Metabolic activation of the phenothiazine antipsychotics chlorpromazine and thioridazine to electrophilic iminoquinone species in human liver microsomes and recombinant P450s

Predicting non-chemotherapy drug-induced agranulocytosis toxicity through ensemble machine learning approaches

Agranulocytosis, induced by non-chemotherapy drugs, is a serious medical condition that presents a formidable challenge in predictive toxicology due to its idiosyncratic nature and complex mechanisms. In this study, we assembled a dataset of 759 compounds and applied a rigorous feature selection process prior to employing ensemble machine learning classifiers to forecast non-chemotherapy drug-induced agranulocytosis (NCDIA) toxicity. The balanced bagging classifier combined with a gradient boosting decision tree (BBC + GBDT), utilizing the combined descriptor set of DS and RDKit comprising 237 features, emerged as the top-performing model, with an external validation AUC of 0.9164, ACC of 83.55%, and MCC of 0.6095. The model's predictive reliability was further substantiated by an applicability domain analysis. Feature importance, assessed through permutation importance within the BBC + GBDT model, highlighted key molecular properties that significantly influence NCDIA toxicity. Additionally, 16 structural alerts identified by SARpy software further revealed potential molecular signatures associated with toxicity, enriching our understanding of the underlying mechanisms. We also applied the constructed models to assess the NCDIA toxicity of novel drugs approved by FDA. This study advances predictive toxicology by providing a framework to assess and mitigate agranulocytosis risks, ensuring the safety of pharmaceutical development and facilitating post-market surveillance of new drugs.

Electrochemical Synthesis of the In Human S-oxide Metabolites of Phenothiazine-Containing Antipsychotic Medications

The tractable preparation of Phase I drug metabolites is a critical step to understand the first-pass behaviour of novel chemical entities (NCEs) in drug discovery. In this study, we have developed a structure-electroactivity relationship (SeAR)-informed electrochemical reaction of the parent 2-chlorophenothiazine and the antipsychotic medication, chlorpromazine. With the ability to dial-in under current controlled conditions, the formation of S-oxide and novel S,S-dioxide metabolites has been achieved for the first time on a multi-milligram scale using a direct batch electrode platform. A potential rationale for the electrochemical formation of these metabolites in situ is proposed using molecular docking to a cytochrome P450 enzyme.

Formation of potentially toxic metabolites of drugs in reactions catalyzed by human drug-metabolizing enzymes

Data are presented on the formation of potentially toxic metabolites of drugs that are substrates of human drug metabolizing enzymes. The tabular data lists the formation of potentially toxic/reactive products. The data were obtained from in vitro experiments and showed that the oxidative reactions predominate (with 96% of the total potential toxication reactions). Reductive reactions (e.g., reduction of nitro to amino group and reductive dehalogenation) participate to the extent of 4%. Of the enzymes, cytochrome P450 (P450, CYP) enzymes catalyzed 72% of the reactions, myeloperoxidase (MPO) 7%, flavin-containing monooxygenase (FMO) 3%, aldehyde oxidase (AOX) 4%, sulfotransferase (SULT) 5%, and a group of minor participating enzymes to the extent of 9%. Within the P450 Superfamily, P450 Subfamily 3A (P450 3A4 and 3A5) participates to the extent of 27% and the Subfamily 2C (P450 2C9 and P450 2C19) to the extent of 16%, together catalyzing 43% of the reactions, followed by P450 Subfamily 1A (P450 1A1 and P450 1A2) with 15%. The P450 2D6 enzyme participated in an extent of 8%, P450 2E1 in 10%, and P450 2B6 in 6% of the reactions. All other enzymes participate to the extent of 14%. The data show that, of the human enzymes analyzed, P450 enzymes were dominant in catalyzing potential toxication reactions of drugs and their metabolites, with the major role assigned to the P450 Subfamily 3A and significant participation of the P450 Subfamilies 2C and 1A, plus the 2D6, 2E1 and 2B6 enzymes contributing. Selected examples of drugs that are activated or proposed to form toxic species are discussed.

Identifying chemicals based on receptor binding/bioactivation/mechanistic explanation associated with potential to elicit hepatotoxicity and to support structure activity relationship-based read-across

The liver is the most common target organ in toxicology studies. The development of chemical structural alerts for identifying hepatotoxicity will play an important role in in silico model prediction and help strengthen the identification of analogs used in structure activity relationship (SAR)- based read-across. The aim of the current study is development of an SAR-based expert-system decision tree for screening of hepatotoxicants across a wide range of chemistry space and proposed modes of action for clustering of chemicals using defined core chemical categories based on receptor-binding or bioactivation. The decision tree is based on ∼ 1180 different chemicals that were reviewed for hepatotoxicity information. Knowledge of chemical receptor binding, metabolism and mechanistic information were used to group these chemicals into 16 different categories and 102 subcategories: four categories describe binders to 9 different receptors, 11 categories are associated with possible reactive metabolites (RMs) and there is one miscellaneous category. Each chemical subcategory has been associated with possible modes of action (MOAs) or similar key structural features. This decision tree can help to screen potential liver toxicants associated with core structural alerts of receptor binding and/or RMs and be used as a component of weight of evidence decisions based on SAR read-across, and to fill data gaps.

Idiosyncratic Drug-Induced Liver Injury: Mechanistic and Clinical Challenges

Idiosyncratic drug-induced liver injury (IDILI) remains a significant problem for patients and drug development. The idiosyncratic nature of IDILI makes mechanistic studies difficult, and little is known of its pathogenesis for certain. Circumstantial evidence suggests that most, but not all, IDILI is caused by reactive metabolites of drugs that are bioactivated by cytochromes P450 and other enzymes in the liver. Additionally, there is overwhelming evidence that most IDILI is mediated by the adaptive immune system; one example being the association of IDILI caused by specific drugs with specific human leukocyte antigen (HLA) haplotypes, and this may in part explain the idiosyncratic nature of these reactions. The T cell receptor repertoire likely also contributes to the idiosyncratic nature. Although most of the liver injury is likely mediated by the adaptive immune system, specifically cytotoxic CD8+ T cells, adaptive immune activation first requires an innate immune response to activate antigen presenting cells and produce cytokines required for T cell proliferation. This innate response is likely caused by either a reactive metabolite or some form of cell stress that is clinically silent but not idiosyncratic. If this is true it would make it possible to study the early steps in the immune response that in some patients can lead to IDILI. Other hypotheses have been proposed, such as mitochondrial injury, inhibition of the bile salt export pump, unfolded protein response, and oxidative stress although, in most cases, it is likely that they are also involved in the initiation of an immune response rather than representing a completely separate mechanism. Using the clinical manifestations of liver injury from a number of examples of IDILI-associated drugs, this review aims to summarize and illustrate these mechanistic hypotheses.

Modeling the Bioactivation and Subsequent Reactivity of Drugs

Electrophilically reactive drug metabolites are implicated in many adverse drug reactions. In this mechanism-termed bioactivation-metabolic enzymes convert drugs into reactive metabolites that often conjugate to nucleophilic sites within biological macromolecules like proteins. Toxic metabolite-product adducts induce severe immune responses that can cause sometimes fatal disorders, most commonly in the form of liver injury, blood dyscrasia, or the dermatologic conditions toxic epidermal necrolysis and Stevens-Johnson syndrome. This study models four of the most common metabolic transformations that result in bioactivation: quinone formation, epoxidation, thiophene sulfur-oxidation, and nitroaromatic reduction, by synthesizing models of metabolism and reactivity. First, the metabolism models predict the formation probabilities of all possible metabolites among the pathways studied. Second, the exact structures of these metabolites are enumerated. Third, using these structures, the reactivity model predicts the reactivity of each metabolite. Finally, a feedfoward neural network converts the metabolism and reactivity predictions to a bioactivation prediction for each possible metabolite. These bioactivation predictions represent the joint probability that a metabolite forms and that this metabolite subsequently conjugates to protein or glutathione. Among molecules bioactivated by these pathways, we predicted the correct pathway with an AUC accuracy of 89.98%. Furthermore, the model predicts whether molecules will be bioactivated, distinguishing bioactivated and nonbioactivated molecules with 81.06% AUC. We applied this algorithm to withdrawn drugs. The known bioactivation pathways of alclofenac and benzbromarone were identified by the algorithm, and high probability bioactivation pathways not yet confirmed were identified for safrazine, zimelidine, and astemizole. This bioactivation model-the first of its kind that jointly considers both metabolism and reactivity-enables drug candidates to be quickly evaluated for a toxicity risk that often evades detection during preclinical trials. The XenoSite bioactivation model is available at http://swami.wustl.edu/xenosite/p/bioactivation.

A Robust, Mechanistically Based In Silico Structural Profiler for Hepatic Cholestasis

Owing to the primary role which it holds within metabolism of xenobiotics, the liver stands at heightened risk of exposure to, and injury from, potentially hazardous substances. A principal manifestation of liver dysfunction is cholestasis-the impairment of physiological bile circulation from its point of origin within the organ to the site of action in the small intestine. The capacity for early identification of compounds liable to exert cholestatic effects is of particular utility within the field of pharmaceutical development, where contribution toward candidate attrition is great. Shortcomings associated with the present in vitro methodologies forecasting cholestasis render their predictivity questionable, permitting scope for the adoption of computational toxicology techniques. As such, the intention of this study has been to construct an in silico profiler, founded upon clinical data, highlighting structural motifs most reliably associated with the end point. Drawing upon a list of >1500 small molecular drugs, compiled and annotated by Kotsampasakou, E. and Ecker, G. F. (J. Chem. Inf. Model. 2017, 57, 608-615), we have formulated a series of 15 structural alerts. These describe fragments intrinsic within distinct pharmaceutical classes including psychoactive tricyclics, β-lactam antimicrobials, and estrogenic/androgenic steroids. Description of the coverage and selectivity of each are provided, alongside consideration of the underlying reactive mechanisms and relevant structure-activity concerns. Provision of mechanistic anchoring ensures that potential exists for framing within the adverse outcome pathway paradigm-the chemistry conveyed through the alert, in particular enabling rationalization at the level of the molecular initiating event.

How Can Drug Metabolism and Transporter Genetics Inform Psychotropic Prescribing?

Many genetic variants in drug metabolizing enzymes and transporters have been shown to be relevant for treating psychiatric disorders. Associations are strong enough to feature on drug labels and for prescribing guidelines based on such data. A range of commercial tests are available; however, there is variability in included genetic variants, methodology, and interpretation. We herein provide relevant background for understanding clinical associations with specific variants, other factors that are relevant to consider when interpreting such data (such as age, gender, drug-drug interactions), and summarize the data relevant to clinical utility of pharmacogenetic testing in psychiatry and the available prescribing guidelines. We also highlight areas for future research focus in this field.

Molecular Hydrogen Metabolism: a Widespread Trait of Pathogenic Bacteria and Protists

Pathogenic microorganisms use various mechanisms to conserve energy in host tissues and environmental reservoirs. One widespread but often overlooked means of energy conservation is through the consumption or production of molecular hydrogen (H2). Here, we comprehensively review the distribution, biochemistry, and physiology of H2 metabolism in pathogens. Over 200 pathogens and pathobionts carry genes for hydrogenases, the enzymes responsible for H2 oxidation and/or production. Furthermore, at least 46 of these species have been experimentally shown to consume or produce H2 Several major human pathogens use the large amounts of H2 produced by colonic microbiota as an energy source for aerobic or anaerobic respiration. This process has been shown to be critical for growth and virulence of the gastrointestinal bacteria Salmonella enterica serovar Typhimurium, Campylobacter jejuni, Campylobacter concisus, and Helicobacter pylori (including carcinogenic strains). H2 oxidation is generally a facultative trait controlled by central regulators in response to energy and oxidant availability. Other bacterial and protist pathogens produce H2 as a diffusible end product of fermentation processes. These include facultative anaerobes such as Escherichia coli, S Typhimurium, and Giardia intestinalis, which persist by fermentation when limited for respiratory electron acceptors, as well as obligate anaerobes, such as Clostridium perfringens, Clostridioides difficile, and Trichomonas vaginalis, that produce large amounts of H2 during growth. Overall, there is a rich literature on hydrogenases in growth, survival, and virulence in some pathogens. However, we lack a detailed understanding of H2 metabolism in most pathogens, especially obligately anaerobic bacteria, as well as a holistic understanding of gastrointestinal H2 transactions overall. Based on these findings, we also evaluate H2 metabolism as a possible target for drug development or other therapies.

Biotransformation and bioactivation reactions - 2017 literature highlights *

This annual review is the third one to highlight recent advances in the study and assessment of biotransformations and bioactivations ( Table 1 ). We followed the same format as the previous years with selection and authoring each section (see Baillie et al. 2016 ; Khojasteh et al. 2017 ). We acknowledge that many universities no longer train students in mechanistic biotransformation studies reflecting a decline in the investment for those efforts by public funded granting institutions. We hope this work serves as a resource to appreciate the knowledge gained each year to understand and hopefully anticipate toxicological outcomes dependent on biotransformations and bioactivations. This effort itself also continues to evolve. I am pleased that Drs. Rietjens and Miller have again contributed to this annual review. We would like to welcome Kaushik Mitra as an author for this year's issue, and we thank Deepak Dalvie for his contributions to last year's edition. We have intentionally maintained a balance of authors such that two come from an academic setting and two come from industry. As always, please drop us a note if you find this review helpful. We would be pleased to hear your opinions of our commentary, and we extend an invitation to anyone who would like to contribute to a future edition of this review.

Schizophrenia: synthetic strategies and recent advances in drug design

Schizophrenia is a complex and unpredictable mental disorder which affects several domains of cognition and behaviour. It is a heterogeneous illness characterised by positive, negative, and cognitive symptoms, often accompanied by signs of depression. In this tutorial review, we discuss recent progress in understanding the target sites and mechanisms of action of second-generation antipsychotic drugs. Progress in identifying and defining target sites has been accelerated recently by advances in neuroscience, and newly developed agents that regulate signalling by the main excitatory neurotransmitters in the brain are surveyed. Examples of novel molecules for the treatment of schizophrenia in preclinical and clinical development and their industrial sponsors are highlighted.

Deep Learning to Predict the Formation of Quinone Species in Drug Metabolism

Many adverse drug reactions are thought to be caused by electrophilically reactive drug metabolites that conjugate to nucleophilic sites within DNA and proteins, causing cancer or toxic immune responses. Quinone species, including quinone-imines, quinone-methides, and imine-methides, are electrophilic Michael acceptors that are often highly reactive and comprise over 40% of all known reactive metabolites. Quinone metabolites are created by cytochromes P450 and peroxidases. For example, cytochromes P450 oxidize acetaminophen to N-acetyl-p-benzoquinone imine, which is electrophilically reactive and covalently binds to nucleophilic sites within proteins. This reactive quinone metabolite elicits a toxic immune response when acetaminophen exceeds a safe dose. Using a deep learning approach, this study reports the first published method for predicting quinone formation: the formation of a quinone species by metabolic oxidation. We model both one- and two-step quinone formation, enabling accurate quinone formation predictions in nonobvious cases. We predict atom pairs that form quinones with an AUC accuracy of 97.6%, and we identify molecules that form quinones with 88.2% AUC. By modeling the formation of quinones, one of the most common types of reactive metabolites, our method provides a rapid screening tool for a key drug toxicity risk. The XenoSite quinone formation model is available at http://swami.wustl.edu/xenosite/p/quinone .

Molecular dynamics and density functional studies on the metabolic selectivity of antipsychotic thioridazine by cytochrome P450 2D6: Connection with crystallographic and metabolic results

CYP2D6, a cytochrome P450 isoform, significantly contributes to the metabolism of many clinically important drugs. Thioridazine (THD) is one of the phenothiazine-type antipsychotics, which exhibit dopamine D2 antagonistic activity. THD shows characteristic metabolic profiles compared to other phenothiazine-type antipsychotics such as chlorpromazine. The sulfur atom attached to the phenothiazine ring is preferentially oxidized mainly by CYP2D6, that is, the 2-sulfoxide is a major metabolite, and interestingly this metabolite shows more potent activity against dopamine D2 receptors than THD. On the other hand, the formation of this metabolite causes many serious problems for its clinical use. Wójcikowski et al. (Drug Metab. Dispos. 2006, 34, 471) reported a kinetic study of THD formed by CYP2D6. Recently, Wang et al. (J. Biol. Chem. 2012, 287, 10834 and J. Biol. Chem. 2015, 290, 5092) revealed the crystallographic structure of THD with CYP2D6. In the current study, the binding and reaction mechanisms at the atomic and electronic levels were computationally examined based on the assumption as to whether or not the different crystallographic binding poses correspond to the different metabolites. The binding and oxidative reaction steps in the whole metabolic process were investigated using molecular dynamics and density functional theory calculations, respectively. The current study demonstrated the essential importance of the orientation of the substrate in the reaction center of CYP2D6 for the metabolic reaction.

Contributions of ionic interactions and protein dynamics to cytochrome P450 2D6 (CYP2D6) substrate and inhibitor binding

P450 2D6 contributes significantly to the metabolism of >15% of the 200 most marketed drugs. Open and closed crystal structures of P450 2D6 thioridazine complexes were obtained using different crystallization conditions. The protonated piperidine moiety of thioridazine forms a charge-stabilized hydrogen bond with Asp-301 in the active sites of both complexes. The more open conformation exhibits a second molecule of thioridazine bound in an expanded substrate access channel antechamber with its piperidine moiety forming a charge-stabilized hydrogen bond with Glu-222. Incubation of the crystalline open thioridazine complex with alternative ligands, prinomastat, quinidine, quinine, or ajmalicine, displaced both thioridazines. Quinine and ajmalicine formed charge-stabilized hydrogen bonds with Glu-216, whereas the protonated nitrogen of quinidine is equidistant from Asp-301 and Glu-216 with protonated nitrogen H-bonded to a water molecule in the access channel. Prinomastat is not ionized. Adaptations of active site side-chain rotamers and polypeptide conformations were evident between the complexes, with the binding of ajmalicine eliciting a closure of the open structure reflecting in part the inward movement of Glu-216 to form a hydrogen bond with ajmalicine as well as sparse lattice restraints that would hinder adaptations. These results indicate that P450 2D6 exhibits sufficient elasticity within the crystal lattice to allow the passage of compounds between the active site and bulk solvent and to adopt a more closed form that adapts for binding alternative ligands with different degrees of closure. These crystals provide a means to characterize substrate and inhibitor binding to the enzyme after replacement of thioridazine with alternative compounds.

Molecular cytotoxic mechanisms of chlorpromazine in isolated rat hepatocytes

Chlorpromazine (CPZ), a member of the largest class of first-generation antipsychotic agents, is known to cause hepatotoxicity in the form of cholestasis and hepatocellular necrosis in some patients. The mechanism of CPZ hepatotoxicity is unclear, but is thought to result from reactive metabolite formation. The goal of this research was to assess potential cytotoxic mechanisms of CPZ using the accelerated cytotoxicity mechanism screening (ACMS) technique with freshly isolated rat hepatocytes. This study identified CPZ cytotoxicity and inhibition of mitochondrial membrane potential (MMP) to be concentration-dependent. Furthermore, inhibition of cytochrome P450s (CYPs), including CYP2D1 and 1A2, delayed CPZ cytotoxicity, suggesting a role for CYP activation of CPZ to a toxic metabolite(s) in this model. Metabolism studies also demonstrated glucuronide and glutathione (GSH) requirement for CPZ detoxification in hepatocytes. Inactivating the 2-electron reduction pathway, NAD(P)H quinone oxidoreductase (NQO1), caused a significant increase in hepatocyte susceptibility to CPZ, indicating quinoneimine contribution to CPZ cytotoxicity. Nontoxic concentrations of peroxidase/H2O2 (inflammatory model) increased cytotoxicity in CPZ-treated hepatocytes and caused additional mitochondrial toxicity. Inflammation further depleted GSH and increased oxidized glutathione (GSSG) levels. Results suggest activation of CPZ to reactive metabolites by 2 pathways in hepatocytes: (i) a CYP-catalyzed quinoneimine pathway, and (ii) a peroxidase-catalyzed oxidation of CPZ to CPZ radicals.

Characterization of primary human hepatocytes, HepG2 cells, and HepaRG cells at the mRNA level and CYP activity in response to inducers and their predictivity for the detection of human hepatotoxins

In the pharmaceutical industry, improving the early detection of drug-induced hepatotoxicity is essential as it is one of the most important reasons for attrition of candidate drugs during the later stages of drug development. The first objective of this study was to better characterize different cellular models (i.e., HepG2, HepaRG cells, and fresh primary human hepatocytes) at the gene expression level and analyze their metabolic cytochrome P450 capabilities. The cellular models were exposed to three different CYP450 inducers; beta-naphthoflavone (BNF), phenobarbital (PB), and rifampicin (RIF). HepG2 cells responded very weakly to the different inducers at the gene expression level, and this translated generally into low CYP450 activities in the induced cells compared with the control cells. On the contrary, HepaRG cells and the three human donors were inducible after exposure to BNF, PB, and RIF according to gene expression responses and CYP450 activities. Consequently, HepaRG cells could be used in screening as a substitute and/or in complement to primary hepatocytes for CYP induction studies. The second objective was to investigate the predictivity of the different cellular models to detect hepatotoxins (16 hepatotoxic and 5 nonhepatotoxic compounds). Specificity was 100% with the different cellular models tested. Cryopreserved human hepatocytes gave the highest sensitivity, ranging from 31% to 44% (depending on the donor), followed by lower sensitivity (13%) for HepaRG and HepG2 cells (6.3%). Overall, none of the models under study gave desirable sensitivities (80-100%). Consequently, a high metabolic capacity and CYP inducibility in cell lines does not necessarily correlate with a high sensitivity for the detection of hepatotoxic drugs. Further investigations are necessary to compare different cellular models and determine those that are best suited for the detection of hepatotoxic compounds.

Central role of mitochondria in drug-induced liver injury

A frequent mechanism for drug-induced liver injury (DILI) is the formation of reactive metabolites that trigger hepatitis through direct toxicity or immune reactions. Both events cause mitochondrial membrane disruption. Genetic or acquired factors predispose to metabolite-mediated hepatitis by increasing the formation of the reactive metabolite, decreasing its detoxification, or by the presence of critical human leukocyte antigen molecule(s). In other instances, the parent drug itself triggers mitochondrial membrane disruption or inhibits mitochondrial function through different mechanisms. Drugs can sequester coenzyme A or can inhibit mitochondrial β-oxidation enzymes, the transfer of electrons along the respiratory chain, or adenosine triphosphate (ATP) synthase. Drugs can also destroy mitochondrial DNA, inhibit its replication, decrease mitochondrial transcripts, or hamper mitochondrial protein synthesis. Quite often, a single drug has many different effects on mitochondrial function. A severe impairment of oxidative phosphorylation decreases hepatic ATP, leading to cell dysfunction or necrosis; it can also secondarily inhibit ß-oxidation, thus causing steatosis, and can also inhibit pyruvate catabolism, leading to lactic acidosis. A severe impairment of β-oxidation can cause a fatty liver; further, decreased gluconeogenesis and increased utilization of glucose to compensate for the inability to oxidize fatty acids, together with the mitochondrial toxicity of accumulated free fatty acids and lipid peroxidation products, may impair energy production, possibly leading to coma and death. Susceptibility to parent drug-mediated mitochondrial dysfunction can be increased by factors impairing the removal of the toxic parent compound or by the presence of other medical condition(s) impairing mitochondrial function. New drug molecules should be screened for possible mitochondrial effects.

Fragmentation of toxicologically relevant drugs in positive-ion liquid chromatography-tandem mass spectrometry

The identification of drugs and related compounds by LC-MS-MS is an important analytical challenge in several application areas, including clinical and forensic toxicology, doping control analysis, and environmental analysis. Although target-compound based analytical strategies are most frequently applied, at some point the information content of the MS-MS spectra becomes relevant. In this article, the positive-ion MS-MS spectra of a wide variety of drugs and related substances are discussed. Starting point was an MS-MS mass spectral library of toxicologically relevant compounds, available on the internet. The positive-ion MS-MS spectra of ∼570 compounds were interpreted by chemical and therapeutic class, thus involving a wide variety of drug compound classes, such benzodiazepines, beta-blockers, angiotensin-converting enzyme inhibitors, phenothiazines, dihydropyridine calcium channel blockers, diuretics, local anesthetics, vasodilators, as well as various subclasses of anti-diabetic, antidepressant, analgesic, and antihistaminic drugs. In addition, the scientific literature was searched for available MS-MS data of these compound classes and the interpretation thereof. The results of this elaborate study are presented in this article. For each individual compound class, the emphasis is on class-specific fragmentation, as discussing fragmentation of all individual compounds would take far too much space. The recognition of class-specific fragmentation may be quite informative in determining the compound class of a specific unknown, which may further help in the identification. In addition, knowledge on (class-specific) fragmentation may further help in the optimization of the selectivity in targeted analytical approaches of compounds of one particular class.