Detection and characterization of ticlopidine conjugates in rat bile using high-resolution mass spectrometry: applications of various data acquisition and processing tools

Development of a fluorous trapping reagent for rapid detection of electrophilic reactive metabolites

A cysteine-based fluorous trapping reagent, Rf8CYS, was developed. Rf8CYS formed adducts with soft and hard electrophilic reactive metabolites. These fluorous-tagged adducts were purified via both fluorous solid-phase extraction and the direct injection method. The highly sensitive mass spectrometric detection of an unprecedented adduct of the ticlopidine metabolite was realized.

Monooxygenase- and Dioxygenase-Catalyzed Oxidative Dearomatization of Thiophenes by Sulfoxidation, cis-Dihydroxylation and Epoxidation

Enzymatic oxidations of thiophenes, including thiophene-containing drugs, are important for biodesulfurization of crude oil and drug metabolism of mono- and poly-cyclic thiophenes. Thiophene oxidative dearomatization pathways involve reactive metabolites, whose detection is important in the pharmaceutical industry, and are catalyzed by monooxygenase (sulfoxidation, epoxidation) and dioxygenase (sulfoxidation, dihydroxylation) enzymes. Sulfoxide and epoxide metabolites of thiophene substrates are often unstable, and, while cis-dihydrodiol metabolites are more stable, significant challenges are presented by both types of metabolite. Prediction of the structure, relative and absolute configuration, and enantiopurity of chiral metabolites obtained from thiophene enzymatic oxidation depends on the substrate, type of oxygenase selected, and molecular docking results. The racemization and dimerization of sulfoxides, cis/trans epimerization of dihydrodiol metabolites, and aromatization of epoxides are all factors associated with the mono- and di-oxygenase-catalyzed metabolism of thiophenes and thiophene-containing drugs and their applications in chemoenzymatic synthesis and medicine.

1-(Benzo[b]thiophen-4-yl)piperazine Ring Induced Bioactivation of Brexpiprazole in Liver Microsomes: Identification and Characterization of Reactive Conjugates Using Ultra-High-Performance Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry

BACKGROUND AND OBJECTIVES

Brexpiprazole is an atypical antipsychotic approved for the treatment of schizophrenia and major depressive disorders in adults. The structure of brexpiprazole contains well-known structural alerts like a thiophene ring, piperazine ring and quinolinone motifs. Additionally, the literature reveals that its structural analog, aripiprazole, could generate reactive intermediates. However, the bioactivation potential of brexpiprazole is yet unknown. Therefore, this study was planned to identify and characterize reactive adducts of brexpiprazole and its metabolites.

METHODS

Based on the reactivity, the potential atomic sites for a reactive intermediate generation were predicted by a xenosite web predictor tool for glutathione, cyanide, protein and DNA. To study the metabolic activation of brexpiprazole, the drug was individually incubated for 2 h at 37 °C with pooled male rat liver microsomes and human liver microsomes in microcentrifuge tubes fortified with glutathione/N-acetyl cysteine. Nicotinamide adenine dinucleotide phosphate reduced tetrasodium salt was used as a co-factor.

RESULTS

A total of six glutathione and N-acetyl cysteine conjugates of brexpiprazole metabolites were identified and characterized using ultra-high-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry. Reactive metabolite 1 (RM1), RM3, RM4 and RM6 reactive conjugates were formed due to reactive quinone-imine or quinone intermediates, while RM2 and RM5 reactive adducts were generated because of a thiophene-S-oxide intermediate.

CONCLUSION

Brexpirazole is bioactivated due to the presence of a 1-(benzo[b]thiophen-4-yl)piperazine ring in its structure. In contrast to aripiprazole, the quinolinone motif was found latent towards bioactivation in brexpiprazole.

The application of a novel high-resolution mass spectrometry-based analytical strategy to rapid metabolite profiling of a dual drug combination in humans

Metabolite profiling of combination drugs in complex matrix is a big challenge. Development of an effective data mining technique for simultaneously extracting metabolites of one parent drug from both background matrix and combined drug-related signals could be a solution. This study presented a novel high resolution mass spectrometry (HRMS)-based data-mining strategy to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was verapamil-irbesartan (VER-IRB), which is widely used in clinic to treat hypertension. First, mass defect filter (MDF), as a targeted data mining tool, worked effectively except for those metabolites with similar MDF values. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, was able to recover all relevant metabolites of VER-IRB from the full-scan MS dataset except for trace metabolites buried in the background noise and/or combined drug-related signals. Third, the novel ring double bond (RDB; valence values of elements in structure) filter, could show rich structural information in more sensitive full-scan MS chromatograms; however, it had a low capability to remove background noise and was difficult to differentiate the metabolites with RDB coverage. Fourth, an integrated strategy, i.e., untargeted BS followed by RDB, was effective for metabolite identification of VER and IRB, which have different RDB values. Majority of matrix signals were firstly removed using BS. Metabolite ions for each parent drug were then isolated from remaining background matrix and combined drug-related signals by imposing of preset RDB values/ranges around the parent drug and selected core substructures. In parallel, MDF was used to recover potential metabolites with similar RDB. As a result, a total of 74 metabolites were found for VER-IRB in human plasma and urine, among which ten metabolites have not been previously reported in human. The results demonstrated that the combination of accurate mass-based multiple data-mining techniques, i.e., untargeted background subtraction followed by ring double bond filtering in parallel with targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drug.

Post-acquisition data mining techniques for LC–MS/MS-acquired data in drug metabolite identification

Metabolite identification is a crucial part of the drug discovery process. LC–MS/MS-based metabolite identification has gained widespread use, but the data acquired by the LC–MS/MS instrument is complex, and thus the interpretation of data becomes troublesome. Fortunately, advancements in data mining techniques have simplified the process of data interpretation with improved mass accuracy and provide a potentially selective, sensitive, accurate and comprehensive way for metabolite identification. In this review, we have discussed the targeted (extracted ion chromatogram, mass defect filter, product ion filter, neutral loss filter and isotope pattern filter) and untargeted (control sample comparison, background subtraction and metabolomic approaches) post-acquisition data mining techniques, which facilitate the drug metabolite identification. We have also discussed the importance of integrated data mining strategy.

An efficient data-filtering strategy for easy metabolite detection from the direct analysis of a biological fluid using Fourier transform mass spectrometry

RATIONALE

High-throughput analyses require an overall analytical workflow including not only a robust and high-speed technical platform, but also dedicated data-processing tools able to extract the relevant information. This work aimed at evaluating post-acquisition data-mining tools for selective extraction of metabolite species from direct introduction high-resolution mass spectrometry data.

METHODS

Investigations were performed on spectral data in which seven metabolites of vinclozolin, a dicarboximide fungicide containing two chloride atoms, were previously manually identified. The spectral data obtained from direct introduction (DI) and high-resolution mass spectrometry (HRMS) detection were post-processed by plotting the mass defect profiles and applying various data-filtering methods based on accurate mass values.

RESULTS

Exploration of mass defect profiles highlighted, in a specific plotting region, the presence of compounds containing common chemical elements and pairs of conjugated and non-conjugated metabolites resulting from classical metabolic pathways. Additionally, the judicious application of mass defect and/or isotope pattern filters removed many interfering ions from DI-HRMS data, greatly facilitating the detection of vinclozolin metabolites. Compared with previous results obtained by manual data treatment, three additional metabolites of vinclozolin were detected and putatively annotated.

CONCLUSIONS

Tracking simultaneously several specific species could be efficiently performed using data-mining tools based on accurate mass values. The selectivity of the data extraction was improved when the isotope filter was used for halogenated compounds, facilitating metabolite ion detection even for low-abundance species. Copyright © 2016 John Wiley & Sons, Ltd.

Computational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes

Structural alerts are commonly used in drug discovery to identify molecules likely to form reactive metabolites and thereby become toxic. Unfortunately, as useful as structural alerts are, they do not effectively model if, when, and why metabolism renders safe molecules toxic. Toxicity due to a specific structural alert is highly conditional, depending on the metabolism of the alert, the reactivity of its metabolites, dosage, and competing detoxification pathways. A systems approach, which explicitly models these pathways, could more effectively assess the toxicity risk of drug candidates. In this study, we demonstrated that mathematical models of P450 metabolism can predict the context-specific probability that a structural alert will be bioactivated in a given molecule. This study focuses on the furan, phenol, nitroaromatic, and thiophene alerts. Each of these structural alerts can produce reactive metabolites through certain metabolic pathways but not always. We tested whether our metabolism modeling approach, XenoSite, can predict when a given molecule's alerts will be bioactivated. Specifically, we used models of epoxidation, quinone formation, reduction, and sulfur-oxidation to predict the bioactivation of furan-, phenol-, nitroaromatic-, and thiophene-containing drugs. Our models separated bioactivated and not-bioactivated furan-, phenol-, nitroaromatic-, and thiophene-containing drugs with AUC performances of 100%, 73%, 93%, and 88%, respectively. Metabolism models accurately predict whether alerts are bioactivated and thus serve as a practical approach to improve the interpretability and usefulness of structural alerts. We expect that this same computational approach can be extended to most other structural alerts and later integrated into toxicity risk models. This advance is one necessary step toward our long-term goal of building comprehensive metabolic models of bioactivation and detoxification to guide assessment and design of new therapeutic molecules.

A strategy for fast screening and identification of sulfur derivatives in medicinal Pueraria species based on the fine isotopic pattern filtering method using ultra-high-resolution mass spectrometry

Sulfurous compounds are commonly present in plants, fungi, and animals. Most of them were reported to possess various bioactivities. Isotopic pattern filter (IPF) is a powerful tool for screening compounds with distinct isotope pattern. Over the past decades, the IPF was used mainly to study Cl- and Br-containing compounds. To our knowledge, the algorithm was scarcely used to screen S-containing compounds, especially when combined with chromatography analyses, because the (34)S isotopic ion is drastically affected by (13)C2 and (18)O. Thus, we present a new method for a fine isotopic pattern filter (FIPF) based on the separated M + 2 ions ((12)C(x)(1)H(y)(16)O(z)(32)S(13)C2(18)O, (12)C(x+2)(1)H(y)(16)O(z+1)(34)S, tentatively named M + 2OC and M + 2S) with an ultra-high-resolution mass (100,000 FWHM @ 400 m/z) to screen sulfur derivatives in traditional Chinese medicines (TCM).This finer algorithm operates through convenient filters, including an accurate mass shift of M + 2OC and M + 2S from M and their relative intensity compared to M. The method was validated at various mass resolutions, mass accuracies, and screening thresholds of flexible elemental compositions. Using the established FIPF method, twelve S-derivatives were found in the popular medicinal used Pueraria species, and 9 of them were tentatively identified by high-resolution multiple stage mass spectrometry (HRMS(n)). The compounds were used to evaluate the sulfurous compounds' situation in commercially purchased Pueraria products. The strategy presented here provides a promising application of the IPF method in a new field.

Rapid determination of oligopeptides and amino acids in soybean protein hydrolysates using high-resolution mass spectrometry

INTRODUCTION

Soybean protein hydrolysates (SPHs), especially oligopeptides, have shown a variety of functional properties, including immunomodulatory and anti-oxidant effects. Soybean protein hydrolysate products have been used as functional ingredients in food, sports nutrition or clinical nutrition. However, the mixture is mostly undefined due to its complex nature, containing peptides and minor amino acids as well as small proteins.

OBJECTIVES

To develop a specific and efficient method for the identification and structural characterisation of oligopeptides in SPHs, and to determine free amino acids in SPHs in the same analytical run, for evaluation of the chemical profile of SPH products.

METHODS

Accurate mass spectrometry (MS) datasets of SPH samples were recorded on a high-performance liquid chromatography (HPLC) tandem high-resolution (HR) MS system. Potential oligopeptides were tentatively characterised based on their elemental compositions and ring double bond equivalent (RDBE) values, as well as HRMS/MS data. The analytical method to determine amino acids was evaluated in terms of linearity, precision, apparent recovery and limits of detection and quantitation.

RESULTS

In total, 186 oligopeptides spanning the mass range of m/z 200-1500 and three major free amino acids could be determined in SPH samples in a single sample injection. Ninety-nine oligopeptides were tentatively characterised. The sensitive and specific instrumental performances also permitted the determination of 19 amino acids with a limit of quantitation of ≤ 0.1 μg/mL.

CONCLUSION

The HPLC-HRMS technique has proven to be an advantageous tool for the rapid characterisation of oligopeptides and determination of amino acids in soybean protein hydrolysates.

Identification of xenobiotic metabolites from biological fluids using flow injection analysis high-resolution mass spectrometry and post-acquisition data filtering

RATIONALE

Concern for public health entails the need to evaluate the degree of exposure of population to toxicants. To do this, robust high-throughput approaches are required to be able to perform a large number of analyses in cohort studies. In this study, a data-filtering procedure was applied to mass spectral data acquired by direct analysis of biological fluids leading to rapid detection of metabolites in a model xenobiotic system.

METHODS

Flow injection analysis (FIA) coupled to negative electrospray ionization (ESI)-LTQ Orbitrap Fourier transform mass spectrometry was used to directly analyze urine of rats treated with vinclozolin. Tandem mass spectrometry (MS/MS) experiments were subsequently performed for confirmation of a new metabolite structure. The isotope filtering based on the difference between accurate masses of (35)Cl and (37)Cl was applied to the raw data for the specific detection of ions containing at least one chlorine atom.

RESULTS

Seven metabolites of vinclozolin were manually identified thanks to the characteristic isotope pattern of dichlorinated compounds. A new metabolite of vinclozolin was detected for the first time and identified as a sulfate conjugate. The application of an isotope-filtering procedure allowed the selective extraction of pertinent signals from the data. The processed mass spectrum was greatly simplified, significantly facilitating the detection of the seven metabolites previously identified.

CONCLUSIONS

The use of FIA-HRMS in combination with dedicated bio-informatics data processing is shown to be an efficient approach for the rapid detection of metabolites in biological fluids. This is a very promising high-throughput approach for rapid characterization of the exposure status to xenobiotics.

A short expedient synthesis of [(14)C]Ticlopidine

To support the development of a reactive metabolite strategy, the preparation of several radiolabelled compounds such as [(14)C] Ticlopidine was required. In this report, we describe a facile and rapid synthesis of [(14)C] Ticlopidine starting from [(14)C] carbon dioxide. The compound was radiolabelled in the 2-chloromethyl portion of the molecule with a specific activity of 53.4 mCi/mmol and with a radiochemical purity of 98.5%. Storage stability was best as the hydrochloride salt in an ethanol solution.

Metabolism and tissue distribution study of Vaccaria seeds (Wang-Bu-Liu-Xing) in benign prostatic hyperplasia model rat: toward an in-depth study for its bioactive components

Vaccaria seeds (Wang-Bu-Liu-Xing), a well-known traditional Chinese medicine (TCM), has been used as an emperor herb of many ancient formulas to treat benign prostatic hyperplasia (BPH) in clinic. However, its metabolism and tissue distribution, especially in the target tissue, had not been investigated so far. Based on the hypothesis that the components which exert effect against BPH of Vaccaria seeds would be measureable in target tissue (prostate), in vivo metabolism and tissue distribution of Vaccaria seeds in rats were profiled using a specific and sensitive high performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (LC-QTOF-MS/MS). As a result, 19 major constituents in the Vaccaria seeds decoction and 19 constituents in rat plasma, feces and tissues after oral administration of Vaccaria seeds decoction were identified. Accurate mass measurement for molecular ions and characteristic fragment ions could represent reliable identification criteria for these compounds. Two prototypes were detected in prostate. An in vitro metabolism analysis of them was studied after incubation with rat intestinal flora and rat liver microsome (RLM) in this paper, which is helpful for further investigation of the potential effect of these two components. The result of this study provided meaningful information for further pharmacology research on Vaccaria seeds.