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

Systematic Review of Naturally Derived Substances That Act as Inhibitors of the Nicotine Metabolizing Enzyme Cytochrome P450 2A6

Tobacco smoking has been highlighted as a major health challenge in modern societies. Despite not causing death directly, smoking has been associated with several health issues, such as cardiovascular diseases, respiratory disorders, and several cancer types. Moreover, exposure to nicotine during pregnancy has been associated with adverse neurological disorders in babies. Nicotine Replacement Therapy (NRT) is the most common strategy employed for smoking cessation, but despite its widespread use, NRT presents with low success and adherence rates. This is attributed partially to the rate of nicotine metabolism by cytochrome P450 2A6 (CYP2A6) in each individual. Nicotine addiction is correlated with the high rate of its metabolism, and thus, novel strategies need to be implemented in NRT protocols. Naturally derived products are a cost-efficient and rich source for potential inhibitors, with the main advantages being their abundance and ease of isolation. This systematic review aims to summarize the natural products that have been identified as CYP2A6 inhibitors, validated through in vitro and/or in vivo assays, and could be implemented as nicotine metabolism inhibitors. The scope is to present the different compounds and highlight their possible implementation in NRT strategies. Additionally, this information would provide valuable insight regarding CYP2A6 inhibitors, that can be utilized in drug development via the use of in silico methodologies and machine-learning models to identify new potential lead compounds for optimization and implementation in NRT regimes.

Nicotine alleviates MPTP-induced nigrostriatal damage through modulation of JNK and ERK signaling pathways in the mice model of Parkinson's disease

Introduction: Nicotine (Nic) has previously been proven to reduce neurodegeneration in the models of Parkinson's disease (PD). The present study is intended to investigate the detailed mechanisms related to the potential neuroprotective effects of Nic in vivo. Methods: We established a PD model using 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced C57BL6 mice (25 mg/kg/d, 5 d, i.p.) to investigate the neuropharmacological modulation of Nic pretreatment (2.5 mg/kg/d, 5 d, i.p., 30 min before MPTP injection) from the perspectives of neurobehavioral assessment, the pathological alterations, microglial cell inflammation and MAPK signaling pathways in specific brain regions. Results: The open field test, elevated plus maze, rotarod and traction test suggested that Nic pretreatment could significantly improve MPTP-induced motor impairment and had an anxiolytic effect. Nic was found to improve neuroapoptosis, enhance tyrosine hydroxylase activity, and reduce the accumulation of the phosphorylated α-synuclein in the substantia nigra and striatal regions of PD mice by TUNEL and immunohistochemical assays. Immuno-fluorescent method for labeling Iba1 and CD68 indicated that Nic remarkably alleviates the activation of microglia which represents the M1 polarization state in the mice brain under MPTP stimulation. No significant difference in the expression of p38/MAPK pathway was found in the nigrostriatal regions, while Nic could significantly inhibit the elevated p-JNK/JNK ratio and increase the declined p-ERK/ERK ratio in the substantia nigra of MPTP-exposed brains, which was further confirmed by the pretreatment of CYP2A5 inhibitor to decline the metabolic activity of Nic. Discussion: The molecular signaling mechanism by which Nic exerts its neuroprotective effects against PD may be achieved by regulating the JNK and ERK signaling pathways in the nigra-striatum related brain regions.

Compounds with Antiviral, Anti-Inflammatory and Anticancer Activity Identified in Wine from Hungary's Tokaj Region via High Resolution Mass Spectrometry and Bioinformatics Analyses

(1) Background: Wine contains a variety of molecules with potential beneficial effects on human health. Our aim was to examine the wine components with high-resolution mass spectrometry including high-resolution tandem mass spectrometry in two wine types made from grapes with or without the fungus Botrytis cinerea, or "noble rot". (2) For LC-MS/MS analysis, 12 wine samples (7 without and 5 with noble rotting) from 4 different wineries were used and wine components were identified and quantified. (3) Results: 288 molecules were identified in the wines and the amount of 169 molecules was statistically significantly different between the two wine types. A database search was carried out to find the molecules, which were examined in functional studies so far, with high emphasis on molecules with antiviral, anti-inflammatory and anticancer activities. (4) Conclusions: A comprehensive functional dataset related to identified wine components is also provided highlighting the importance of components with potential health benefits.

Increased Intestinal Absorption of Vitamin U in Steamed Graviola Leaf Extract Activates Nicotine Detoxification

Graviola leaves contain much vitamin U (vit U), but their sensory quality is not good enough for them to be developed as food ingredients. Addition of excipient natural ingredients formulated alongside vit U as active ingredients could enhance not only its sensory quality but also its bioavailability. The objectives of this study were to measure the bioaccessibility and intestinal cellular uptake of bioactive components, including rutin, kaempferol-rutinoside, and vit U, from steamed extract of graviola leaves (SGV) and SGV enriched with kale extract (SGK), and to examine how much they can detoxify nicotine in HepG2 cells. The bioaccessibility of vit U from SGV and SGK was 82.40% and 68.03%, respectively. The cellular uptake of vit U in SGK by Caco-2 cells was higher than that in SGV. Cotinine content converted from nicotine in HepG2 cells for 120 min was 0.22 and 0.25 μg/mg protein in 50 μg/mL of SGV and SGK, respectively, which were 2.86 and 3.57 times higher than the no-treatment control. SGK treatment of HepG2 cells upregulated CYP2A6 three times as much as did that of SGV. Our results suggest that graviola leaf extract enriched with excipient ingredients such as kale could improve vit U absorption and provide a natural therapy for detoxifying nicotine.

Improving Detection of Arrhythmia Drug-Drug Interactions in Pharmacovigilance Data through the Implementation of Similarity-Based Modeling

Identification of Drug-Drug Interactions (DDIs) is a significant challenge during drug development and clinical practice. DDIs are responsible for many adverse drug effects (ADEs), decreasing patient quality of life and causing higher care expenses. DDIs are not systematically evaluated in pre-clinical or clinical trials and so the FDA U. S. Food and Drug Administration relies on post-marketing surveillance to monitor patient safety. However, existing pharmacovigilance algorithms show poor performance for detecting DDIs exhibiting prohibitively high false positive rates. Alternatively, methods based on chemical structure and pharmacological similarity have shown promise in adverse drug event detection. We hypothesize that the use of chemical biology data in a post hoc analysis of pharmacovigilance results will significantly improve the detection of dangerous interactions. Our model integrates a reference standard of DDIs known to cause arrhythmias with drug similarity data. To compare similarity between drugs we used chemical structure (both 2D and 3D molecular structure), adverse drug side effects, chemogenomic targets, drug indication classes, and known drug-drug interactions. We evaluated the method on external reference standards. Our results showed an enhancement of sensitivity, specificity and precision in different top positions with the use of similarity measures to rank the candidates extracted from pharmacovigilance data. For the top 100 DDI candidates, similarity-based modeling yielded close to twofold precision enhancement compared to the proportional reporting ratio (PRR). Moreover, the method helps in the DDI decision making through the identification of the DDI in the reference standard that generated the candidate.

Inhibitory effects and oxidation of 6-methylcoumarin, 7-methylcoumarin and 7-formylcoumarin via human CYP2A6 and its mouse and pig orthologous enzymes

1. Information about the metabolism of compounds is essential in drug discovery and development, risk assessment of chemicals and further development of predictive methods. 2. In vitro and in silico methods were applied to evaluate the metabolic and inhibitory properties of 6-methylcoumarin, 7-methylcoumarin and 7-formylcoumarin with human CYP2A6, mouse CYP2A5 and pig CYP2A19. 3. 6-Methylcoumarin was oxidized to fluorescent 7-hydroxy-6-methylcoumarin by CYP2A6 (Km: 0.64-0.91 µM; Vmax: 0.81-0.89 min(-1)) and by CYP2A5 and CYP2A19. The reaction was almost completely inhibited at 10 µM 7-methylcoumarin in liver microsomes of human and mouse, but in pig only 40% inhibition was obtained with the anti-CYP2A5 antibody or with methoxsalen and pilocarpine. 7-Methylcoumarin was a mechanism-based inhibitor for CYP2A6, but not for the mouse and pig enzymes. 7-Formylcoumarin was a mechanism-based inhibitor for CYP2As of all species. 4. Docking and molecular dynamics simulations of 6-methylcoumarin and 7-methylcoumarin in the active sites of CYP2A6 and CYP2A5 demonstrated a favorable orientation of the 7-position of 6-methylcoumarin towards the heme moiety. Several orientations of 7-methylcoumarin were possible in CYP2A6 and CYP2A5. 5. These results indicate that the active site of CYP2A6 has unique interaction properties for ligands and differs in this respect from CYP2A5 and CYP2A19.

Similarity-based modeling in large-scale prediction of drug-drug interactions

Drug-drug interactions (DDIs) are a major cause of adverse drug effects and a public health concern, as they increase hospital care expenses and reduce patients' quality of life. DDI detection is, therefore, an important objective in patient safety, one whose pursuit affects drug development and pharmacovigilance. In this article, we describe a protocol applicable on a large scale to predict novel DDIs based on similarity of drug interaction candidates to drugs involved in established DDIs. The method integrates a reference standard database of known DDIs with drug similarity information extracted from different sources, such as 2D and 3D molecular structure, interaction profile, target and side-effect similarities. The method is interpretable in that it generates drug interaction candidates that are traceable to pharmacological or clinical effects. We describe a protocol with applications in patient safety and preclinical toxicity screening. The time frame to implement this protocol is 5-7 h, with additional time potentially necessary, depending on the complexity of the reference standard DDI database and the similarity measures implemented.

Interactions of inhibitor molecules with the human CYP2E1 enzyme active site

CYP2E1 is an important enzyme oxidizing ethanol as well as several drugs and other xenobiotics in the human liver. We determined the inhibition potency of structurally diverse compounds against human CYP2E1, and analyzed their interactions with the enzyme active site by molecular docking and 3D-QSAR approaches. The IC(50) values for the tested compounds varied from 1.4 μM for γ-undecanolactone to over 46 mM for glycerol. This data set was used to create a comparative molecular field analysis (CoMFA) model. The most important interactions for binding of inhibitors were identified by docking and key features for inhibitors were characterized via the COMFA model. Since the active site of CYP2E1 is flexible, long chain lactones and alkyl alcohols fitted best into the larger open form while the other compounds fitted better in the smaller closed form of the active site. Electrostatic interactions near the Thr(303) residue proved to be important for inhibition of the enzyme activity. Thus, docking analysis and the predictive CoMFA model proved to be efficient tools for revealing interactions between inhibiting compounds and CYP2E1. These approaches can be used to analyze CYP2E1-mediated metabolism and drug interactions in the development of new chemical entities.

Insights on cytochrome p450 enzymes and inhibitors obtained through QSAR studies

The cytochrome P450 (CYP) superfamily of heme enzymes play an important role in the metabolism of a large number of endogenous and exogenous compounds, including most of the drugs currently on the market. Inhibitors of CYP enzymes have important roles in the treatment of several disease conditions such as numerous cancers and fungal infections in addition to their critical role in drug-drug interactions. Structure activity relationships (SAR), and three-dimensional quantitative structure activity relationships (3D-QSAR) represent important tools in understanding the interactions of the inhibitors with the active sites of the CYP enzymes. A comprehensive account of the QSAR studies on the major human CYPs 1A1, 1A2, 1B1, 2A6, 2B6, 2C9, 2C19, 2D6, 2E1, 3A4 and a few other CYPs are detailed in this review which will provide us with an insight into the individual/common characteristics of the active sites of these enzymes and the enzyme-inhibitor interactions.

Prediction of pharmacokinetic parameters

In silico tools specifically developed for prediction of pharmacokinetic parameters are of particular interest to pharmaceutical industry because of the high potential of discarding inappropriate molecules during an early stage of drug development itself with consequent saving of vital resources and valuable time. The ultimate goal of the in silico models of absorption, distribution, metabolism, and excretion (ADME) properties is the accurate prediction of the in vivo pharmacokinetics of a potential drug molecule in man, whilst it exists only as a virtual structure. Various types of in silico models developed for successful prediction of the ADME parameters like oral absorption, bioavailability, plasma protein binding, tissue distribution, clearance, half-life, etc. have been briefly described in this chapter.

Identification of novel CYP2A6 inhibitors by virtual screening

The human CYP2A6 enzyme metabolises several xenobiotics including nicotine, the addictive component in tobacco. Reduced activity of CYP2A6, either for genetic reasons or by administering inhibitors of CYP2A6, reduces tobacco smoking. The aim was to design novel inhibitors of CYP2A6 using 3D-QSAR analysis combined with virtual screening. A 3D-QSAR model was utilised to identify the most important features of the inhibitors, and this knowledge was used to design inhibitors for CYP2A6. Chemical database screening yielded several potent inhibitor candidates such as alkylamine derivatives (compound no. 5, IC(50)=0.1 μM) and 1-benzothiophene-3-carbaldehyde that can be used as lead compounds in the development of drugs for smoking reduction therapy.

Classification of cytochrome P450 inhibitors with respect to binding free energy and pIC50 using common molecular descriptors

Virtual screening of chemical libraries following experimental assays of drug candidates is a common procedure in structure based drug discovery. However, the relationship between binding free energies and biological activities (pIC50) of drug candidates is still an unsolved issue that limits the efficiency and speed of drug development processes. In this study, the relationship between them is investigated based on a common molecular descriptor set for human cytochrome P450 enzymes (CYPs). CYPs play an important role in drug-drug interactions, drug metabolism, and toxicity. Therefore, in silico prediction of CYP inhibition by drug candidates is one of the major considerations in drug discovery. The combination of partial least-squares regression (PLSR) and a variety of classification algorithms were employed by considering this relationship as a classification problem. Our results indicate that PLSR with classification is a powerful tool to predict more than one output such as binding free energy and pIC50 simultaneously. PLSR with mixed-integer linear programming based hyperboxes predicts the binding free energy and pIC50 with a mean accuracy of 87.18% (min: 81.67% max: 97.05%) and 88.09% (min: 79.83% max: 92.90%), respectively, for the cytochrome p450 superfamily using the common 6 molecular descriptors with a 10-fold cross-validation.

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.

Identification of inhibitors of the nicotine metabolising CYP2A6 enzyme--an in silico approach

The compulsive nature of tobacco use is attributable to nicotine addiction. Nicotine is eliminated by metabolism through the cytochrome P450 2A6 (CYP2A6) enzyme in liver. Inhibition of CYP2A6 by chemical compounds may represent a potential supplement to anti-smoking therapy. The purpose of this study was to rationally design potent inhibitors of CYP2A6. 3D-QSAR models were constructed to find out which structural characteristics are important for inhibition potency. Specifically located hydrophobic and hydrogen donor features were found to affect inhibition potency. These features were used in virtual screening of over 60,000 compounds in the Maybridge chemical database. A total of 22 candidate molecules were selected and tested for inhibition potency. Four of these were potent and selective CYP2A6 inhibitors with IC(50) values lower than 1 muM. They represent novel structures of CYP2A6 inhibitors, especially N1-(4-fluorophenyl)cyclopropane-1-carboxamide. This compound can be used as a lead in the design of CYP2A6 inhibitor drugs to combat nicotine addiction.

New potent and selective cytochrome P450 2B6 (CYP2B6) inhibitors based on three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis

BACKGROUND AND PURPOSE

The cytochrome P450 2B6 (CYP2B6) enzyme metabolises a number of clinically important drugs. Drug-drug interactions resulting from inhibition or induction of CYP2B6 activity may cause serious adverse effects. The aims of this study were to construct a three-dimensional structure-activity relationship (3D-QSAR) model of the CYP2B6 protein and to identify novel potent and selective inhibitors of CYP2B6 for in vitro research purposes.

EXPERIMENTAL APPROACH

The inhibition potencies (IC(50) values) of structurally diverse chemicals were determined with recombinant human CYP2B6 enzyme. Two successive models were constructed using Comparative Molecular Field Analysis (CoMFA).

KEY RESULTS

Three compounds proved to be very potent and selective competitive inhibitors of CYP2B6 in vitro (IC(50)<1 microM): 4-(4-chlorobenzyl)pyridine (CBP), 4-(4-nitrobenzyl)pyridine (NBP), and 4-benzylpyridine (BP). A complete inhibition of CYP2B6 activity was achieved with 0.1 microM CBP, whereas other CYP-related activities were not affected. Forty-one compounds were selected for further testing and construction of the final CoMFA model. The created CoMFA model was of high quality and predicted accurately the inhibition potency of a test set (n=7) of structurally diverse compounds.

CONCLUSIONS AND IMPLICATIONS

Two CoMFA models were created which revealed the key molecular characteristics of inhibitors of the CYP2B6 enzyme. The final model accurately predicted the inhibitory potencies of several structurally unrelated compounds. CBP, BP and NBP were identified as novel potent and selective inhibitors of CYP2B6 and CBP especially is a suitable inhibitor for in vitro screening studies.

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.

Cytochrome P450 (CYP) inhibition screening: Comparison of three tests

There are several different experimental systems for screening of in vitro inhibitory potency of drugs under development. In this study we compared three different types of cytochrome P450 (CYP) inhibition tests: the traditional single substrate assays, the fluorescent probe method with recombinant human CYPs, and a novel n-in-one technique. All major hepatic drug-metabolizing CYPs were included (1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4). Six compounds (sotalol, propranolol, citalopram, fluoxetine, oxazepam and diazepam) were selected for detailed comparisons. The IC50 values of each of these compounds were measured using the three assay types. The inhibitory potencies of these model drugs were generally within the same order of magnitude and followed similar inhibition profiles in all the assay types. Clinically observed inhibitory interactions, or lack thereof, were predictable with all three assays. Comparison of potencies of 'diagnostic' inhibitors revealed also some notable differences between the assays, especially regarding CYP2E1. The potency of inhibitors towards CYP3A4 was dependent on the substrate and reaction measured. Generally all three assays gave reasonably comparable results, although some unexplained differences were also noted.

Systematic Statistical Comparison of Comparative Molecular Similarity Indices Analysis Molecular Fields for Computer-Aided Lead Optimization

Comparative molecular similarity indices analysis (CoMSIA) is a 3D quantitative structure-activity relationship technique used to determine structural and electronic features influencing biological activity. This proves particularly useful for facilitating lead optimization projects. This study aimed to compare CoMSIA models produced using different subsets of the CoMSIA molecular fields (steric, electrostatic, hydrophobic, hydrogen-bond donor, and hydrogen-bond acceptor) in a systematic and statistically valid manner. A total of 23 data sets sourced from the literature were used to compare molecular field contribution and model predictivity using leave-one-out cross-validated R2 values. Predictive ability varied in a highly statistically significant manner depending on the set of CoMSIA molecular fields used. In general, the greater the number of CoMSIA molecular fields included in the analysis, the better the model predictivity was. There is great redundancy in the information contained in the different CoMSIA molecular fields. When all five CoMSIA molecular fields are included, the hydrophobic and electrostatic fields had the largest and the steric field the smallest contribution. Data sets were clustered into four groups on the basis of the utility of molecular field sets to generate predictive models.

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.

Functional interaction of nitrogenous organic bases with cytochrome P450: A critical assessment and update of substrate features and predicted key active-site elements steering the access, binding, and orientation of amines

The widespread use of nitrogenous organic bases as environmental chemicals, food additives, and clinically important drugs necessitates precise knowledge about the molecular principles governing biotransformation of this category of substrates. In this regard, analysis of the topological background of complex formation between amines and P450s, acting as major catalysts in C- and N-oxidative attack, is of paramount importance. Thus, progress in collaborative investigations, combining physico-chemical techniques with chemical-modification as well as genetic engineering experiments, enables substantiation of hypothetical work resulting from the design of pharmacophores or homology modelling of P450s. Based on a general, CYP2D6-related construct, the majority of prospective amine-docking residues was found to cluster near the distal heme face in the six known SRSs, made up by the highly variant helices B', F and G as well as the N-terminal portion of helix C and certain beta-structures. Most of the contact sites examined show a frequency of conservation < 20%, hinting at the requirement of some degree of conformational versatility, while a limited number of amino acids exhibiting a higher level of conservation reside close to the heme core. Some key determinants may have a dual role in amine binding and/or maintenance of protein integrity. Importantly, a series of non-SRS elements are likely to be operative via long-range effects. While hydrophobic mechanisms appear to dominate orientation of the nitrogenous compounds toward the iron-oxene species, polar residues seem to foster binding events through H-bonding or salt-bridge formation. Careful uncovering of structure-function relationships in amine-enzyme association together with recently developed unsupervised machine learning approaches will be helpful in both tailoring of novel amine-type drugs and early elimination of potentially toxic or mutagenic candidates. Also, chimeragenesis might serve in the construction of more efficient P450s for activation of amine drugs and/or bioremediation.

A comprehensive view of polyamine and histamine metabolism to the light of new technologies

Polyamines and histamine are biogenic amines with multiple biological roles. In spite of the evidence for the involvement of both polyamines and histamine metabolism impairment in several highly prevalent pathological conditions, multiple questions concerning the molecular processes behind these effects remain to be elucidated. More comprehensive and systemic studies integrating molecular biology, biophysical and bioinformatics tools could contribute to accelerate the advances in this research area. This review is designed to underscore the main questions to be answered in polyamine and histamine research and how these new systemic approaches could help to find these answers.

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 vitroscreening of drug metabolism during drug development: can we trust the predictions?

Due to the importance of drug metabolism for drug action, side effects, interactions and interindividual differences, in vitro assays of drug metabolism are widely employed during drug development. Validation of the in vitro systems is still in a rather elementary stage, but some tentative conclusions about their performance for predicting various important in vivo characteristics of drugs can be attempted. So far, prediction of drug-drug interactions on the basis of in vitro screens has been advanced to a relatively reliable level. Prediction of other important characteristics, such as metabolic stability and consequent half-life and dosage schedule, or induction potential, is less reliable. Although metabolite profiles and participating enzymes are predicted quite accurately with advanced analytical techniques, an important problem here is the lack of reliable methods to detect reactive metabolites or products, which may be of significance regarding toxicity.