Cytochromes P450: A Structure-Based Summary of Biotransformations Using Representative Substrates

Prediction of Cytochrome P450 Profiles of Environmental Chemicals with QSAR Models Built from Drug-like Molecules

The human cytochrome P450 (CYP) enzyme family is involved in the biotransformation of many xenobiotics. As part of the U.S. Tox21 Phase I effort, we profiled the CYP activity of approximately three thousand compounds, primarily those of environmental concern, against human CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4 isoforms in a quantitative high throughput screening (qHTS) format. In order to evaluate the extent to which computational models built from a drug-like library screened in these five CYP assays under the same conditions can accurately predict the outcome of an environmental compound library, five support vector machines (SVM) models built from over 17,000 drug-like compounds were challenged to predict the CYP activities of the Tox21 compound collection. Although a large fraction of the test compounds fall outside of the applicability domain (AD) of the models, as measured by k-nearest neighbor (k-NN) similarities, the predictions were largely accurate for CYP1A2, CYP2C9, and CYP3A4 ioszymes with area under the receiver operator characteristic curves (AUC-ROC) ranging between 0.82 and 0.84. The lower predictive power of the CYP2C19 model (AUC-ROC = 0.76) is caused by experimental errors and that of the CYP2D6 model (AUC-ROC = 0.76) can be rescued by rebalancing the training data. Our results demonstrate that decomposing molecules into atom types enhanced the coverage of the AD and that computational models built from drug-like molecules can be used to predict the ability of non-drug like compounds to interact with these CYPs.

Peroxisome proliferator-activated receptors in regulation of cytochromes P450: new way to overcome multidrug resistance?

Embryonic and tumour cells are able to protect themselves against various harmful compounds. In human pathology, this phenomenon exists in the form of multidrug resistance (MDR) that significantly deteriorates success of anticancer treatment. Cytochromes P450 (CYPs) play one of the key roles in the xenobiotic metabolism. CYP expression could contribute to resistance of cancer cells to chemotherapy. CYP epoxygenases (CYP2C and CYP2J) metabolize about 20% of clinically important drugs. Besides of drug metabolism, CYP epoxygenases and their metabolites play important role in embryos, normal body function, and tumors. They participate in angiogenesis, mitogenesis, and cell signaling. It was found that CYP epoxygenases are affected by peroxisome proliferator-activated receptor α (PPARα). Based on the results of current studies, we assume that PPARs ligands may regulate CYP2C and CYP2J and in some extent they may contribute to overcoming of MDR in patients with different types of tumours.

Defining the COX inhibitor selectivity of NSAIDs: implications for understanding toxicity

The hypothesis that the anti-inflammatory activity of NSAIDs derives from COX inhibition is well established. It also underpins the accepted mechanism of the gastrointestinal and renal toxicity of NSAIDs. However, in terms of NSAID-induced cardiovascular toxicity, is COX inhibition then guilty by association? Multiple experimental models of COX-1/COX-2 inhibition have enabled ranking of the relative inhibitory activity of NSAIDs. Inhibition is expressed as an IC(50) value and the index of COX selectivity as the ratio of the IC(50) value for COX-2 and COX-1. These data informed the 'imbalance hypothesis' that the cardiovascular risk of NSAIDs results from an imbalance in the detrimental actions of COX-1-derived thromboxane A(2) and the beneficial actions of COX-2-derived prostacyclin (PGI(2)). Data derived from in vitro models used to generate NSAID IC(50) values are discussed in the context of the difficulties in defining COX selectivity and hence understanding the toxicity of NSAIDs in current clinical use.

Computational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and software

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

A comparison of octanol-water partitioning between organic chemicals and their metabolites in mammals

Bioaccumulation models take various elimination and uptake processes into account, estimating rates from chemical lipophilicity, expressed as the octanol-water partition ratio (K(ow)). Here, we focussed on metabolism, which transforms parent compounds into usually more polar metabolites, thus enhancing elimination. The aim of this study was to quantify the change in lipophilicity of relevant organic pollutants undergoing various biotransformation reactions in mammals. We considered oxidation reactions catalyzed by three enzyme groups: cytochrome P450 (CYP), alcohol dehydrogenase (ADH), and aldehyde dehydrogenase (ALDH). Estimated logK(ow) values of a selected dataset of parent compounds were compared with the logK(ow) of their first metabolites. The logK(ow) decreased by a factor that varies between 0 and -2, depending on the metabolic pathway. For reactions mediated by CYP, the decrease in K(ow) was one order of magnitude for hydroxylated and epoxidated compounds and two orders of magnitude for dihydroxylated and sulphoxidated xenobiotics. On the other hand, no significant change in lipophilicity was observed for compounds N-hydroxylated by CYP and for alcohols and aldehydes metabolized by ADH and ALDH. These trends could be anticipated by the calculus method of logK(ow). Yet, they were validated using experimental logK(ow) values, when available. These relationships estimate the extent to which the elimination of pollutants is increased by biotransformation. Thus, the quantification of the K(ow) reduction can be considered as a first necessary step in an alternative approach to anticipate biotransformation rates, which are hard to estimate with existing methods.

Fast bundle algorithm for multiple-instance learning

We present a bundle algorithm for multiple-instance classification and ranking. These frameworks yield improved models on many problems possessing special structure. Multiple-instance loss functions are typically nonsmooth and nonconvex, and current algorithms convert these to smooth nonconvex optimization problems that are solved iteratively. Inspired by the latest linear-time subgradient-based methods for support vector machines, we optimize the objective directly using a nonconvex bundle method. Computational results show this method is linearly scalable, while not sacrificing generalization accuracy, permitting modeling on new and larger data sets in computational chemistry and other applications. This new implementation facilitates modeling with kernels.

RS-Predictor models augmented with SMARTCyp reactivities: robust metabolic regioselectivity predictions for nine CYP isozymes

RS-Predictor is a tool for creating pathway-independent, isozyme-specific, site of metabolism (SOM) prediction models using any set of known cytochrome P450 (CYP) substrates and metabolites. Until now, the RS-Predictor method was only trained and validated on CYP 3A4 data, but in the present study, we report on the versatility the RS-Predictor modeling paradigm by creating and testing regioselectivity models for substrates of the nine most important CYP isozymes. Through curation of source literature, we have assembled 680 substrates distributed among CYPs 1A2, 2A6, 2B6, 2C19, 2C8, 2C9, 2D6, 2E1, and 3A4, the largest publicly accessible collection of P450 ligands and metabolites released to date. A comprehensive investigation into the importance of different descriptor classes for identifying the regioselectivity mediated by each isozyme is made through the generation of multiple independent RS-Predictor models for each set of isozyme substrates. Two of these models include a density functional theory (DFT) reactivity descriptor derived from SMARTCyp. Optimal combinations of RS-Predictor and SMARTCyp are shown to have stronger performance than either method alone, while also exceeding the accuracy of the commercial regioselectivity prediction methods distributed by Optibrium and Schrödinger, correctly identifying a large proportion of the metabolites in each substrate set within the top two rank-positions: 1A2 (83.0%), 2A6 (85.7%), 2B6 (82.1%), 2C19 (86.2%), 2C8 (83.8%), 2C9 (84.5%), 2D6 (85.9%), 2E1 (82.8%), 3A4 (82.3%), and merged (86.0%). Comprehensive datamining of each substrate set and careful statistical analyses of the predictions made by the different models revealed new insights into molecular features that control metabolic regioselectivity and enable accurate prospective prediction of likely SOMs.

Metabolism of ibuprofen in zebrafish larvae

The application of zebrafish (Danio rerio) larvae to drug discovery assays and toxicity testing, and the occurrence of pharmaceuticals in the environment, has resulted in a need to understand the extent of the metabolic capabilities in the early life stages of this species. The aims of this study were to determine if zebrafish larvae absorbed, metabolized and excreted the model pharmaceutical, ibuprofen. Zebrafish larvae (72 h post fertilization) were exposed to ibuprofen (100 µg/L), (14)C-ibuprofen (100 µg/L) or a solvent control (ethanol) for ≤ 24 h. Water samples and larval extracts were assessed for metabolites of ibuprofen using liquid chromatography mass spectrometry (LC-MS-MS). Fractions from the separation of the samples treated with (14)C-ibuprofen were collected after chromatography and analysed for (14)C content by scintillation counting. Assessment of larval extracts and water samples by LC-MS-MS at 24 h resulted in the identification of hydroxy-ibuprofen in both water samples and larval extracts (8.2 and 0.08% of the total detected (14)C, respectively). A second putative hydroxy-ibuprofen moiety was also observed in water samples at trace levels, and a third minor unknown metabolite was detected in larval extracts only by scintillation counting (0.02% of the total (14)C detected). This study provides evidence that zebrafish larvae can metabolize and excrete ibuprofen in a manner known to be cytochrome P450-dependent in mammals, and the similarity to the mammalian pathway supports the use of this system as a surrogate in toxicity and efficacy screening.

RS-predictor: a new tool for predicting sites of cytochrome P450-mediated metabolism applied to CYP 3A4

This article describes RegioSelectivity-Predictor (RS-Predictor), a new in silico method for generating predictive models of P450-mediated metabolism for drug-like compounds. Within this method, potential sites of metabolism (SOMs) are represented as "metabolophores": A concept that describes the hierarchical combination of topological and quantum chemical descriptors needed to represent the reactivity of potential metabolic reaction sites. RS-Predictor modeling involves the use of metabolophore descriptors together with multiple-instance ranking (MIRank) to generate an optimized descriptor weight vector that encodes regioselectivity trends across all cases in a training set. The resulting pathway-independent (O-dealkylation vs N-oxidation vs Csp(3) hydroxylation, etc.), isozyme-specific regioselectivity model may be used to predict potential metabolic liabilities. In the present work, cross-validated RS-Predictor models were generated for a set of 394 substrates of CYP 3A4 as a proof-of-principle for the method. Rank aggregation was then employed to merge independently generated predictions for each substrate into a single consensus prediction. The resulting consensus RS-Predictor models were shown to reliably identify at least one observed site of metabolism in the top two rank-positions on 78% of the substrates. Comparisons between RS-Predictor and previously described regioselectivity prediction methods reveal new insights into how in silico metabolite prediction methods should be compared.

Developmental pharmacokinetics

The advances in developmental pharmacokinetics during the past decade reside with an enhanced understanding of the influence of growth and development on drug absorption, distribution, metabolism, and excretion (ADME). However, significant information gaps remain with respect to our ability to characterize the impact of ontogeny on the activity of important drug metabolizing enzymes, transporters, and other targets. The ultimate goal of rational drug therapy in neonates, infants, children, and adolescents resides with the ability to individualize it based on known developmental differences in drug disposition and action. The clinical challenge in achieving this is accounting for the variability in all of the contravening factors that influence pharmacokinetics and pharmacodynamics (e.g., genetic variants of ADME genes, different disease phenotypes, disease progression, and concomitant treatment). Application of novel technologies in the fields of pharmacometrics (e.g., in silico simulation of exposure-response relationships; disease progression modeling), pharmacogenomics and biomarker development (e.g., creation of pharmacodynamic surrogate endpoints suitable for pediatric use) are increasingly making integrated approaches for developmentally appropriate dose regimen selection possible.

SMARTCyp: A 2D Method for Prediction of Cytochrome P450-Mediated Drug Metabolism

SMARTCyp is an in silico method that predicts the sites of cytochrome P450-mediated metabolism of druglike molecules. The method is foremost a reactivity model, and as such, it shows a preference for predicting sites that are metabolized by the cytochrome P450 3A4 isoform. SMARTCyp predicts the site of metabolism directly from the 2D structure of a molecule, without requiring calculation of electronic properties or generation of 3D structures. This is a major advantage, because it makes SMARTCyp very fast. Other advantages are that experimental data are not a prerequisite to create the model, and it can easily be integrated with other methods to create models for other cytochrome P450 isoforms. Benchmarking tests on a database of 394 3A4 substrates show that SMARTCyp successfully identifies at least one metabolic site in the top two ranked positions 76% of the time. SMARTCyp is available for download at http://www.farma.ku.dk/p450.

Electron flow through metalloproteins

Electron transfers in photosynthesis and respiration commonly occur between metal-containing cofactors that are separated by large molecular distances. Understanding the underlying physics and chemistry of these biological electron transfer processes is the goal of much of the work in our laboratories. Employing laser flash-quench triggering methods, we have shown that 20A, coupling-limited Fe(II) to Ru(III) and Cu(I) to Ru(III) electron tunneling in Ru-modified cytochromes and blue copper proteins can occur on the microsecond timescale both in solutions and crystals; and, further, that analysis of these rates suggests that distant donor-acceptor electronic couplings are mediated by a combination of sigma and hydrogen bonds in folded polypeptide structures. Redox equivalents can be transferred even longer distances by multistep tunneling, often called hopping, through intervening amino acid side chains. In recent work, we have found that 20A hole hopping through an intervening tryptophan is several hundred-fold faster than single-step electron tunneling in a Re-modified blue copper protein.

Probing the cannabinoid CB1/CB2 receptor subtype selectivity limits of 1,2-diarylimidazole-4-carboxamides by fine-tuning their 5-substitution pattern

The cannabinoid CB(1)/CB(2) receptor subtype selectivity in the 1,2-diarylimidazole-4-carboxamide series was boosted by fine-tuning its 5-substitution pattern. The presence of the 5-methylsulfonyl group in 11 led to a greater than approximately 840-fold CB(1)/CB(2) subtype selectivity. The compounds 10, 18 and 19 were found more active than rimonabant (1) in a CB(1)-mediated rodent hypotension model after oral administration. Our findings suggest a limited brain exposure of the P-glycoprotein substrates 11, 12 and 21.

Mechanisms of multidrug resistance in cancer

The development of multidrug resistance (MDR) to chemotherapy remains a major challenge in the treatment of cancer. Resistance exists against every effective anticancer drug and can develop by numerous mechanisms including decreased drug uptake, increased drug efflux, activation of detoxifying systems, activation of DNA repair mechanisms, evasion of drug-induced apoptosis, etc. In the first part of this chapter, we briefly summarize the current knowledge on individual cellular mechanisms responsible for MDR, with a special emphasis on ATP-binding cassette transporters, perhaps the main theme of this textbook. Although extensive work has been done to characterize MDR mechanisms in vitro, the translation of this knowledge to the clinic has not been crowned with success. Therefore, identifying genes and mechanisms critical to the development of MDR in vivo and establishing a reliable method for analyzing clinical samples could help to predict the development of resistance and lead to treatments designed to circumvent it. Our thoughts about translational research needed to achieve significant progress in the understanding of this complex phenomenon are therefore discussed in a third section. The pleotropic response of cancer cells to chemotherapy is summarized in a concluding diagram.

Predicting activation enthalpies of cytochrome-P450-mediated hydrogen abstractions. 2. Comparison of semiempirical PM3, SAM1, and AM1 with a density functional theory method

Predicting the biotransformation of xenobiotics is important in the chemical and pharmaceutical industries, as well as in toxicology. Here, we extend and evaluate the rapid methodology of Korzekwa, Jones, and Gillette (J. Am. Chem. Soc. 1990, 112, 7042-7046 ) to estimate the activation enthalpy (DeltaH) of hydrogen-abstraction by cytochrome P450 (CYP) enzymes, using the p-nitrosophenoxy radical (PNPO) as a simple surrogate for the CYP active oxygen species. The DeltaH is estimated with a linear regression model using the reaction enthalpy and ionization energy (of the substrate radical) as predictor variables, calculated by semiempirical (SE) methods. While Korzekwa et al. used the SE method AM1, we applied PM3 and SAM1 and compared the results of the three methods. For 24 substrates, the AM1-, PM3-, and SAM1-derived regression models showed R(2) values of 0.89, 0.90, and 0.93, respectively, for the correlation between calculated and predicted DeltaH. Furthermore, we compared the DeltaH() calculated semiempirically using PNPO radical with density functional theory (DFT) B3LYP activation energies calculated by Olsen et al. (J. Med. Chem. 2006, 49, 6489-6499 ) using a more realistic iron-oxo-porphine model, and the results revealed limitations of the PNPO radical model. Thus, predictive models developed using SE predictors provide rapid and generally internally consistent results, but they should be interpreted and used cautiously.

Statin regulation of CYP3A4 and CYP3A5 expression

CYP3A4 and CYP3A5 are cytochrome P450 enzymes that are highly expressed in the liver and gut and metabolize endogenous compounds and xenobiotics. Statins are cholesterol-lowering drugs that are extensively metabolized by CYP3A4 and CYP3A5. The bioavailability of statins is affected by CYP3A4 and CYP3A5 and glucuronidases metabolism as well as uptake and efflux transporters that affect drug disposition. CYP3A4 and CYP3A5 variants have been demonstrated to influence the pharmacokinetics, efficacy and safety of statins. Inducers and inhibitors of CYP3A4 and CYP3A5 play an important role in reducing statin efficacy and increase the risk of adverse effects, respectively. Statins have been demonstrated to increase CYP3A expression in vitro, most likely because they are ligands to nuclear receptors (pregnane X receptor and constitutive androsterone receptor) that form heterodimers with retinoid X receptors and bind to responsive elements in the CYP3A4 and CYP3A5 promoter regions. This special report outlines the earlier studies on variability of response to statins owing to CYP3A variants and highlights findings on the induction of CYP3A4 and CYP3A5 expression by statins.

Cytochrome P450-dependent metabolism of PCB52 in the nematode Caenorhabditis elegans

There are 75 full length cytochrome P450 (CYP) genes known in the genome of the nematode Caenorhabditis elegans. The individual biological functions of the vast majority are mostly as yet unknown. Here the impact of cytochrome P450 isoforms on the metabolism of PCB52, an ortho-substituted, non-coplanar 2,2',5,5'-tetrachlorbiphenyl, as a model PCB of these worldwide distributed pollutants is investigated. Organic extracts, isolated from treated worms and analyzed by GC/MS, contained two obvious PCB52-derived products which have been identified as C3-, C4- and/or C6-hydroxy-PCB52. Moreover, these hydroxylase reactions strictly required the functional expression of the NADPH-dependent cytochrome P450 reductase (CPR) encoding emb-8 gene, which was recently shown to be essential also for several other cytochrome P450-dependent enzymatic reactions. Multiple and subsequent single RNAi-gene silencing experiments, as well as the use of cyp-mutant strains, identified members of the CYP-14A subfamily and CYP-34A6 as the major isoforms contributing to PCB52 metabolism in C. elegans. In the gene-silenced worms and mutants, the reduction in formation of hydroxylated products ranged from 55% to 78%. These results demonstrate for the first time that C. elegans shares with mammals the capacity to produce CYP-dependent PCB metabolites and may thus facilitate future studies on biotransformation.

In vitro metabolism study of a new nitrosyl ruthenium complex [Ru(NH.NHq)(terpy)NO]3+ nitric oxide donor using rat microsomes

A new nitrosyl ruthenium complex [Ru(NH.NHq)(terpy)NO](3+) nitric oxide donor was recently developed and due to its excellent vasodilator activity, it has been considered as a potential drug candidate. Drug metabolism is one of the main parameters that should be evaluated in the early drug development, so the biotransformation of this complex by rat hepatic microsomes was investigated. In order to perform the biotransformation study, a simple, sensitive and selective HPLC method was developed and carefully validated. The parameters evaluated in the validation procedure were: linearity, recovery, precision, accuracy, selectivity and stability. Except for the stability study, all the parameters evaluated presented values below the recommended by FDA guidelines. The stability study showed a time-dependent degradation profile. After method validation, the biotransformation study was accomplished and the kinetic parameters were determined. The biotransformation study obeyed the Michaelis-Menten kinetics. The V(max) and K(m) were, respectively, 0.1625+/-0.010 micromol/mg protein/min and 79.97+/-11.52 microM. These results indicate that the nitrosyl complex is metabolized by CYP450.

The role of biotransformation and bioactivation in toxicity

Biotransformation is essential to convert lipophilic chemicals to water-soluble and readily excretable metabolites. Formally, biotransformation reactions are classified into phase I and phase II reactions. Phase I reactions represent the introduction of functional groups, whereas phase II reactions are conjugations of such functional groups with endogenous, polar products. Biotransformation also plays an essential role in the toxicity of many chemicals due to the metabolic formation of toxic metabolites. These may be classified as stable but toxic products, reactive electrophiles, radicals, and reactive oxygen metabolites. The interaction of toxic products formed by biotransformation reactions with cellular macromolecules initiates the sequences resulting in cellular damage, cell death and toxicity.

On the impact of the molecule structure in chemical carcinogenesis

Cancer is as a highly complex and multifactorial disease responsible for the death of hundreds of thousands of people in the western countries every year. Since cancer is clonal and due to changes at the level of the genetic material, viruses, chemical mutagens and other exogenous factors such as short-waved electromagnetic radiation that alter the structure of DNA are among the principal causes. The focus of this present review lies on the influence of the molecular structure of two well-investigated chemical carcinogens from the group of polycyclic aromatic hydrocarbons (PAHs), benzo[a]pyrene (BP) and dibenzo[a,l]pyrene (DBP). Although there is only one additional benzo ring present in the latter compound, DBP exerts much stronger genotoxic and carcinogenic effects in certain tumor models as compared to BP. Actually, DBP has been identified as the most potent tumorigen among all carcinogenic PAHs tested to date. The genotoxic effects of both compounds investigated in mammalian cells in culture or in animal models are described. Comparison of enzymatic activation, DNA binding levels of reactive diol-epoxide metabolites, efficiency of DNA adduct repair and mutagenicity provides some clues on why this compound is about 100-fold more potent in inducing tumors than BP. The data published during the past 20 years support and strengthen the idea that compound-inherent physicochemical parameters, along with inefficient repair of certain kinds of DNA lesions formed upon metabolic activation, can be considered as strong determinants for high carcinogenic potency of a chemical.

Versatile capacity of shuffled cytochrome P450s for dye production

DNA family shuffling is a relatively new method of directed evolution used to create novel enzymes in order to improve their existing properties or to develop new features. This method of evolution in vitro has one basic requirement: a high similarity of initial parental sequences. Cytochrome P450 enzymes are relatively well conserved in their amino acid sequences. Members of the same family can have more than 40% of sequence identity at the protein level and are therefore good candidates for DNA family shuffling. These xenobiotic-metabolising enzymes have an ability to metabolise a wide range of chemicals and produce a variety of products including blue pigments such as indigo. By applying the specifically designed DNA family shuffling approach, catalytic properties of cytochrome P450 enzymes were further extended in the chimeric progeny to include a new range of blue colour formations. This mini-review evokes the possibility of exploiting directed evolution of cytochrome P450s and the novel enzymes created by DNA family shuffling for the production of new dyes.

Engineering and assaying of cytochrome P450 biocatalysts

Cytochrome P450s constitute a highly fascinating superfamily of enzymes which catalyze a broad range of reactions. They are essential for drug metabolism and promise industrial applications in biotechnology and biosensing. The constant search for cytochrome P450 enzymes with enhanced catalytic performances has generated a large body of research. This review will concentrate on two key aspects related to the identification and improvement of cytochrome P450 biocatalysts, namely the engineering and assaying of these enzymes. To this end, recent advances in cytochrome P450 development are reported and commonly used screening methods are surveyed.

Inhibition and induction of human cytochrome P450 enzymes: current status

Variability of drug metabolism, especially that of the most important phase I enzymes or cytochrome P450 (CYP) enzymes, is an important complicating factor in many areas of pharmacology and toxicology, in drug development, preclinical toxicity studies, clinical trials, drug therapy, environmental exposures and risk assessment. These frequently enormous consequences in mind, predictive and pre-emptying measures have been a top priority in both pharmacology and toxicology. This means the development of predictive in vitro approaches. The sound prediction is always based on the firm background of basic research on the phenomena of inhibition and induction and their underlying mechanisms; consequently the description of these aspects is the purpose of this review. We cover both inhibition and induction of CYP enzymes, always keeping in mind the basic mechanisms on which to build predictive and preventive in vitro approaches. Just because validation is an essential part of any in vitro-in vivo extrapolation scenario, we cover also necessary in vivo research and findings in order to provide a proper view to justify in vitro approaches and observations.