Insights on cytochrome p450 enzymes and inhibitors obtained through QSAR studies

Evaluation of the Usefulness of Topological Indices for Predicting Selected Physicochemical Properties of Bioactive Substances with Anti-Androgenic and Hypouricemic Activity

Due to the observed increase in the importance of computational methods in determining selected physicochemical parameters of biologically active compounds that are key to understanding their ADME/T profile, such as lipophilicity, there is a great need to work on accurate and precise in silico models based on some structural descriptors, such as topological indices for predicting lipophilicity of certain anti-androgenic and hypouricemic agents and their derivatives, for which the experimental lipophilicity parameter is not accurately described in the available literature, e.g., febuxostat, oxypurinol, ailanthone, abiraterone and teriflunomide. Therefore, the following topological indices were accurately calculated in this paper: Gutman (M, Mν), Randić (0χ, 1χ, 0χν, 1χν), Wiener (W), Rouvray-Crafford (R) and Pyka (A, 0B, 1B) for the selected anti-androgenic drugs (abiraterone, bicalutamide, flutamide, nilutamide, leflunomide, teriflunomide, ailanthone) and some hypouricemic compounds (allopurinol, oxypurinol, febuxostat). Linear regression analysis was used to create simple linear correlations between the newly calculated topological indices and some physicochemical parameters, including lipophilicity descriptors of the tested compounds (previously obtained by TLC and theoretical methods). Our studies confirmed the usefulness of the obtained linear regression equations based on topological indices to predict ADME/T important parameters, such as lipophilicity descriptors of tested compounds with anti-androgenic and hypouricemic effects. The proposed calculation method based on topological indices is fast, easy to use and avoids valuable and lengthy laboratory experiments required in the case of experimental ADME/T studies.

Identification of Selective CYP3A7 and CYP3A4 Substrates and Inhibitors Using a High-Throughput Screening Platform

Cytochrome P450 (CYP) 3A7 is one of the major xenobiotic metabolizing enzymes in human embryonic, fetal, and newborn liver. CYP3A7 expression has also been observed in a subset of the adult population, including pregnant women, as well as in various cancer patients. The characterization of CYP3A7 is not as extensive as other CYPs, and health authorities have yet to provide guidance towards DDI assessment. To identify potential CYP3A7-specific molecules, we used a P450-Glo CYP3A7 enzyme assay to screen a library of ∼5,000 compounds, including FDA-approved drugs and drug-like molecules, and compared these screening data with that from a P450-Glo CYP3A4 assay. Additionally, a subset of 1,000 randomly selected compounds were tested in a metabolic stability assay. By combining the data from the qHTS P450-Glo and metabolic stability assays, we identified several chemical features important for CYP3A7 selectivity. Halometasone was chosen for further evaluation as a potential CYP3A7-selective inhibitor using molecular docking. From the metabolic stability assay, we identified twenty-two CYP3A7-selective substrates over CYP3A4 in supersome setting. Our data shows that CYP3A7 has ligand promiscuity, much like CYP3A4. Furthermore, we have established a large, high-quality dataset that can be used in predictive modeling for future drug metabolism and interaction studies.

Coumarins and P450s, Studies Reported to-Date

Cytochrome P450 enzymes (CYPs) are important phase I enzymes involved in the metabolism of endogenous and xenobiotic compounds mainly through mono-oxygenation reactions into more polar and easier to excrete species. In addition to their role in detoxification, they play important roles in the biosynthesis of endogenous compounds and the bioactivation of xenobiotics. Coumarins, phytochemicals abundant in food and commonly used in fragrances and cosmetics, have been shown to interact with P450 enzymes as substrates and/or inhibitors. In this review, these interactions and their significance in pharmacology and toxicology are discussed in detail.

Ethyl 2-[2-(4-oxo-4H-chromen-2-yl)phenoxy]acetate

In the title flavonoid derivative, C19H16O5, the chromene portion is planar (r.m.s. deviation = 0.022 Å) with the substituents lying closely to the same plane. The dihedral angle between its mean plane and that of the benzene ring is 4.9 (1)°. This planarity is due, in part, to the presence of a strong intramolecular C-H⋯O hydrogen bond and to two weak C-H⋯O contacts. In the crystal, neighboring molecules are linked by a C-H⋯O hydrogen bond and a C-H⋯π interaction, forming chains along the a-axis direction.

Comprehensive and Automated Linear Interaction Energy Based Binding-Affinity Prediction for Multifarious Cytochrome P450 Aromatase Inhibitors

Cytochrome P450 aromatase (CYP19A1) plays a key role in the development of estrogen dependent breast cancer, and aromatase inhibitors have been at the front line of treatment for the past three decades. The development of potent, selective and safer inhibitors is ongoing with in silico screening methods playing a more prominent role in the search for promising lead compounds in bioactivity-relevant chemical space. Here we present a set of comprehensive binding affinity prediction models for CYP19A1 using our automated Linear Interaction Energy (LIE) based workflow on a set of 132 putative and structurally diverse aromatase inhibitors obtained from a typical industrial screening study. We extended the workflow with machine learning methods to automatically cluster training and test compounds in order to maximize the number of explained compounds in one or more predictive LIE models. The method uses protein-ligand interaction profiles obtained from Molecular Dynamics (MD) trajectories to help model search and define the applicability domain of the resolved models. Our method was successful in accounting for 86% of the data set in 3 robust models that show high correlation between calculated and observed values for ligand-binding free energies (RMSE < 2.5 kJ mol-1), with good cross-validation statistics.

Review of Ligand Specificity Factors for CYP1A Subfamily Enzymes from Molecular Modeling Studies Reported to-Date

The cytochrome P450 (CYP) family 1A enzymes, CYP1A1 and CYP1A2, are two of the most important enzymes implicated in the metabolism of endogenous and exogenous compounds through oxidation. These enzymes are also known to metabolize environmental procarcinogens into carcinogenic species, leading to the advent of several types of cancer. The development of selective inhibitors for these P450 enzymes, mitigating procarcinogenic oxidative effects, has been the focus of many studies in recent years. CYP1A1 is mainly found in extrahepatic tissues while CYP1A2 is the major CYP enzyme in human liver. Many molecules have been found to be metabolized by both of these enzymes, with varying rates and/or positions of oxidation. A complete understanding of the factors that govern the specificity and potency for the two CYP 1A enzymes is critical to the development of effective inhibitors. Computational molecular modeling tools have been used by several research groups to decipher the specificity and potency factors of the CYP1A1 and CYP1A2 substrates. In this review, we perform a thorough analysis of the computational studies that are ligand-based and protein-ligand complex-based to catalog the various factors that govern the specificity/potency toward these two enzymes.

Inhibition of Carcinogen-Activating Cytochrome P450 Enzymes by Xenobiotic Chemicals in Relation to Antimutagenicity and Anticarcinogenicity

A variety of xenobiotic chemicals, such as polycyclic aromatic hydrocarbons (PAHs), aryl- and heterocyclic amines and tobacco related nitrosamines, are ubiquitous environmental carcinogens and are required to be activated to chemically reactive metabolites by xenobiotic-metabolizing enzymes, including cytochrome P450 (P450 or CYP), in order to initiate cell transformation. Of various human P450 enzymes determined to date, CYP1A1, 1A2, 1B1, 2A13, 2A6, 2E1, and 3A4 are reported to play critical roles in the bioactivation of these carcinogenic chemicals. In vivo studies have shown that disruption of Cyp1b1 and Cyp2a5 genes in mice resulted in suppression of tumor formation caused by 7,12-dimethylbenz[a]anthracene and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, respectively. In addition, specific inhibitors for CYP1 and 2A enzymes are able to suppress tumor formation caused by several carcinogens in experimental animals in vivo, when these inhibitors are applied before or just after the administration of carcinogens. In this review, we describe recent progress, including our own studies done during past decade, on the nature of inhibitors of human CYP1 and CYP2A enzymes that have been shown to activate carcinogenic PAHs and tobacco-related nitrosamines, respectively, in humans. The inhibitors considered here include a variety of carcinogenic and/or non-carcinogenic PAHs and acethylenic PAHs, many flavonoid derivatives, derivatives of naphthalene, phenanthrene, biphenyl, and pyrene and chemopreventive organoselenium compounds, such as benzyl selenocyanate and benzyl selenocyanate; o-XSC, 1,2-, 1,3-, and 1,4-phenylenebis( methylene)selenocyanate.

Drug Metabolism in Preclinical Drug Development: A Survey of the Discovery Process, Toxicology, and Computational Tools

BACKGROUND

While establishing efficacy in translational models and humans through clinically-relevant endpoints for disease is of great interest, assessing the potential toxicity of a putative therapeutic drug is critical. Toxicological assessments in the pre-clinical discovery phase help to avoid future failure in the clinical phases of drug development. Many in vitro assays exist to aid in modular toxicological assessment, such as hepatotoxicity and genotoxicity. While these methods have provided tremendous insight into human toxicity by investigational new drugs, they are expensive, require substantial resources, and do not account for pharmacogenomics as well as critical ADME properties. Computational tools can fill this niche in toxicology if in silico models are accurate in relating drug molecular properties to toxicological endpoints as well as reliable in predicting important drug-target interactions that mediate known adverse events or adverse outcome pathways (AOPs).

METHODS

We undertook an unstructured search of multiple bibliographic databases for peer-reviewed literature regarding computational methods in predictive toxicology for in silico drug discovery. As this review paper is meant to serve as a survey of available methods for the interested reader, no focused criteria were applied. Literature chosen was based on the writers' expertise and intent in communicating important aspects of in silico toxicology to the interested reader.

CONCLUSION

This review provides a purview of computational methods of pre-clinical toxicologic assessments for novel small molecule drugs that may be of use for novice and experienced investigators as well as academic and commercial drug discovery entities.

Characterization of Atomoxetine Biotransformation and Implications for Development of PBPK Models for Dose Individualization in Children

Atomoxetine (ATX) is a second-line nonstimulant medication used to control symptoms of attention deficit hyperactivity disorder (ADHD). Inconsistent therapeutic efficacy has been reported with ATX, which may be related to variable CYP2D6-mediated drug clearance. We characterized ATX metabolism in a panel of human liver samples as a basis for a bottom-up PBPK model to aid in ATX exposure prediction and control. Km, Vmax, and Clint values in pooled human liver microsomes (HLMs) were 2.4 µM, 479 pmol/min/mg protein, and 202 µl/min/mg protein, respectively. Mean population values of kinetic parameters are not adequate to describe variability in a population, given that Km, Vmax, and Clint values from single-donor HLMs ranged from 0.93 to 79.2 µM, 20.0 to 1600 pmol/min/mg protein, and 0.3 to 936 µl/min/mg protein. All kinetic parameters were calculated from 4-hydroxyatomoxetine (4-OH-ATX) formation. CYP2E1 and CYP3A contributed to 4-OH-ATX formation in livers with CYP2D6 intermediate and poor metabolizer status. In HLMs with lower CYP2D6 activity levels, 2-hydroxymethylatomoxetine (2-CH2OH-ATX) formation became a more predominant pathway of metabolism, which appeared to be catalyzed by CYP2B6. ATX biotransformation at clinically relevant plasma concentrations was characterized in a panel of pediatric HLM (n = 116) samples by evaluating primary metabolites. Competing pathways of ATX metabolism [N-desmethylatomoxetine (NDM-ATX) and 2-CH2OH-ATX formation] had increasing importance in livers with lesser CYP2D6 activity, but, overall ATX clearance was still compromised. Modeling ATX exposure to individualize therapy would require comprehensive knowledge of factors that affect CYP2D6 activity as well as an understanding of competing pathways, particularly for individuals with lower CYP2D6 activity.

Effects of salvianolic acid B and tanshinone IIA on the pharmacokinetics of losartan in rats by regulating the activities and expression of CYP3A4 and CYP2C9

Losartan (LST) is a common chemical drug used to treat high blood pressure and reduce the risk of stroke in certain people with heart disease. Danshen, prepared from the dried root and rhizome of Salvia miltiorrhiza Bunge, has been widely used for prevention and treatment of various cardiovascular and cerebrovascular diseases. There are more than 35 formulations containing Danshen indexed in the 2010 Chinese Pharmacopoeia, which are often combined with LST to treat cardiovascular and cerebrovascular diseases in the clinic. The effects of the two major components of Danshen, salvianolic acid B (SA-B) and tanshinone IIA (Tan IIA), on the pharmacokinetics of losartan and its metabolite, EXP3174, in rats were investigated by liquid chromatography coupled with mass spectrometry (LC-MS). Male Sprague-Dawley rats were randomly assigned to 3 groups: LST, LST+SA-B and LST+Tan IIA, and the main pharmacokinetic parameters were estimated after oral administration of LST, LST+SA-B and LST+Tan IIA. It was found that there are significant differences in the pharmacokinetic parameters among the three groups: Cmax, t1/2, AUC, AUMC in the LST+SA-B group was smaller than those in group LST, while larger in group LST+Tan IIA. Further, the effects of SA-B and Tan IIA on the metabolism of losartan was also investigated using rat liver microsomes in vitro. The results indicated that SA-B can induce the metabolism of LST, while Tan IIA can inhibit the metabolism of LST in rat liver microsomes in vitro by regulating activities of CYP450 enzymes. In addition, the effect of SA-B and Tan IIA on CYP3A4 and CYP2C9 expression was studied in Chang liver cells by western-blotting and Real-time PCR. It was concluded that the two components of Danshen, SA-B and Tan IIA have different influences on the metabolism of LST: SA-B can obviously speed up the metabolism of LST by inducing CYP3A4/CYP2C9 activities and expression, however, Tan IIA can slow down the metabolism of LST by inhibiting CYP3A4/CYP2C9 activities.

Linear Interaction Energy Based Prediction of Cytochrome P450 1A2 Binding Affinities with Reliability Estimation

Prediction of human Cytochrome P450 (CYP) binding affinities of small ligands, i.e., substrates and inhibitors, represents an important task for predicting drug-drug interactions. A quantitative assessment of the ligand binding affinity towards different CYPs can provide an estimate of inhibitory activity or an indication of isoforms prone to interact with the substrate of inhibitors. However, the accuracy of global quantitative models for CYP substrate binding or inhibition based on traditional molecular descriptors can be limited, because of the lack of information on the structure and flexibility of the catalytic site of CYPs. Here we describe the application of a method that combines protein-ligand docking, Molecular Dynamics (MD) simulations and Linear Interaction Energy (LIE) theory, to allow for quantitative CYP affinity prediction. Using this combined approach, a LIE model for human CYP 1A2 was developed and evaluated, based on a structurally diverse dataset for which the estimated experimental uncertainty was 3.3 kJ mol-1. For the computed CYP 1A2 binding affinities, the model showed a root mean square error (RMSE) of 4.1 kJ mol-1 and a standard error in prediction (SDEP) in cross-validation of 4.3 kJ mol-1. A novel approach that includes information on both structural ligand description and protein-ligand interaction was developed for estimating the reliability of predictions, and was able to identify compounds from an external test set with a SDEP for the predicted affinities of 4.6 kJ mol-1 (corresponding to 0.8 pKi units).

Modeling of interactions between xenobiotics and cytochrome P450 (CYP) enzymes

The adverse effects to humans and environment of only few chemicals are well known. Absorption, distribution, metabolism, and excretion (ADME) are the steps of pharmaco/toxicokinetics that determine the internal dose of chemicals to which the organism is exposed. Of all the xenobiotic-metabolizing enzymes, the cytochrome P450 (CYP) enzymes are the most important due to their abundance and versatility. Reactions catalyzed by CYPs usually turn xenobiotics to harmless and excretable metabolites, but sometimes an innocuous xenobiotic is transformed into a toxic metabolite. Data on ADME and toxicity properties of compounds are increasingly generated using in vitro and modeling (in silico) tools. Both physics-based and empirical modeling approaches are used. Numerous ligand-based and target-based as well as combined modeling methods have been employed to evaluate determinants of CYP ligand binding as well as predicting sites of metabolism and inhibition characteristics of test molecules. In silico prediction of CYP–ligand interactions have made crucial contributions in understanding (1) determinants of CYP ligand binding recognition and affinity; (2) prediction of likely metabolites from substrates; (3) prediction of inhibitors and their inhibition potency. Truly predictive models of toxic outcomes cannot be created without incorporating metabolic characteristics; in silico methods help producing such information and filling gaps in experimentally derived data. Currently modeling methods are not mature enough to replace standard in vitro and in vivo approaches, but they are already used as an important component in risk assessment of drugs and other chemicals.

Interactions between CYP3A4 and Dietary Polyphenols

The human cytochrome P450 enzymes (P450s) catalyze oxidative reactions of a broad spectrum of substrates and play a critical role in the metabolism of xenobiotics, such as drugs and dietary compounds. CYP3A4 is known to be the main enzyme involved in the metabolism of drugs and most other xenobiotics. Dietary compounds, of which polyphenolics are the most studied, have been shown to interact with CYP3A4 and alter its expression and activity. Traditionally, the liver was considered the prime site of CYP3A-mediated first-pass metabolic extraction, but in vitro and in vivo studies now suggest that the small intestine can be of equal or even greater importance for the metabolism of polyphenolics and drugs. Recent studies have pointed to the role of gut microbiota in the metabolic fate of polyphenolics in human, suggesting their involvement in the complex interactions between dietary polyphenols and CYP3A4. Last but not least, all the above suggests that coadministration of drugs and foods that are rich in polyphenols is expected to stimulate undesirable clinical consequences. This review focuses on interactions between dietary polyphenols and CYP3A4 as they relate to structural considerations, food-drug interactions, and potential negative consequences of interactions between CYP3A4 and polyphenols.

An improved large-scale prediction model of CYP1A2 inhibitors by using combined fragment descriptors

Combined fragment descriptors are used to develop a predictive SVM model for virtual screening of CYP1A2 inhibitors.

A Comparison of the In Vitro Inhibitory Effects of Thelephoric Acid and SKF-525A on Human Cytochrome P450 Activity

Thelephoric acid is an antioxidant produced by the hydrolysis of polyozellin, which is isolated from Polyozellus multiplex. In the present study, the inhibitory effects of polyozellin and thelephoric acid on 9 cytochrome P450 (CYP) family members (CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and CYP3A4) were examined in pooled human liver microsomes (HLMs) using a cocktail probe assay. Polyozellin exhibited weak inhibitory effects on the activities of all 9 CYPs examined, whereas thelephoric acid exhibited dose- and time-dependent inhibition of all 9 CYP isoforms (IC50 values, 3.2-33.7 μM). Dixon plots of CYP inhibition indicated that thelephoric acid was a competitive inhibitor of CYP1A2 and CYP3A4. In contrast, thelephoric acid was a noncompetitive inhibitor of CYP2D6. Our findings indicate that thelephoric acid may be a novel, non-specific CYP inhibitor, suggesting that it could replace SKF-525A in inhibitory studies designed to investigate the effects of CYP enzymes on the metabolism of given compounds.

Functional characterization of cytochromes P450 2B from the desert woodrat Neotoma lepida

Mammalian detoxification processes have been the focus of intense research, but little is known about how wild herbivores process plant secondary compounds, many of which have medicinal value or are drugs. cDNA sequences that code for three enzymes of the cytochrome P450 (CYP) 2B subfamily, here termed 2B35, 2B36, and 2B37 have been recently identified from a wild rodent, the desert woodrat (Malenke et al., 2012). Two variant clones of each enzyme were engineered to increase protein solubility and to facilitate purification, as reported for CYP2B enzymes from multiple species. When expressed in Escherichia coli each of the woodrat proteins gave the characteristic maximum at 450nm in a reduced carbon monoxide difference spectrum but generally expressed at lower levels than rat CYP2B1. Two enzymes, 2B36 and 2B37, showed dealkylation activity with the model substrates 7-ethoxy-4-(trifluoromethyl)coumarin and 7-benzyloxyresorufin, whereas 2B35 was inactive. Binding of the monoterpene (+)-α-pinene produced a Type I shift in the absorbance spectrum of each enzyme. Mutation of 2B37 at residues 114, 262, or 480, key residues governing ligand interactions with other CYP2B enzymes, did not significantly change expression levels or produce the expected functional changes. In summary, two catalytic and one ligand-binding assay are sufficient to distinguish among CYP2B35, 2B36, and 2B37. Differences in functional profiles between 2B36 and 2B37 are partially explained by changes in substrate recognition site residue 114, but not 480. The results advance our understanding of the mechanisms of detoxification in wild mammalian herbivores and highlight the complexity of this system.

Pharmacological potential of biogenic amine-polyamine interactions beyond neurotransmission

Histamine, serotonin and dopamine are biogenic amines involved in intercellular communication with multiple effects on human pathophysiology. They are products of two highly homologous enzymes, histidine decarboxylase and l-aromatic amino acid decarboxylase, and transmit their signals through different receptors and signal transduction mechanisms. Polyamines derived from ornithine (putrescine, spermidine and spermine) are mainly involved in intracellular effects related to cell proliferation and death mechanisms. This review summarizes structural and functional evidence for interactions between components of all these amine metabolic and signalling networks (decarboxylases, transporters, oxidases, receptors etc.) at cellular and tissue levels, distinct from nervous and neuroendocrine systems, where the crosstalk among these amine-related components can also have important pathophysiological consequences. The discussion highlights aspects that could help to predict and discuss the effects of intervention strategies.

Redox activation of Nrf2 & NF-κB: a double end sword?

Moderate concentrations of reactive oxygen species (ROS) are produced by diverse sources under physiological conditions. At such low levels, these molecules may act as upstream mediators of relevant signaling pathways; however an increase in their concentration with respect to the antioxidant system activity, changes their redox signaling function into a deleterious role. Thus, cell health depends, at least in part, on redox balance. This review includes global aspects of oxygen chemistry, ROS generation, antioxidant system, and redox signaling. It is also focused on the description of two relevant redox-sensitive transcription factors: nuclear factor erythroid 2-related factor 2 (Nrf2), which may be a potential target to confer cell protection, and nuclear factor κB (NF-κB), which is involved in deleterious effects in the cell. Finally, recent findings on the interplay between both factors for the development of different pathologies are discussed.

Structural and thermodynamic basis of (+)-α-pinene binding to human cytochrome P450 2B6

Despite recent advances in atomic-level understanding of drug and inhibitor interactions with human cytochromes P450, the decades-old questions of chemical and structural determinants of hydrocarbon binding are still unanswered. (+)-α-Pinene is a monoterpene hydrocarbon that is widely distributed in the environment and a potent P450 2B inhibitor. Therefore, a combined biophysical and structural analysis of human P450 2B6 interactions with (+)-α-pinene was undertaken to elucidate the basis of the very high affinity binding. Binding of (+)-α-pinene to the P450 active site was demonstrated by a Type I spectral shift. Thermodynamics of ligand binding were explored using isothermal titration calorimetry and compared to those of P450 2A6, which is much less flexible than 2B6 based on comparison of multiple X-ray crystal structures. Consistent with expectation, entropy is the major driving force for hydrocarbon binding to P450 2A6, as evidenced by the calorimetric results. However, formation of the 2B6-(+)-α-pinene complex has a significant enthalpic component. A 2.0 Å resolution crystal structure of this enzyme-ligand complex reveals that the highly plastic 2B6 utilizes previously unrecognized rearrangements of protein motifs. The results indicate that the specific components of enthalpic contribution to ligand binding are closely tied to the degree of enzyme flexibility.

Predicting CYP2C19 catalytic parameters for enantioselective oxidations using artificial neural networks and a chirality code

Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (k(cat), K(m), and k(cat)/K(m)), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (k(cat) and K(m)) were more consistent with experimental values than those for catalytic efficiency (k(cat)/K(m)). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds.

Development of flavone propargyl ethers as potent and selective inhibitors of cytochrome P450 enzymes 1A1 and 1A2

Naturally occurring flavonoids are known to be metabolized by several cytochrome P450 enzymes including P450s 1A1, 1A2, 1B1, 2C9, 3A4, and 3A5. In general flavonoids can act as substrates, inducers, and/or inhibitors of P450 enzymes. The position of the substituents on the flavone backbone has been shown to impact the biological activity against P450 enzymes. To explore the effect of a propargyl ether substitution on flavones and flavanones, 2´-flavone propargyl ether (2´-PF), 3´-flavone propargyl ether (3´-PF), 4´-flavone propargyl ether (4´-PF), 5-flavone propargyl ether (5-PF), 6-flavone propargyl ether (6-PF), 7-flavone propargyl ether (7-PF), 6-flavanone propargyl ether (6-PFN), and 7- flavanone propargyl ether (7-PFN) were synthesized. All of the newly synthesized compounds and the parent hydroxy flavones were tested for both direct inhibition and mechanism-based inhibition of cytochrome P450 enzymes 1A1, 1A2, 2A6, and 2B1. The flavone propargyl ether derivatives were found to be more potent inhibitors of P450s 1A1 and 1A2. None of the flavones and flavanones in our study showed any inhibition of P450 2A6. Only 2´-PF and 6-PFN inhibited P450 2B1. 3´-PF showed direct inhibition of P450 1A1 with the highest observed potency of 0.02 µM, in addition to its ability to cause mechanism-based inhibition with KI and kinactivation values of 0.24 µM and 0.09 min-1 for this enzyme. 7- Hydroxy flavone also exhibited mechanism-based inhibition of P450 1A1 with KI and kinactivation values of 2.43 µM and 0.115 min-1. Docking studies and QSAR studies on P450 enzymes 1A1 and 1A2 were performed which revealed important insights into the nature of binding of these molecules and provided us with good QSAR models that can be used to design new flavone derivatives.