Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism.

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

Industry Perspective on the Pharmacokinetic and Absorption, Distribution, Metabolism, and Excretion Characterization of Heterobifunctional Protein Degraders.

Targeted protein degraders (TPDs), specifically the bifunctional protein degraders discussed in this manuscript, consist of two linked ligands for a protein of interest and an E3 ligase, resulting in molecules that largely violate accepted physicochemical limits (e.g., Lipinski's Rule of Five) for oral bioavailability. In 2021, the IQ Consortium Degrader DMPK/ADME Working Group undertook a survey of 18 IQ member and nonmember companies working on degraders to understand whether the characterization and optimization of these molecules were different from any other beyond the Rule of Five (bRo5) compounds. Additionally, the working group sought to identify pharmacokinetic (PK)/absorption, distribution, metabolism, and excretion (ADME) areas in need of further evaluation and where additional tools could aid in more rapid advancement of TPDs to patients. The survey revealed that although TPDs reside in a challenging bRo5 physicochemical space, most respondents focus their efforts on oral delivery. Physicochemical properties required for oral bioavailability were generally consistent across the companies surveyed. Many of the member companies used modified assays to address challenging degrader properties (e.g., solubility, nonspecific binding), but only half indicated that they modified their drug discovery workflows. The survey also suggested the need for further scientific investigation in the areas of central nervous system penetration, active transport, renal elimination, lymphatic absorption, in silico/machine learning, and human pharmacokinetic prediction. Based on the survey results, the Degrader DMPK/ADME Working Group concluded that TPD evaluation does not fundamentally differ from other bRo5 compounds but requires some modification compared with traditional small molecules and proposes a generic workflow for PK/ADME evaluation of bifunctional TPDs. SIGNIFICANCE STATEMENT: Based on an industry survey, this article provides an understanding of the current state of absorption, distribution, metabolism, and excretion science pertaining to characterizing and optimizing targeted protein degraders, specifically bifunctional protein degraders, based upon responses by 18 IQ consortium members and non-members developing targeted protein degraders. Additionally, this article puts into context the differences / similarities in methods and strategies utilized for heterobifunctional protein degraders compared to other beyond Rule of Five molecules and conventional small molecule drugs.

Dissecting Parameters Contributing to the Underprediction of Aldehyde Oxidase-Mediated Metabolic Clearance of Drugs.

We investigated the effect of variability and instability in aldehyde oxidase (AO) content and activity on the scaling of in vitro metabolism data. AO content and activity in human liver cytosol (HLC) and five recombinant human AO preparations (rAO) were determined using targeted proteomics and carbazeran oxidation assay, respectively. AO content was highly variable as indicated by the relative expression factor (REF; i.e., HLC to rAO content) ranging from 0.001 to 1.7 across different in vitro systems. The activity of AO in HLC degrades at a 10-fold higher rate in the presence of the substrate as compared with the activity performed after preincubation without substrate. To scale the metabolic activity from rAO to HLC, a protein-normalized activity factor (pnAF) was proposed wherein the activity was corrected by AO content, which revealed up to sixfold higher AO activity in HLC versus rAO systems. A similar value of pnAF was observed for another substrate, ripasudil. Physiologically based pharmacokinetic (PBPK) modeling revealed a significant additional clearance (CL; 66%), which allowed for the successful prediction of in vivo CL of four other substrates, i.e., O-benzyl guanine, BIBX1382, zaleplon, and zoniporide. For carbazeran, the metabolite identification study showed that the direct glucuronidation may be contributing to around 12% elimination. Taken together, this study identified differential protein content, instability of in vitro activity, role of additional AO clearance, and unaccounted metabolic pathways as plausible reasons for the underprediction of AO-mediated drug metabolism. Consideration of these factors and integration of REF and pnAF in PBPK models will allow better prediction of AO metabolism. SIGNIFICANCE STATEMENT: This study elucidated the plausible reasons for the underprediction of aldehyde oxidase (AO)-mediated drug metabolism and provided recommendations to address them. It demonstrated that integrating protein content and activity differences and accounting for the loss of AO activity, as well as consideration of extrahepatic clearance and additional pathways, would improve the in vitro to in vivo extrapolation of AO-mediated drug metabolism using physiologically based pharmacokinetic modeling.

Challenges and Opportunities for In Vitro-In Vivo Extrapolation of Aldehyde Oxidase-Mediated Clearance: Toward a Roadmap for Quantitative Translation.

Underestimation of aldehyde oxidase (AO)-mediated clearance by current in vitro assays leads to uncertainty in human dose projections, thereby reducing the likelihood of success in drug development. In the present study we first evaluated the current drug development practices for AO substrates. Next, the overall predictive performance of in vitro-in vivo extrapolation of unbound hepatic intrinsic clearance (CLint,u) and unbound hepatic intrinsic clearance by AO (CLint,u,AO) was assessed using a comprehensive literature database of in vitro (human cytosol/S9/hepatocytes) and in vivo (intravenous/oral) data collated for 22 AO substrates (total of 100 datapoints from multiple studies). Correction for unbound fraction in the incubation was done by experimental data or in silico predictions. The fraction metabolized by AO (fmAO) determined via in vitro/in vivo approaches was found to be highly variable. The geometric mean fold errors (gmfe) for scaled CLint,u (mL/min/kg) were 10.4 for human hepatocytes, 5.6 for human liver cytosols, and 5.0 for human liver S9, respectively. Application of these gmfe's as empirical scaling factors improved predictions (45%-57% within twofold of observed) compared with no correction (11%-27% within twofold), with the scaling factors qualified by leave-one-out cross-validation. A road map for quantitative translation was then proposed following a critical evaluation on the in vitro and clinical methodology to estimate in vivo fmAO In conclusion, the study provides the most robust system-specific empirical scaling factors to date as a pragmatic approach for the prediction of in vivo CLint,u,AO in the early stages of drug development. SIGNIFICANCE STATEMENT: Confidence remains low when predicting in vivo clearance of AO substrates using in vitro systems, leading to de-prioritization of AO substrates from the drug development pipeline to mitigate risk of unexpected and costly in vivo impact. The current study establishes a set of empirical scaling factors as a pragmatic tool to improve predictability of in vivo AO clearance. Developing clinical pharmacology strategies for AO substrates by utilizing mass balance/clinical drug-drug interaction data will help build confidence in fmAO.

Contribution of Extrahepatic Aldehyde Oxidase Activity to Human Clearance.

Aldehyde oxidase (AOX) is a soluble, cytosolic enzyme that metabolizes various N-heterocyclic compounds and organic aldehydes. It has wide tissue distribution with highest levels found in liver, kidney, and lung. Human clearance projections of AOX substrates by in vitro assessments in isolated liver fractions (cytosol, S9) and even hepatocytes have been largely underpredictive of clinical outcomes. Various hypotheses have been suggested as to why this is the case. One explanation is that extrahepatic AOX expression contributes measurably to AOX clearance and is at least partially responsible for the often observed underpredictions. Although AOX expression has been confirmed in several extrahepatic tissues, activities therein and potential contribution to overall human clearance have not been thoroughly studied. In this work, the AOX enzyme activity using the S9 fractions of select extrahepatic human tissues (kidney, lung, vasculature, and intestine) were measured using carbazeran as a probe substrate. Measured activities were scaled to a whole-body clearance using best-available parameters and compared with liver S9 fractions. Here, the combined scaled AOX clearance obtained from the kidney, lung, vasculature, and intestine is very low and amounted to <1% of liver. This work suggests that AOX metabolism from extrahepatic sources plays little role in the underprediction of activity in human. One of the notable outcomes of this work has been the first direct demonstration of AOX activity in human vasculature. SIGNIFICANCE STATEMENT: This work demonstrates aldehyde oxidase (AOX) activity is measurable in a variety of extrahepatic human tissues, including vasculature, yet activities and potential contributions to human clearance are relatively low and insignificant when compared with the liver. Additionally, the modeling of the tissue-specific in vitro kinetic data suggests that AOX may be influenced by the tissue it resides in and thus show different affinity, activity, and modified activity over time.

Clearance Prediction of Targeted Covalent Inhibitors by In Vitro-In Vivo Extrapolation of Hepatic and Extrahepatic Clearance Mechanisms.

The concept of target-specific covalent enzyme inhibitors appears attractive from both an efficacy and a selectivity viewpoint considering the potential for enhanced biochemical efficiency associated with an irreversible mechanism. Aside from potential safety concerns, clearance prediction of covalent inhibitors represents a unique challenge due to the inclusion of nontraditional metabolic pathways of direct conjugation with glutathione (GSH) or via GSH S-transferase-mediated processes. In this article, a novel pharmacokinetic algorithm was developed using a series of Pfizer kinase selective acrylamide covalent inhibitors based on their in vitro-in vivo extrapolation of systemic clearance in rats. The algorithm encompasses the use of hepatocytes as an in vitro model for hepatic clearance due to oxidative metabolism and GSH conjugation, and the use of whole blood as an in vitro surrogate for GSH conjugation in extrahepatic tissues. Initial evaluations with clinical covalent inhibitors suggested that the scaling algorithm developed from rats may also be useful for human clearance prediction when species-specific parameters, such as hepatocyte and blood stability and blood binding, were considered. With careful consideration of clearance mechanisms, the described in vitro-in vivo extrapolation approach may be useful to facilitate candidate optimization, selection, and prediction of human pharmacokinetic clearance during the discovery and development of targeted covalent inhibitors.

In Vitro Kinetic Characterization of Axitinib Metabolism.

N-Methyl-2-[3-((E)-2-pyridin-2-yl-vinyl)-1H-indazol-6-ylsulfanyl]-benzamide (axitinib) is an oral inhibitor of vascular endothelial growth factor receptors 1-3, which is approved for the treatment of advanced renal cell cancer. Human [(14)C]-labeled clinical studies indicate axitinib's primary route of clearance is metabolism. The aims of the in vitro experiments presented herein were to identify and characterize the enzymes involved in axitinib metabolic clearance. In vitro biotransformation studies of axitinib identified a number of metabolites including an axitinib sulfoxide, several less abundant oxidative metabolites, and glucuronide conjugates. The most abundant NADPH- and UDPGA-dependent metabolites, axitinib sulfoxide (M12) and axitinib N-glucuronide (M7) were selected for phenotyping and kinetic study. Phenotyping experiments with human liver microsomes (HLMs) using chemical inhibitors and recombinant human cytochrome P450s demonstrated axitinib was predominately metabolized by CYP3A4/5, with minor contributions from CYP2C19 and CYP1A2. The apparent substrate concentration at half-maximal velocity (Km) and Vmax values for the formation of axitinib sulfoxide by CYP3A4 or CYP3A5 were 4.0 or 1.9 µM and 9.6 or 1.4 pmol·min(-1)·pmol(-1), respectively. Using a CYP3A4-specific inhibitor (Cyp3cide) in liver microsomes expressing CYP3A5, 66% of the axitinib intrinsic clearance was attributable to CYP3A4 and 15% to CYP3A5. Axitinib N-glucuronidation was primarily catalyzed by UDP-glucuronosyltransferase (UGT) UGT1A1, which was verified by chemical inhibitors and UGT1A1 null expressers, with lesser contributions from UGTs 1A3, 1A9, and 1A4. The Km and Vmax values describing the formation of the N-glucuronide in HLM or rUGT1A1 were 2.7 µM or 0.75 µM and 8.9 or 8.3 pmol·min(-1)·mg(-1), respectively. In summary, CYP3A4 is the major enzyme involved in axitinib clearance with lesser contributions from CYP3A5, CYP2C19, CYP1A2, and UGT1A1.

Reaction phenotyping: advances in the experimental strategies used to characterize the contribution of drug-metabolizing enzymes.

During the process of drug discovery, the pharmaceutical industry is faced with numerous challenges. One challenge is the successful prediction of the major routes of human clearance of new medications. For compounds cleared by metabolism, accurate predictions help provide an early risk assessment of their potential to exhibit significant interpatient differences in pharmacokinetics via routes of metabolism catalyzed by functionally polymorphic enzymes and/or clinically significant metabolic drug-drug interactions. This review details the most recent and emerging in vitro strategies used by drug metabolism and pharmacokinetic scientists to better determine rates and routes of metabolic clearance and how to translate these parameters to estimate the amount these routes contribute to overall clearance, commonly referred to as fraction metabolized. The enzymes covered in this review include cytochrome P450s together with other enzymatic pathways whose involvement in metabolic clearance has become increasingly important as efforts to mitigate cytochrome P450 clearance are successful. Advances in the prediction of the fraction metabolized include newly developed methods to differentiate CYP3A4 from the polymorphic enzyme CYP3A5, scaling tools for UDP-glucuronosyltranferase, and estimation of fraction metabolized for substrates of aldehyde oxidase.

Relative contributions of cytochrome CYP3A4 versus CYP3A5 for CYP3A-cleared drugs assessed in vitro using a CYP3A4-selective inactivator (CYP3cide).

Metabolism by cytochrome P4503A (CYP3A) is the most prevalent clearance pathway for drugs. Designation of metabolism by CYP3A commonly refers to the potential contribution by one or both of two enzymes, CYP3A4 and CYP3A5. The metabolic turnover of 32 drugs known to be largely metabolized by CYP3A was examined in human liver microsomes (HLMs) from CYP3A5 expressers (*1/*1 genotype) and nonexpressers (*3/*3 genotype) in the presence and absence of ketoconazole and CYP3cide (a selective CYP3A4 inactivator) to calculate the contribution of CYP3A5 to metabolism. Drugs with the highest contribution of CYP3A5 included atazanavir, vincristine, midazolam, vardenafil, otenabant, verapamil, and tacrolimus, whereas 17 of the 32 tested showed negligible CYP3A5 contribution. For specific reactions in HLMs from *1/*1 donors, CYP3A5 contributes 55% and 44% to midazolam 1'- and 4-hydroxylation, 16% to testosterone 6ß-hydroxylation, 56% and 19% to alprazolam 1'- and 4-hydroxylation, 10% to tamoxifen N-demethylation, and 58% to atazanavir p-hydroxylation. Comparison of the in vitro observations to clinical pharmacokinetic data showed only a weak relationship between estimated contribution by CYP3A5 and impact of CYP3A5 genotype on oral clearance, in large part because of the scatter in clinical data and the low numbers of study subjects used in CYP3A5 pharmacogenetics studies. These data should be useful in guiding which drugs should be evaluated for differences in pharmacokinetics and metabolism between subjects expressing CYP3A5 and those who do not express this enzyme.

Why do most human liver cytosol preparations lack xanthine oxidase activity?

When investigating the potential for xanthine oxidase (XO)-mediated metabolism of a new chemical entity in vitro, selective chemical inhibition experiments are typically used. Most commonly, these inhibition experiments are performed using the inhibitor allopurinol (AP) and commercially prepared human liver cytosol (HLC) as the enzyme source. For reasons detailed herein, it is also a common practice to perfuse livers with solutions containing AP prior to liver harvest. The exposure to AP in HLC preparations could obviously pose a problem for measuring in vitro XO activity. To investigate this potential problem, an HPLC-MS/MS assay was developed to determine whether AP and its primary metabolite, oxypurinol, are retained within the cytosol for livers that were treated with AP during liver harvest. Differences in enzymatic activity for XO and aldehyde oxidase (AO) in human cytosol that can be ascribed to AP exposure were also evaluated. The results confirmed the presence of residual AP (some) and oxypurinol (all) human liver cytosol preparations that had been perfused with an AP-containing solution. In every case where oxypurinol was detected, XO activity was not observed. In contrast, the presence of AP and oxypurinol did not appear to have an impact on AO activity. Pooled HLC that was purchased from a commercial source also contained residual oxypurinol and did not show any XO activity. In the future, it is recommended that each HLC batch is screened for oxypurinol and/or XO activity prior to testing for XO-mediated metabolism of a new chemical entity.

Use of a multistaged time-dependent inhibition assay to assess the impact of intestinal metabolism on drug-drug interaction potential.

In early discovery, compounds are often eliminated because of their potential to undergo metabolic activation and/or cytochrome P450 time-dependent inactivation (TDI). The blockbuster drug raloxifene is an example of a compound that would have been eliminated in the current paradigm. Despite raloxifene's in vitro bioactivation and TDI of CYP3A4, it is well tolerated in patients with no drug-drug interactions. This discordance is attributed to its presystemic glucuronidation, thereby decreasing the amount of unchanged raloxifene available for CYP3A inactivation. The current study used raloxifene as a model to assess the effect of hepatic and intestinal glucuronidation on the kinetic parameters of CYP3A4 inactivation. Therefore, a simple multistaged time-dependent inactivation using UDP-glucuronosyltransferase-enabled and -absent reactions was built to understand the impact of the gut metabolism on inactivation potential. The results of these experiments demonstrated a 2.7-fold change in inactivation efficiency of CYP3A4. Incorporation of these results into a simulated midazolam drug-drug interaction study showed very little change in the pharmacokinetic parameters of the victim drug. In contrast, the absence of glucuronidation resulted in a 4.1-fold increase in the area under the curve (AUC) of midazolam, when in the presence of raloxifene, hence providing an understanding of the impact of intestinal glucuronidation on raloxifene's time-dependent inhibition of CYP3A4 and also providing a validation of a simple in vitro experiment to assess the influence of gut metabolism on time-dependent inhibitors at the discovery phase.

Selective mechanism-based inactivation of CYP3A4 by CYP3cide (PF-04981517) and its utility as an in vitro tool for delineating the relative roles of CYP3A4 versus CYP3A5 in the metabolism of drugs.

CYP3cide (PF-4981517; 1-methyl-3-[1-methyl-5-(4-methylphenyl)-1H-pyrazol-4-yl]-4-[(3S)-3-piperidin-1-ylpyrrolidin-1-yl]-1H-pyrazolo[3,4-d]pyrimidine) is a potent, efficient, and specific time-dependent inactivator of human CYP3A4. When investigating its inhibitory properties, an extreme metabolic inactivation efficiency (k(inact)/K(I)) of 3300 to 3800 ml · min⁻¹ · µmol⁻¹ was observed using human liver microsomes from donors of nonfunctioning CYP3A5 (CYP3A5 *3/*3). This observed efficiency equated to an apparent K(I) between 420 and 480 nM with a maximal inactivation rate (k(inact)) equal to 1.6 min⁻¹. Similar results were achieved with testosterone, another CYP3A substrate, and other sources of the CYP3A4 enzyme. To further illustrate the abilities of CYP3cide, its partition ratio of inactivation was determined with recombinant CYP3A4. These studies produced a partition ratio approaching unity, thus underscoring the inactivation capacity of CYP3cide. When CYP3cide was tested at a concentration and preincubation time to completely inhibit CYP3A4 in a library of genotyped polymorphic CYP3A5 microsomes, the correlation of the remaining midazolam 1'-hydroxylase activity to CYP3A5 abundance was significant (R² value equal to 0.51, p value of <0.0001). The work presented here supports these findings by fully characterizing the inhibitory properties and exploring CYP3cide's mechanism of action. To aid the researcher, multiple commercially available sources of CYP3cide were established, and a protocol was developed to quantitatively determine CYP3A4 contribution to the metabolism of an investigational compound. Through the establishment of this protocol and the evidence provided here, we believe that CYP3cide is a very useful tool for understanding the relative roles of CYP3A4 versus CYP3A5 and the impact of CYP3A5 genetic polymorphism on a compound's pharmacokinetics.

Direct Comparison of the Prediction of the Unbound Brain-to-Plasma Partitioning Utilizing Machine Learning Approach and Mechanistic Neuropharmacokinetic Model.

The mechanistic neuropharmacokinetic (neuroPK) model was established to predict unbound brain-to-plasma partitioning (Kp,uu,brain) by considering in vitro efflux activities of multiple drug resistance 1 (MDR1) and breast cancer resistance protein (BCRP). Herein, we directly compare this model to a computational machine learning approach utilizing physicochemical descriptors and efflux ratios of MDR1 and BCRP-expressing cells for predicting Kp,uu,brain in rats. Two different types of machine learning techniques, Gaussian processes (GP) and random forest regression (RF), were assessed by the time and cluster-split validation methods using 640 internal compounds. The predictivity of machine learning models based on only molecular descriptors in the time-split dataset performed worse than the cluster-split dataset, whereas the models incorporating MDR1 and BCRP efflux ratios showed similar predictivity between time and cluster-split datasets. The GP incorporating MDR1 and BCRP in the time-split dataset achieved the highest correlation (R2 = 0.602). These results suggested that incorporation of MDR1 and BCRP in machine learning is beneficial for robust and accurate prediction. Kp,uu,brain prediction utilizing the neuroPK model was significantly worse compared to machine learning approaches for the same dataset. We also investigated the predictivity of Kp,uu,brain using an external independent test set of 34 marketed drugs. Compared to machine learning models, the neuroPK model showed better predictive performance with R2 of 0.577. This work demonstrates that the machine learning model for Kp,uu,brain achieves maximum predictive performance within the chemical applicability domain, whereas the neuroPK model is applicable more widely beyond the chemical space covered in the training dataset.

In vitro-in vivo correlation for intrinsic clearance for drugs metabolized by human aldehyde oxidase.

The ability to predict in vivo clearance from in vitro intrinsic clearance for compounds metabolized by aldehyde oxidase has not been demonstrated. To date, there is no established scaling method for predicting aldehyde oxidase-mediated clearance using in vitro or animal data. This challenge is exacerbated by the fact that rats and dogs, two of the laboratory animal species commonly used to develop in vitro-in vivo correlations of clearance, differ from humans with regard to expression of aldehyde oxidase. The objective of this investigation was to develop an in vitro-in vivo correlation of intrinsic clearance for aldehyde oxidase, using 11 drugs known to be metabolized by this enzyme. The set consisted of methotrexate, XK-469, (+/-)-4-(4-cyanoanilino)-5,6-dihydro-7-hydroxy-7H-cyclopenta[d]pyrimidine (RS-8359), zaleplon, 6-deoxypenciclovir, zoniporide, O(6)-benzylguanine, N-[(2'-dimethylamino)ethyl]acridine-4-carboxamide (DACA), carbazeran, PF-4217903, and PF-945863. These compounds were assayed using two in vitro systems (pooled human liver cytosol and liver S-9 fractions) to calculate scaled unbound intrinsic clearance, and they were then compared with calculated in vivo unbound intrinsic clearance. The investigation provided a relative scale that can be used for in vitro-in vivo correlation of aldehyde oxidase clearance and suggests limits as to when a potential new drug candidate that is metabolized by this enzyme will possess acceptable human clearance, or when structural modification is required to reduce aldehyde oxidase catalyzed metabolism.

Quantifying and predicting the promiscuity and isoform specificity of small-molecule cytochrome P450 inhibitors.

Drug promiscuity (i.e., inhibition of multiple enzymes by a single compound) is increasingly recognized as an important pharmacological consideration in the drug development process. However, systematic studies of functional or physicochemical characteristics that correlate with drug promiscuity are handicapped by the lack of a good way of quantifying promiscuity. In this article, we present a new entropy-based index of drug promiscuity. We apply this index to two high-throughput data sets describing inhibition of cytochrome P450 isoforms by small-molecule drugs and drug candidates, and we demonstrate how drug promiscuity or specificity can be quantified. For these drug-metabolizing enzymes, we find that there is essentially no correlation between a drug's potency and specificity. We also present an index to quantify the susceptibilities of different enzymes to inhibition by diverse substrates. Finally, we use partial least-squares regression to successfully predict isoform specificity and promiscuity of small molecules, using a set of fingerprint-based descriptors.

Identification of novel substrates for human cytochrome P450 2J2.

Several antihistamine drugs including terfenadine, ebastine, and astemizole have been identified as substrates for CYP2J2. The overall importance of this enzyme in drug metabolism has not been fully explored. In this study, 139 marketed therapeutic agents and compounds were screened as potential CYP2J2 substrates. Eight novel substrates were identified that vary in size and overall topology from relatively rigid structures (amiodarone) to larger complex structures (cyclosporine). The substrates displayed in vitro intrinsic clearance values ranging from 0.06 to 3.98 mul/min/pmol CYP2J2. Substrates identified for CYP2J2 are also metabolized by CYP3A4. Extracted ion chromatograms of metabolites observed for albendazole, amiodarone, astemizole, thioridazine, mesoridazine, and danazol showed marked differences in the regioselectivity of CYP2J2 and CYP3A4. CYP3A4 commonly metabolized compounds at multiple sites, whereas CYP2J2 metabolism was more restrictive and limited, in general, to a single site for large compounds. Although the CYP2J2 active site can accommodate large substrates, it may be more narrow than CYP3A4, limiting metabolism to moieties that can extend closer toward the active heme iron. For albendazole, CYP2J2 forms a unique metabolite compared with CYP3A4. Albendazole and amiodarone were evaluated in various in vitro systems including recombinant CYP2J2 and CYP3A4, pooled human liver microsomes (HLM), and human intestinal microsomes (HIM). The Michaelis-Menten-derived intrinsic clearance of N-desethyl amiodarone was 4.6 greater in HLM than in HIM and 17-fold greater in recombinant CYP3A4 than in recombinant CYP2J2. The resulting data suggest that CYP2J2 may be an unrecognized participant in first-pass metabolism, but its contribution is minor relative to that of CYP3A4.

Integrated in silico-in vitro strategy for addressing cytochrome P450 3A4 time-dependent inhibition.

Throughout the past decade, the expectations from the regulatory agencies for safety, drug-drug interactions (DDIs), pharmacokinetic, and disposition characterization of new chemical entities (NCEs) by pharmaceutical companies seeking registration have increased. DDIs are frequently assessed using in silico, in vitro, and in vivo methodologies. However, a key gap in this screening paradigm is a full structural understanding of time-dependent inhibition (TDI) on the cytochrome P450 systems, particularly P450 3A4. To address this, a number of high-throughput in vitro assays have been developed. This work describes an automated assay for TDI using two concentrations at two time points (2 + 2 assay). Data generated with this assay for over 2000 compounds from multiple therapeutic programs were used to generate in silico Bayesian classification models of P450 3A4-mediated TDI. These in silico models were validated using several external test sets and multiple random group testing (receiver operator curve value >0.847). We identified a number of substructures that were likely to elicit TDI, the majority containing indazole rings. These in vitro and in silico approaches have been implemented as a part of the Pfizer screening paradigm. The Bayesian models are available on the intranet to guide synthetic strategy, predict whether a NCE is likely to cause a TDI via P450 3A4, filter for in vitro testing, and identify substructures important for TDI as well as those that do not cause TDI. This represents an integrated in silico-in vitro strategy for addressing P450 3A4 TDI and improving the efficiency of screening.

Mechanism-based inactivation of cytochrome P450 2C9 by tienilic acid and (+/-)-suprofen: a comparison of kinetics and probe substrate selection.

In vitro experiments were conducted to compare k(inact), K(I) and inactivation efficiency (k(inact)/K(I)) of cytochrome P450 (P450) 2C9 by tienilic acid and (+/-)-suprofen using (S)-flurbiprofen, diclofenac, and (S)-warfarin as reporter substrates. Although the inactivation of P450 2C9 by tienilic acid when (S)-flurbiprofen and diclofenac were used as substrates was similar (efficiency of approximately 9 ml/min/micromol), the inactivation kinetics were characterized by a sigmoidal profile. (+/-)-Suprofen inactivation of (S)-flurbiprofen and diclofenac hydroxylation was also described by a sigmoidal profile, although inactivation was markedly less efficient (approximately 1 ml/min/micromol). In contrast, inactivation of P450 2C9-mediated (S)-warfarin 7-hydroxylation by tienilic acid and (+/-)-suprofen was best fit to a hyperbolic equation, where inactivation efficiency was moderately higher (10 ml/min/micromol) and approximately 3-fold higher (3 ml/min/micromol), respectively, relative to that of the other probe substrates, which argues for careful consideration of reporter substrate when mechanism-based inactivation of P450 2C9 is assessed in vitro. Further investigations into the increased inactivation seen with tienilic acid relative to that with (+/-)-suprofen revealed that tienilic acid is a higher affinity substrate with a spectral binding affinity constant (K(s)) of 2 microM and an in vitro half-life of 5 min compared with a K(s) of 21 microM and a 50 min in vitro half-life for (+/-)-suprofen. Lastly, a close analog of tienilic acid with the carboxylate functionality replaced by an oxirane ring was devoid of inactivation properties, which suggests that an ionic binding interaction with a positively charged residue in the P450 2C9 active site is critical for recognition and mechanism-based inactivation by these close structural analogs.

Characterization of cytochrome P450-mediated bioactivation of a compound containing the chemical scaffold, 4,5-dihydropyrazole-1-carboxylic acid-(4-chlorophenyl amide), to a chemically reactive p-chlorophenyl isocyanate intermediate in human liver microsomes.

Compound A (Cmpd A) was previously reported to form p-chlorophenyl isocyanate (CPIC), which was trapped by GSH to yield S- (N- [p-chlorophenyl] carbamoyl) glutathione adduct (SCPG) in the presence of human liver microsomes. In this study, P450 3A4 and 2C9 were demonstrated to be the enzymes mediating the activation of Cmpd A to CPIC in human liver microsomes based on inhibitory and correlation studies. Enzyme kinetics studies indicated that P450 3A4 was the primary enzyme involved in the activation of Cmpd A. In silico P450 3A4 active site docking of Cmpd A exhibited a low energy pose that orientated the pyrazole ring proximate to the heme iron atom, in which the distance between the C-3 and potential activated oxygen species was shown to be 3.4 A. Quantum molecular calculations showed that the electron density on C-3 was relatively higher than those on C-4 and C-5. These measurements suggested that the C-3 of Cmpd A was the preferred site of oxidation and hence predisposed Cmpd A in forming CPIC as previously proposed. The in silico prediction was corroborated by studies with the C-3 substituted analogue (methyl at C-3), which showed minimal conversion to CPIC in human liver microsomes. These results demonstrated a pivotal role for P450 3A4 in bioactivating Cmpd A by oxidizing at C-3 of the pyrazoline, hence facilitating the CPIC formation. Evidence of the bioactivation to CPIC in vivo was obtained by liquid chromatography-mass spectrometry (LC/MS) analysis of urine samples from human subjects administered a structural analogue of Cmpd A. The presence of S-(N-[p-chlorophenyl] carbamoyl) N-acetyl l-cysteine (SCPAC) as well as p-chlorophenyl aniline (CPA) was unequivocally demonstrated in the urine samples. The chemical scaffold, 4,5-dihydropyrazole-1-carboxylic acid-[(4-chlorophenyl)-amide], was demonstrated to possess potential metabolic liability in forming a reactive intermediate, CPIC, in humans. Bioactivation to CPIC may cause undesirable side effects through its reactivity and subsequent conversion to CPA, an established rodent carcinogen.

Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.

Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this "White Paper" alongside unresolved issues that were outlined for future debates.