In silico toxicology in its broadest sense means “anything that we can do with a computer in toxicology.” Many different types of in silico methods have been developed to characterize and predict toxic outcomes in humans and environment. The term non-testing methods denote grouping approaches, structure–activity relationship, and expert systems. These methods are already used for regulatory purposes and it is anticipated that their role will be much more prominent in the near future. This Perspective will delineate the basic principles of non-testing methods and evaluate their role in current and future risk assessment of chemical compounds.

The human CYP2A gene subfamily consists of three members, CYP2A6 , CYP2A7 , and CYP2A13 . The CYP2A6 gene is highly polymorphic with approximately 40 annotated allelic variants. Individuals homozygous for some of these alleles have a total lack of CYP2A6 activity. The CYP2A6 protein is most abundant in liver and is expressed, although at much lower levels, in some other tissues, especially nasal mucosa. CYP2A6 differs from other human liver CYP forms in that it participates in the metabolism of very few currently used drugs. The two most relevant substrates for CYP2A6 are coumarin and nicotine. Coumarin is the marker substance for determining CYP2A6 activity both in vitro and in vivo. Approximately 80% of a nicotine dose is eliminated by CYP2A6, and there is a clear link between CYP2A6 genotypes, smoking behavior, and lung cancer risk.

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 (ADMET) 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.

In vivo methods, such as spectrophotometric, fluorometric, mass spectrometric, and radioactivity-based techniques. In fluorescence-based assays, the reaction produces a fluorescent product from a nonfluorescent substrate or vice versa. Fluorescence-based enzyme assays are usually highly sensitive and specific, allowing measurements on small specimens of tissues with low enzyme activities. Fluorescence assays are also amenable to miniaturization of the reaction mixtures and can thus be done in high throughput. 7-Hydroxycoumarin and its derivatives are widely used as fluorophores due to their desirable photophysical properties. They possess a large - conjugated system with electron-rich and charge transfer properties. This conjugated structure leads to applications of 7-hydroxycoumarins as fluorescent sensors for biological activities. We describe in this review historical highlights and current use of coumarins and their derivatives in evaluating activities of the major types of xenobiotic-metabolizing enzyme systems. Traditionally, coumarin substrates have been used to measure oxidative activities of cytochrome P450 (CYP) enzymes. For this purpose, profluorescent coumarins are very sensitive, but generally lack selectivity for individual CYP forms. With the aid of molecular modeling, we have recently described several new coumarin-based substrates for measuring activities of CYP and conjugating enzymes with improved selectivity.

Background: Tobacco smoking is a leading cause of preventable disease and death globally. Nicotine is the main addictive component in tobacco. Nicotine is eliminated from the body by biotransformation in the liver to inactive metabolites. This reaction is catalyzed by the cytochrome P450 2A6 (CYP2A6) enzyme. Administering chemical inhibitors of CYP2A6 has been shown to slow down the elimination of nicotine with consequent reduction in number of cigarettes smoked. We have systematically developed small molecule CYP2A6 inhibitors with good balance between potency and CYP selectivity. Objective: During this process we have noticed that many potent CYP2A6 inhibitors also inhibit other human liver CYP forms, most notably CYP1A2 and CYP2B6. This study aimed at defining common and distinct features of ligand binding to CYP1A2, CYP2A6 and CYP2B6 active sites. Methods: We used our previous chemical inhibitor databases to construct improved 3-dimensional quantitative structureactivity relationship (3D-QSAR) models for CYP1A2, CYP2A6 and CYP2B6. Results: Combined 3D-QSAR and docking procedures yielded precise information about the common and distinct interactions of inhibitors and the enzyme active sites. Positioning of hydrogen bond donor/acceptor atoms and the shape and volume of the compound defined the potency and specificity of inhibition. A novel potent and selective CYP1A2 inhibitor was found. Conclusion: This in silico approach will provide a means for very rapid and high throughput prediction of cross-inhibition of these three CYP enzymes.