially for non-cytochrome P450 (P450) substrates. Hepatocytes might be suitable for predicting hepatic intrinsic clearance (CL_int) of new chemical entities, because they can be applied to various compounds regardless of the metabolic enzymes. However, it was reported that hepatic CL_int is underestimated in hepatocytes. The purpose of the present study was to confirm the predictability of human hepatic clearance for P450 and non-P450 substrates in hepatocytes and the utility of animal scaling factors for the prediction using hepatocytes. CL_int values for 30 substrates of P450, UDP-glucuronosyltransferase, flavin-containing monooxygenase, esterases, reductases, and aldehyde oxidase in human microsomes, human S9 and human, rat, and monkey hepatocytes were estimated. Hepatocytes were incubated in serum of each species. Furthermore, CL_int values in human hepatocytes were corrected with empirical, monkey, and rat scaling factors. CL_int values in hepatocytes for most compounds were underestimated compared to observed values regardless of the metabolic enzyme, and the predictability was improved by using the scaling factors. The prediction using human hepatocytes corrected with monkey scaling factor showed the highest predictability for both P450 and non-P450 substrates among the predictions using liver microsomes, liver S9, and hepatocytes with or without scaling factors. CL_int values by this method for 80% and 90% of all compounds were within 2- and 3-fold of observed values, respectively. This method is accurate and useful for estimating new chemical entities, with no need to care about cofactors, localization of metabolic enzymes, or protein binding in plasma and incubation mixture.

Metabolism of c-Met Kinase Inhibitors Containing Quinoline by Aldehyde Oxidase, Electron Donating, and Steric Hindrance Effect

Some quinoline-containing c-Met kinase inhibitors are aldehyde oxidase (AO) substrates. 3-Substituted quinoline triazolopyridine analogs were synthesized to understand the electron-donating and steric hindrance effects on AO-mediated metabolism. Metabolic stability studies for these quinoline analogs were carried out in liver cytosol from mice, rats, cynomolgus monkeys, and humans. Several 3-N-substituted analogs were found to be unstable in monkey liver cytosolic incubations (half-life, <10 minutes), and five of them (63, 53, 51, 11, and 71) were chosen for additional mechanistic studies. Mono-oxygenation on the quinoline ring was identified by liquid chromatography tandem mass spectrometry. Metabolite formation was inhibited by the AO inhibitors menadione and raloxifene, but not by the xanthine oxidase inhibitor allopurinol. It was found that small electron-donating groups at the 3-quinoline moiety made the analogs more susceptible to AO metabolism, whereas large 3-substituents could reverse the trend. Although species differences were observed, this trend was applicable to all species tested. Small electron-donating substituents at the 3-quinoline moiety increased both affinity (decreased Michaelis constant) and V _max maximum velocity toward AO in kinetic studies, whereas large substituents decreased both parameters probably as a result of steric hindrance. Based on our analysis, a common structural feature with high AO liability was proposed. Our finding could provide useful information for chemists to minimize potential AO liability when designing quinoline analogs.

ecoAO: A Simple System for the Study of Human Aldehyde Oxidases Role in Drug Metabolism

Although aldehyde oxidase (AO) is an important hepatic drug-metabolizing enzyme, it remains understudied and is consequently often overlooked in preclinical studies, an oversight that has resulted in the failure of multiple clinical trials. AO's preclusion to investigation stems from the following: (1) difficulties synthesizing metabolic standards due to the chemospecificity and regiospecificity of the enzyme and (2) significant inherent variability across existing in vitro systems including liver cytosol, S9 fractions, and primary hepatocytes, which lack specificity and generate discordant expression and activity profiles. Here, we describe a practical bacterial biotransformation system, ecoAO, addressing both issues simultaneously. ecoAO is a cell paste of MoCo-producing Escherichia coli strain TP1017 expressing human AO. It exhibits specific activity toward known substrates, zoniporide, 4-trans-(N,N-dimethylamino)cinnamaldehyde, O6-benzylguanine, and zaleplon; it also has utility as a biocatalyst, yielding milligram quantities of synthetically challenging metabolite standards such as 2-oxo-zoniporide. Moreover, ecoAO enables routine determination of kcat and V/K, which are essential parameters for accurate in vivo clearance predictions. Furthermore, ecoAO has potential as a preclinical in vitro screening tool for AO activity, as demonstrated by its metabolism of 3-aminoquinoline, a previously uncharacterized substrate. ecoAO promises to provide easy access to metabolites with the potential to improve pharmacokinetic clearance predictions and guide drug development.

Aldehyde Oxidase: Reaction Mechanism and Prediction of Site of Metabolism

Aldehyde oxidase (AO) is a molybdenum-containing enzyme involved in the clearance of drug compounds containing aldehydes and N-containing heterocyclic fragments. AO has gained considerable interest in recent years because of examples of too fast clearance of drug compounds in development. Thus, it is important to be able to predict AO-mediated drug metabolism. Therefore, we have characterized the structural and energetic aspects of different mechanisms with density functional theory using the molybdenum cofactor as a model for the reactive part of the enzyme. For a series of 6-substituted 4-quinazolinones, the trend in activation energies is the same for three tested reaction mechanisms. Using the concerted mechanism as a model for the enzymatic reaction, the transition states (TSs) for the formation of all possible metabolites for a series of known AO substrates were determined. The lowest activation energies correspond in all cases to the experimentally observed sites of metabolism (SOMs). Various molecular properties were calculated and investigated as more easily determinable markers for reactivity. The stabilities of both intermediates and products correlate to some extent with the TS energies and may be used to predict the SOM. The electrostatic-potential-derived charges are also good markers for the prediction of the experimental SOM for this set of compounds and may pave the way for the development of fast methods for the prediction of SOM for AO substrates.

Structure-metabolism relationships in human-AOX: Chemical insights from a large database of aza-aromatic and amide compounds

Aldehyde oxidase (AOX) is a metabolic enzyme catalyzing the oxidation of aldehyde and aza-aromatic compounds and the hydrolysis of amides, moieties frequently shared by the majority of drugs. Despite its key role in human metabolism, to date only fragmentary information about the chemical features responsible for AOX susceptibility are reported and only "very local" structure-metabolism relationships based on a small number of similar compounds have been developed. This study reports a more comprehensive coverage of the chemical space of structures with a high risk of AOX phase I metabolism in humans. More than 270 compounds were studied to identify the site of metabolism and the metabolite(s). Both electronic [supported by density functional theory (DFT) calculations] and exposure effects were considered when rationalizing the structure-metabolism relationship.

Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data

PURPOSE

Mouse efficacy studies are a critical hurdle to advance translational research of potential therapeutic compounds for many diseases. Although mouse liver microsomal (MLM) stability studies are not a perfect surrogate for in vivo studies of metabolic clearance, they are the initial model system used to assess metabolic stability. Consequently, we explored the development of machine learning models that can enhance the probability of identifying compounds possessing MLM stability.

METHODS

Published assays on MLM half-life values were identified in PubChem, reformatted, and curated to create a training set with 894 unique small molecules. These data were used to construct machine learning models assessed with internal cross-validation, external tests with a published set of antitubercular compounds, and independent validation with an additional diverse set of 571 compounds (PubChem data on percent metabolism).

RESULTS

"Pruning" out the moderately unstable / moderately stable compounds from the training set produced models with superior predictive power. Bayesian models displayed the best predictive power for identifying compounds with a half-life ≥1 h.

CONCLUSIONS

Our results suggest the pruning strategy may be of general benefit to improve test set enrichment and provide machine learning models with enhanced predictive value for the MLM stability of small organic molecules. This study represents the most exhaustive study to date of using machine learning approaches with MLM data from public sources.

Interspecies differences in the metabolism of methotrexate: An insight into the active site differences between human and rabbit aldehyde oxidase

Several drug compounds have failed in clinical trials due to extensive biotransformation by aldehyde oxidase (AOX) (EC 1.2.3.1). One of the main reasons is the difficulty in scaling clearance for drugs metabolised by AOX, from preclinical species to human. Using methotrexate as a probe substrate, we evaluated AOX metabolism in liver cytosol from human and commonly used laboratory species namely guinea pig, monkey, rat and rabbit. We found that the metabolism of methotrexate in rabbit liver cytosol was several orders of magnitude higher than any of the other species tested. The results of protein quantitation revealed that the amount of AOX1 in human liver was similar to rabbit liver. To understand if the observed differences in activity were due to structural differences, we modelled rabbit AOX1 using the previously generated human AOX1 homology model. Molecular docking of methotrexate into the active site of the enzyme led to the identification of important residues that could potentially be involved in substrate binding and account for the observed differences. In order to study the impact of these residue changes on enzyme activity, we used site directed mutagenesis to construct mutant AOX1 cDNAs by substituting nucleotides of human AOX1 with relevant ones of rabbit AOX1. AOX1 mutant proteins were expressed in Escherichia coli. Differences in the kinetic properties of these mutants have been presented in this study.

A novel reaction mediated by human aldehyde oxidase: amide hydrolysis of GDC-0834

GDC-0834, a Bruton's tyrosine kinase inhibitor investigated as a potential treatment of rheumatoid arthritis, was previously reported to be extensively metabolized by amide hydrolysis such that no measurable levels of this compound were detected in human circulation after oral administration. In vitro studies in human liver cytosol determined that GDC-0834 (R)-N-(3-(6-(4-(1,4-dimethyl-3-oxopiperazin-2-yl)phenylamino)-4-methyl-5-oxo- 4,5-dihydropyrazin-2-yl)-2-methylphenyl)-4,5,6,7-tetrahydrobenzo[b] thiophene-2-carboxamide) was rapidly hydrolyzed with a CLint of 0.511 ml/min per milligram of protein. Aldehyde oxidase (AO) and carboxylesterase (CES) were putatively identified as the enzymes responsible after cytosolic fractionation and mass spectrometry-proteomics analysis of the enzymatically active fractions. Results were confirmed by a series of kinetic experiments with inhibitors of AO, CES, and xanthine oxidase (XO), which implicated AO and CES, but not XO, as mediating GDC-0834 amide hydrolysis. Further supporting the interaction between GDC-0834 and AO, GDC-0834 was shown to be a potent reversible inhibitor of six known AO substrates with IC50 values ranging from 0.86 to 1.87 μM. Additionally, in silico modeling studies suggest that GDC-0834 is capable of binding in the active site of AO with the amide bond of GDC-0834 near the molybdenum cofactor (MoCo), orientated in such a way to enable potential nucleophilic attack on the carbonyl of the amide bond by the hydroxyl of MoCo. Together, the in vitro and in silico results suggest the involvement of AO in the amide hydrolysis of GDC-0834.

A simple litmus test for aldehyde oxidase metabolism of heteroarenes

The bioavailability of aromatic azaheterocyclic drugs can be affected by the activity of aldehyde oxidase (AO). Susceptibility to AO metabolism is difficult to predict computationally and can be complicated in vivo by differences between species. Here we report the use of bis(((difluoromethyl)sulfinyl)oxy)zinc (DFMS) as a source of CF₂H radical for a rapid and inexpensive chemical “litmus test” for the early identification of heteroaromatic drug candidates that have a high probability of metabolism by AO.

The role of drug metabolizing enzymes in clearance

INTRODUCTION

Metabolism is one of the most important clearance pathways representing the major clearance route of 75% drugs. The four most common drug metabolizing enzymes (DME) that contribute significantly to elimination pathways of new chemical entities are cytochrome P450s, UDP-glucuronosyltransferases, aldehyde oxidase and sulfotransferases. Accurate prediction of human in vivo clearance by these enzymes, using both in vitro and in vivo tools, is critical for the success of drug candidates in human translation.

AREAS COVERED

Important recent advances of key DME are reviewed and highlighted in the following areas: major isoforms, tissue distribution, generic polymorphism, substrate specificity, species differences, mechanism of catalysis, in vitro-in vivo extrapolation and the importance of using optimal assay conditions and relevant animal models.

EXPERT OPINION

Understanding the clearance mechanism of a compound is the first step toward successful prediction of human clearance. It is critical to apply appropriate in vitro and in vivo methodologies and physiologically based models in human translation. While high-confidence prediction for P450-mediated clearance has been achieved, the accuracy of human clearance prediction is significantly lower for other enzyme classes. More accurate predictive methods and models are being developed to address these challenges.

Use of density functional theory in drug metabolism studies

INTRODUCTION

The cytochrome P450 enzymes (CYPs) metabolize many drug compounds. They catalyze a wide variety of reactions, and potentially, a large number of different metabolites can be generated. Density functional theory (DFT) has, over the past decade, been shown to be a powerful tool to rationalize and predict the possible metabolites generated by the CYPs as well as other drug-metabolizing enzymes.

AREAS COVERED

We review applications of DFT on reactions performed by the CYPs and other drug-metabolizing enzymes able to perform oxidation reactions, with an emphasis on predicting which metabolites are produced. We also cover calculations of binding energies for complexes in which the ligands interact directly with the heme iron atom.

EXPERT OPINION

DFT is a useful tool for prediction of the site of metabolism. The use of small models of the enzymes work surprisingly well for most CYP isoforms. This is probably due to the fact that the binding of the substrates is not the major determinant. When binding of the substrate plays a significant role, the well-known issue of determining the free energy of binding is the challenge. How approaches taking the protein environment into account, like docking, MD and QM/MM, can be used are discussed.

Absolute quantification of aldehyde oxidase protein in human liver using liquid chromatography-tandem mass spectrometry

The function of the enzyme human aldehyde oxidase (AOX1) is uncertain; however, recent studies have implicated significant biochemical involvement in humans. AOX1 has also rapidly become an important drug-metabolizing enzyme. Until now, quantitation of AOX1 in complex matrices such as tissue has not been achieved. Herein, we developed and employed a trypsin digest and subsequent liquid chromatography-tandem mass spectrometry analysis to determine absolute amounts of AOX1 in human liver. E. coli expressed human purified AOX1 was used to validate the linearity, sensitivity, and selectivity of the method. Overall, the method is highly efficient and sensitive for determination of AOX1 in cytosolic liver fractions. Using this method, we observed substantial batch-to-batch variation in AOX1 content (21-40 pmol AOX1/mg total protein) between various pooled human liver cytosol preparations. We also observed interbatch variation in Vmax (3.3-4.9 nmol min(-1) mg(-1)) and a modest correlation between enzyme concentration and activity. In addition, we measured a large difference in kcat/Km, between purified (kcat/Km of 1.4) and human liver cytosol (kcat/Km of 15-20) indicating cytosol to be 11-14 times more efficient in the turnover of DACA than the E. coli expressed purified enzyme. Finally, we discussed the future impact of this method for the development of drug metabolism models and understanding the biochemical role of this enzyme.

Evaluation of rhesus monkey and guinea pig hepatic cytosol fractions as models for human aldehyde oxidase

Aldehyde oxidase (AOX) is a cytosolic enzyme expressed across a wide range of species, including guinea pig and rhesus monkey. These species are believed to be the best preclinical models for studying human AOX-mediated metabolism. We compared AOX activity in rhesus monkeys, guinea pigs, and humans using phthalazine and N-[2-(dimethylamino)ethyl]acridone-4-carboxamide (DACA) as substrates and raloxifene as an inhibitor. Michaelis-Menten kinetics was observed for phthalazine oxidation in rhesus monkey, guinea pig, and human liver cytosol, whereas substrate inhibition was seen with DACA oxidase activity in all three livers. Raloxifene inhibited phthalazine and DACA oxidase activity uncompetitively in guinea pig, whereas mixed-mode inhibition was seen in rhesus monkey. Our analysis of the primary sequence alignment of rhesus monkey, guinea pig, and human aldehyde oxidase isoform 1 (AOX1) along with homology modeling has led to the identification of several amino acid residue differences within the active site and substrate entrance channel of AOX1. We speculate that some of these residues might be responsible for the differences observed in activity. Overall, our data indicate that rhesus monkeys and guinea pigs would overestimate intrinsic clearance in humans and would be unsuitable to use as animal models. Our study also showed that AOX metabolism in species is substrate-dependent and no single animal model can be reliably used to predict every drug response in humans.