Predictive value of comparative molecular field analysis modelling of naphthalene inhibition of human CYP2A6 and mouse CYP2A5 enzymes

Xenobiotica-metabolizing enzymes in the lung of experimental animals, man and in human lung models

The xenobiotic metabolism in the lung, an organ of first entry of xenobiotics into the organism, is crucial for inhaled compounds entering this organ intentionally (e.g. drugs) and unintentionally (e.g. work place and environmental compounds). Additionally, local metabolism by enzymes preferentially or exclusively occurring in the lung is important for favorable or toxic effects of xenobiotics entering the organism also by routes other than by inhalation. The data collected in this review show that generally activities of cytochromes P450 are low in the lung of all investigated species and in vitro models. Other oxidoreductases may turn out to be more important, but are largely not investigated. Phase II enzymes are generally much higher with the exception of UGT glucuronosyltransferases which are generally very low. Insofar as data are available the xenobiotic metabolism in the lung of monkeys comes closed to that in the human lung; however, very few data are available for this comparison. Second best rate the mouse and rat lung, followed by the rabbit. Of the human in vitro model primary cells in culture, such as alveolar macrophages and alveolar type II cells as well as the A549 cell line appear quite acceptable. However, (1) this generalization represents a temporary oversimplification born from the lack of more comparable data; (2) the relative suitability of individual species/models is different for different enzymes; (3) when more data become available, the conclusions derived from these comparisons quite possibly may change.

Effects of 8-methoxypsoralen on the metabolism of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone in mice

8-Methoxypsoralen (8-MOP) is a well established drug in the treatment of various skin diseases. Pretreatment of mice with 8-MOP before administration of 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) significantly reduced the incidence of NNK-induced tumor. The present study was designed to evaluate the in vivo effects of 8-MOP on the bioactivation of NNK in mice. Decrease in the α-hydroxylation of NNK in mouse blood and tissues was observed as the most pronounced effect of 8-MOP. The catalytic property of cytochrome P450 2A5 (CYP2A5) enzyme in mice was determined by the coumarin 7-hydroxylation reaction, suggesting that 8-MOP produced remarkable inhibition on CYP2A5 in female C57BL/6 mice. These results implied that 8-MOP could prevent NNK-induced mutagenesis and tumorigenesis in mice through the inhibition of NNK α-hydroxylation, which may be achieved through the effect of 8-MOP on the bioactivities of CYP2A5.

QSAR of cytochrome inhibitors

Cytochrome P450 (CYP450) enzymes are predominantly involved in the Phase I metabolism of xenobiotics. Metabolic inhibition and induction can give rise to clinically important drug-drug interactions. Metabolic stability is a prerequisite for sustaining the therapeutically relevant concentrations, and very often drug candidates are sacrificed due to poor metabolic profiles. Computational tools such as quantitative structure-activity relationships are widely used to study different metabolic end points successfully to accelerate the drug discovery process. There are a lot of computational studies on clinically important CYPs already reported in recent years. But other clinically significant families are to yet be explored computationally. Powerfulness of quantitative structure-activity relationship will drive computational chemists to develop new potent and selective inhibitors of different classes of CYPs for the treatment of different diseases with least drug-drug interactions. Furthermore, there is a need to enhance the accuracy, interpretability and confidence in the computational models in accelerating the drug discovery pathways.

Nicotine metabolism and urinary elimination in mouse: in vitro and in vivo

This study aimed at elucidating the in vivo metabolism of nicotine both with and without inhibitors of nicotine metabolism. Second, the role of mouse CYP2A5 in nicotine oxidation in vitro was studied as such information is needed to assess whether the mouse is a suitable model for studying chemical inhibitors of the human CYP2A6. The oxidation of nicotine to cotinine was measured and the ability of various inhibitors to modify this reaction was determined. Nicotine and various inhibitors were co-administered to CD2F1 mice, and nicotine and urinary levels of nicotine and four metabolites were determined. In mouse liver microsomes anti-CYP2A5 antibody and known chemical inhibitors of the CYP2A5 enzyme blocked cotinine formation by 85-100%, depending on the pre-treatment of the mice. The amount of trans-3-hydroxycotine was five times higher than cotinine N-oxide, and ten times higher than nicotine N-1-oxide and cotinine. Methoxsalen, an irreversible inhibitor of CYP2A5, significantly reduced the metabolic elimination of nicotine in vivo, but the reversible inhibitors had no effect. It is concluded that the metabolism of nicotine in mouse is very similar to that in man and, therefore, that the mouse is a suitable model for testing novel chemical inhibitors of human CYP2A6.

Comparative molecular field analysis of flavonoid inhibitors of the PIM-1 kinase

The PIM-1 protein, the product of the pim-1 oncogene, is a serine/threonine kinase. Dysregulation of the PIM-1 kinase has been implicated in the development of human malignancies including lymphomas, leukemias, and prostate cancer. Comparative molecular field analysis (CoMFA) is a 3-D QSAR technique that has been widely used, with notable success, to correlate biological activity with the steric and electrostatic properties of ligands. We have used a set of 15 flavonoid inhibitors of the PIM-1 kinase, aligned de novo by common substructure, to generate a CoMFA model for the purpose of elucidating the steric and electrostatic properties involved in flavonoid binding to the PIM-1 kinase. Partial least squares correlation between observed and predicted inhibitor potency (expressed as -logIC50), using a non-cross-validated partial least squares analysis, generated a non-cross-validated q2=0.805 for the training set (n=15) of flavonoids. The CoMFA generated steric map indicated that the PIM-1-binding site was sterically hindered, leading to more efficient binding of planar molecules over (R) or (S) compounds. The electrostatic map identified that positive charges near the flavonoid atom C8 and negative charges near C4' increased flavonoid binding. The CoMFA model accurately predicted the potency of a test set of flavonoids (n=6), generating a correlation between observed and predicted potency of q2=0.825. CoMFA models generated from additional alignment rules, which were guided by co-crystal structure ligand orientations, did not improve the correlative value of the model. Superimposing the PIM-1 kinase crystal structure onto the CoMFA contours validated the steric and electrostatic maps, elucidating the amino acid residues that potentially contribute to the CoMFA fields. Thus we have generated the first predictive model that may be used for the rational design of small-molecule inhibitors of the PIM-1 kinase.

The bacterial P450 BM3: a prototype for a biocatalyst with human P450 activities

The use of cytochrome P450 (P450 or CYP) enzymes as biocatalysts for the production of fine chemicals, including pharmaceuticals, has been of increasing interest, primarily owing to their catalytic diversity and broad substrate range. CYP102A1 (P450 BM3) from Bacillus megaterium integrates an entire monooxygenase system into one polypeptide and represents an appropriate prokaryotic model for industrial applications of mammalian P450 activities. CYP102A1 not only exhibits the highest catalytic activity ever detected in a P450 monooxygenase but also provides a potentially versatile biocatalyst for the production of human P450 metabolites. CYP102A1 can be further engineered to be a drug-metabolizing enzyme, making it a promising candidate to use as a biocatalyst in drug discovery and synthesis.

Non-Nicotinic Therapies for Smoking Cessation

Cigarette smoking is the primary cause of numerous preventable diseases; as such, the goals of smoking cessation are both to reduce health risks and to improve the quality of life. Currently, the first-line smoking cessation therapies include nicotine replacement products and bupropion. The nicotinic receptor partial agonist varenicline has recently been approved by the FDA for smoking cessation. A newer product currently under development and seeking approval by the FDA are nicotine vaccines. Clonidine and nortriptyline have demonstrated some efficacy but side effects may limit their use to second-line therapeutic products. Other therapeutic drugs that are under development include rimonabant, mecamylamine, monoamine oxidase inhibitors, and dopamine receptor D3 antagonists. Inhibitors of nicotine metabolism are also promising candidates for smoking reduction and cessation. In conclusion, promising new therapeutic products are emerging and they will provide smokers additional options to assist in achieving smoking cessation.

Methods for Predicting Human Drug Metabolism

Drug metabolism information is a necessary component of drug discovery and development. The key issues in drug metabolism include identifying: the enzyme(s) involved, the site(s) of metabolism, the resulting metabolite(s), and the rate of metabolism. Methods for predicting human drug metabolism from in vitro and computational methodologies and determining relationships between the structure and metabolic activity of molecules are also critically important for understanding potential drug interactions and toxicity. There are numerous experimental and computational approaches that have been developed in order to predict human metabolism which have their own limitations. It is apparent that few of the computational tools for metabolism prediction alone provide the major integrated functions needed to assist in drug discovery. Similarly the different in vitro methods for human drug metabolism themselves have implicit limitations. The utilization of these methods for pharmaceutical and other applications as well as their integration is discussed as it is likely that hybrid methods will provide the most success.

Naphthalene toxicity in mice and aryl hydrocarbon receptor-mediated CYPs

Naphthalene (NP) has been designated a "reasonably anticipated human carcinogen" because of positive responses in carcinogenicity bioassays in rodents. Whereas CYP2F enzymes are widely regarded as responsible for NP bioactivation, other metabolic enzymes--including CYP1A1 and CYP1A2--produce NP-1,2-oxide in vitro. We investigated the role of these aryl hydrocarbon receptor (AHR)-mediated enzymes in NP toxicity in two ways. First, NP was assessed for the ability to activate transcription via the AHR in an in vitro luciferase reporter assay and was found to have no activity. Second, mice deficient in AHR, CYP1A1 or CYP1A2 were dosed with NP alone, or following pretreatment with the CYP2F inhibitor 5-phenyl-1-pentyne. None of the knockout mice were protected from olfactory toxicity of NP. In contrast, CYP1A1- and CYP1A2-null mice pretreated with 5-phenyl-1-pentyne exhibited no NP olfactory toxicity. These results suggest that AHR-mediated enzymes do not contribute significantly to NP bioactivation in the intact animal.

Computational approaches for predicting CYP-related metabolism properties in the screening of new drugs

The site of biotransformation, the extent and rate of metabolism and the number of active metabolic pathways are among the most important characteristics of the pharmacokinetics of a drug. The catalytic activity of drug metabolizing enzymes is likely the most influential determinant of the pharmacokinetic variability. Metabolic stability is the prerequisite for sustaining the therapeutically relevant concentrations. Metabolic inhibition and induction can give rise to clinically important drug-drug interactions. A variety of computational approaches are currently available for predicting different cytochrome P450 (CYP)-related metabolism endpoints. The present review will describe these approaches and their impact on drug development process. Indications on the available software for the implementation will also be given.

Alternative QSAR models for selected estradiol and cytochrome P450 ligands: comparison between classical, spectroscopic, CoMFA and GRID/GOLPE methods

The performance of the spectroscopic EVA (eigenvalue) and EEVA (electronic eigenvalue) methods was tested with data sets applying coumarin 7-hydroxylation inhibitors (28 compounds) for cytochrome P450 mouse CYP2A5 and human CYP2A6 enzymes and 11ss-, 16a-, and 17a-substituted estradiol derivatives (30 compounds) for the lamb uterine estrogen receptor, and compared with the performance of the classical Hansch-type, CoMFA and GRID/GOLPE methods. Besides the internal predictability, the external predictability of the models was tested with several randomized training and test sets to ensure the validity and reliability of the models. Partial least squares (PLS) regression was employed as a general statistical tool with the EVA and EEVA methods. Some supplementary models were also built using only one PLS component with McGowan's volumes (MgVol and MgVol(2)) as additional descriptors and employing multiple linear regression (MLR) as the modelling tool. In general, both the internal and external performance of the EVA model, and more especially the EEVA model, with one PLS component and MgVol parameters was satisfactory, being either as good as or clearly better than that of the Hansch-type, CoMFA and GRID/GOLPE models.

CYP2S1: A short review

A new member of the cytochrome P450 superfamily, CYP2S1, has recently been identified in human and mouse. In this paper, we review the data currently available for CYP2S1. The human CYP2S1 gene is located in chromosome 19q13.2 within a cluster including CYP2 family members CYP2A6, CYP2A13, CYP2B6, and CYP2F1. These genes also show the highest homology to the human CYP2S1. The gene has recently been found to harbor genetic polymorphism. CYP2S1 is inducible by dioxin, the induction being mediated by the Aryl Hydrocarbon Receptor (AHR) and Aryl Hydrocarbon Nuclear Translocator (ARNT) in a manner typical for CYP1 family members. In line with this, CYP2S1 has been shown to be inducible by coal tar, an abundant source of PAHs, and it was recently reported to metabolize naphthalene. This points to the involvement of CYP2S1 in the metabolism of toxic and carcinogenic compounds, similar to other dioxin-inducible CYPs. CYP2S1 is expressed in epithelial cells of a wide variety of extrahepatic tissues. The highest expression levels have been observed in the epithelial tissues frequently exposed to xenobiotics, e.g., the respiratory, gastrointestinal, and urinary tracts, and in the skin. The observed ubiquitous tissue distribution, as well as the expression of CYP2S1 throughout embryogenesis suggest that CYP2S1 is likely to metabolize important endogenous substrates; thus far, retinoic acid has been identified. In conclusion, CYP2S1 exhibits many features of interest for human health and thus warrants further investigation.

Computational prediction of human drug metabolism

There is an urgent requirement within the pharmaceutical and biotechnology industries, regulatory authorities and academia to improve the success of molecules that are selected for clinical trials. Although absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) properties are some of the many components that contribute to successful drug discovery and development, they represent factors for which we currently have in vitro and in vivo data that can be modelled computationally. Understanding the possible toxicity and the metabolic fate of xenobiotics in the human body is particularly important in early drug discovery. There is, therefore, a need for computational methodologies for uncovering the relationships between the structure and the biological activity of novel molecules. The convergence of numerous technologies, including high-throughput techniques, databases, ADME/Tox modelling and systems biology modelling, is leading to the foundation of systems-ADME/Tox. Results from experiments can be integrated with predictions to globally simulate and understand the likely complete effects of a molecule in humans. The development and early application of major components of MetaDrug (GeneGo, Inc.) software will be described, which includes rule-based metabolite prediction, quantitative structure-activity relationship models for major drug metabolising enzymes, and an extensive database of human protein-xenobiotic interactions. This represents a combined approach to predicting drug metabolism. MetaDrug can be readily used for visualising Phase I and II metabolic pathways, as well as interpreting high-throughput data derived from microarrays as networks of interacting objects. This will ultimately aid in hypothesis generation and the early triaging of molecules likely to have undesirable predicted properties or measured effects on key proteins and cellular functions.

Predictive three-dimensional quantitative structure-activity relationship of cytochrome P450 1A2 inhibitors

The purpose of this study was to determine the cytochrome P450 1A2 (CYP1A2) inhibition potencies of structurally diverse compounds to create a comprehensive three-dimensional quantitative structure-activity relationship (3D-QSAR) model of CYP1A2 inhibitors and to use this model to predict the inhibition potencies of an external set of compounds. Fifty-two compounds including naphthalene, lactone and quinoline derivatives were assayed in a 96-well plate format for CYP1A2 inhibition activity using 7-ethoxyresorufin O-dealkylation as the probe reaction. The IC50 values of the tested compounds varied from 2.3 microM to over 40,000 microM. On the basis of this data set, a comparative molecular field analysis (CoMFA) and GRID/GOLPE models were created that yielded novel structural information about the interaction between inhibitory molecules and the CYP1A2 active site. The created CoMFA model was able to accurately predict inhibitory potencies of several structurally unrelated compounds, including selective inhibitors of other cytochrome P450 forms.

In silico approaches for predicting ADME properties of drugs

Combinatorial chemistry and high-throughput screening have increased the possibility of finding new lead compounds at much shorter time periods than conventional medicinal chemistry. However, too much promising drug candidates often fail because of unsatisfactory ADME properties. In silico ADME studies are expected to reduce the risk of late-stage attrition of drug development and to optimize screening and testing by looking at only the promising compounds. To this end, many in silico approaches for predicting ADME properties of compounds from their chemical structure have been developed, ranging from data-based approaches such as quantitative structure-activity relationship (QSAR), similarity searches, and 3-dimensional QSAR, to structure-based methods such as ligand-protein docking and pharmacophore modelling. In addition, several methods of integrating ADME properties to predict pharmacokinetics at the organ or body level have been studied. In this article, we briefly summarize in silico ADME approaches.

Metabolism and Disposition Kinetics of Nicotine

Nicotine is of importance as the addictive chemical in tobacco, pharmacotherapy for smoking cessation, a potential medication for several diseases, and a useful probe drug for phenotyping cytochrome P450 2A6 (CYP2A6). We review current knowledge about the metabolism and disposition kinetics of nicotine, some other naturally occurring tobacco alkaloids, and nicotine analogs that are under development as potential therapeutic agents. The focus is on studies in humans, but animal data are mentioned when relevant to the interpretation of human data. The pathways of nicotine metabolism are described in detail. Absorption, distribution, metabolism, and excretion of nicotine and related compounds are reviewed. Enzymes involved in nicotine metabolism including cytochrome P450 enzymes, aldehyde oxidase, flavin-containing monooxygenase 3, amine N-methyltransferase, and UDP-glucuronosyltransferases are represented, as well as factors affecting metabolism, such as genetic variations in metabolic enzymes, effects of diet, age, gender, pregnancy, liver and kidney diseases, and racial and ethnic differences. Also effects of smoking and various inhibitors and inducers, including oral contraceptives, on nicotine metabolism are discussed. Due to the significance of the CYP2A6 enzyme in nicotine clearance, special emphasis is given to the effects and population distributions of CYP2A6 alleles and the regulation of CYP2A6 enzyme.

Quantitative Structure−Activity Relationship Analysis of Inhibitors of the Nicotine Metabolizing CYP2A6 Enzyme

The purpose of this study was to develop screening and in silico modeling methods to obtain accurate information on the active center of CYP2A6, a nicotine oxidizing enzyme. The inhibitory potencies of 26 naphthalene and 16 non-naphthalene derivatives were determined for human CYP2A6 and mouse CYP2A5 enzymes. Several comparative molecular field analysis (CoMFA) models were developed to find out what types of steric and electrostatic properties are required for potent inhibitors. The IC(50) values of the tested compounds varied from 0.55 to 35 400 microM for CYP2A6 and from 1 to 1500 microM for CYP2A5. The generated CoMFA models were able to accurately predict the inhibition potencies of an external test set of chemicals. Potent and specific inhibitors of the CYP2A6 enzyme can be used in the future to increase nicotine bioavailability and thus make oral nicotine administration feasible in smoking cessation therapy.