MSE with mass defect filtering for in vitro and in vivo metabolite identification

Metabolite identification studies involve the detection and structural characterization of the biotransformation products of drug candidates. These experiments are necessary throughout the drug discovery and development process. The use of high-resolution chromatography and high-resolution mass spectrometry together with data processing using mass defect filtering is described for in vitro and in vivo metabolite identification studies. Data collection was done using UPLC coupled with an orthogonal hybrid quadrupole time-of-flight mass spectrometer. This experimental approach enabled the use of MS(E) data collection (where E represents collision energy) which has previously been shown to be a powerful approach for metabolite identification studies. Post-acquisition processing with a prototype mass defect filtering program was used to eliminate endogenous interferences in the study samples, greatly enhancing the discovery of metabolites. The ease of this approach is illustrated by results showing the detection and structural characterization of metabolites in plasma from a preclinical rat pharmacokinetic study.     

Application of a linear ion trap/orbitrap mass spectrometer in metabolite characterization studies: Examination of the human liver microsomal metabolism of the non-tricyclic anti-depressant nefazodone using data-dependent accurate mass measurements

We report herein, facile metabolite identification workflow on the anti-depressant nefazodone, which is derived from accurate mass measurements based on a single run/experimental analysis. A hybrid LTQ/orbitrap mass spectrometer was used to obtain accurate mass full scan MS and MS/MS in a data-dependent fashion to eliminate the reliance on a parent mass list. Initial screening utilized a high mass tolerance ( approximately 10 ppm) to filter the full scan MS data for previously reported nefazodone metabolites. The tight mass tolerance reduces or eliminates background chemical noise, dramatically increasing sensitivity for confirming or eliminating the presence of metabolites as well as isobaric forms. The full scan accurate mass analysis of suspected metabolites can be confirmed or refuted using three primary tools: (1) predictive chemical formula and corresponding mass error analysis, (2) rings-plus-double bonds, and (3) accurate mass product ion spectra of parent and suspected metabolites. Accurate mass characterization of the parent ion structure provided the basis for assessing structural assignment for metabolites. Metabolites were also characterized using parent product ion m/z values to filter all tandem mass spectra for identification of precursor ions yielding similar product ions. Identified metabolite parent masses were subjected to chemical formula calculator based on accurate mass as well as bond saturation. Further analysis of potential nefazodone metabolites was executed using accurate mass product ion spectra. Reported mass measurement errors for all full scan MS and MS/MS spectra was <3 ppm, regardless of relative ion abundance, which enabled the use of predictive software in determining product ion structure. The ability to conduct biotransformation profiling via tandem mass spectrometry coupled with accurate mass measurements, all in a single experimental run, is clearly one of the most attractive features of this methodology.     

Rapid detection and structural characterization of verapamil metabolites in rats by UPLC–MSE and UNIFI platform

High-resolution mass spectrometry (HRMS) is an important technology for studying biotransformations of drugs in biological systems. In order to process complex HRMS data, bioinformatics, including data-mining techniques for identifying drug metabolites from liquid chromatography/high-resolution mass spectrometry (LC/HRMS) or multistage mass spectrometry (MSⁿ) datasets as well as elucidating the detected metabolites’ structure by spectral interpretation software, are important tools. Data-mining technologies have widely been used in drug metabolite identification, including mass defect filters, product ion filters, neutral-loss filters, control sample comparisons and extracted ion chromatographic analysis. However, the metabolites identified by current different technologies are not the same, indicating the importance of technique integration for efficient and complete identification of metabolic products. In this study, a universal, high-throughput workflow for identifying and verifying metabolites by applying the drug metabolite identification software UNIFI is reported, to study the biotransformation of verapamil in rats. A total of 71 verapamil metabolites were found in rat plasma, urine and faeces, including two metabolites that have not been reported in the literature. Phase I metabolites of verapamil were identified as N-demethylation, O-demethylation, N-dealkylation and oxidation and dehydrogenation metabolites; phase II metabolites were mainly glucuronidation and sulfate conjugates, indicating that UNIFI software could be effective and valuable in identifying drug metabolites.     

Investigation of low-abundant in vitro metabolites of stable isotope-labelled BAL4815 by accurate mass capillary-LC-ESI-qTof-MS and MS/MS

The metabolic profile of BAL4815, an antifungal azole drug, was determined using in vitro rat hepatocyte incubations and subsequent analysis by capillary LC-qTof-MS and MS/MS including accurate mass determination. For the detection of the metabolites, a mixture of the drug and its deuterium-labelled analogue was used for incubations. Metabolic stability of BAL4815 was high in cultured rat hepatocytes. However, several low-abundant metabolites were detected by the use of capillary LC-qTof-MS and manual investigation of the data. The peak intensity of the most abundant metabolite was close to the limit of detection. Except for an apparent oxidation product, the masses of the other detected metabolites could not be assigned to a single and frequently occurring biotransformation. Accurate mass determination and possible elemental compositions suggested that metabolism occurred through a combination of glutathionylation and defluorination. This was verified using accurate mass MS/MS. The use of accurate mass measurements and the derived suggestions for the elemental compositions were essential to elucidate this atypical metabolic pathway. A mass accuracy better than 8 ppm could be achieved for most assigned MS and MS/MS signals with intensities less than 6 cps in the spectra.     

Product ion mobility as a promising tool for assignment of positional isomers of drug metabolites

Travelling wave ion mobility spectrometry - mass spectrometry (TWIMS-MS) was evaluated as a tool for structural identification of metabolites of small molecule drugs in cases where the exact position of the biotransformation could not be identified by conventional tandem mass spectrometry. Test sets of compounds containing biotransformations at aromatic positions were analyzed. These present a problem for traditional MS methods since an atomic level localization of the biotransformation cannot normally be determined from MS(n) spectra. In addition to ion mobility measurements of the intact metabolite ions, ion mobility measurements of product ions were also made and the results compared with calculated values. This approach reduces the complexity of the problem, making theoretical calculations easier and more predictable when a modeled collision cross section (CCS) is required. A good relative correspondence between theoretical and measured CCSs was obtained allowing the identification of the exact position of the biotransformation. It was also demonstrated that authentic standards with substructures identical to those in the unknown can be used to assign the exact position of the biotransformation. In this approach the identification was based on the comparison of the drift times or CCSs for product ions of the standard, with those of the same product ions in the unknown.     

Two-dimensional liquid chromatography/mass spectrometry set-up for structural elucidation of metabolites in complex biological matrices

For absorption, distribution, metabolism and excretion (ADME) studies of drug candidates, mass spectrometry (MS) has become an indispensable tool for the characterization of biotransformation pathways. Samples from in vivo animal studies such as plasma, tissue extracts or excreta contain vast amounts of endogenous compounds. Therefore, the generation of metabolite patterns requires dedicated sample pre-treatment and sophisticated separation methods. Methodologies used for metabolite separation are often inappropriate for structure elucidation. Therefore, a two-dimensional liquid chromatography (LC) approach in combination with MS was developed. Study samples were analyzed using high-performance liquid chromatography (HPLC) for the generation of a qualitative and quantitative metabolite pattern (first dimension) with high reproducibility and recovery without extensive sample pre-treatment. Selected radioactive metabolite fractions were then applied to micro-HPLC with off-line radioactivity monitoring and subsequent MS detection (second dimension). Applying the two-dimensional HPLC/MS approach not only major metabolites could be identified, even minor and trace metabolites were characterized. The usage of sampled metabolite fractions allowed also the re-analysis of specific metabolites for additional investigations (e.g. H/D exchange experiments or product ion scanning experiments). It could be clearly shown that the two-dimensional HPLC/MS approach showed mass spectra with higher sensitivity and selectivity significantly improving the characterization of minor and trace metabolites in in vivo ADME studies.     

Identification and structural characterization of febuxostat metabolites in rat serum and urine samples using UHPLC–QTOF/MS

Febuxostat is a novel nonpurine type of highly selective xanthine oxidoreductase inhibitor. A rapid and sensitive ultra‐high‐performance liquid chromatography–quadrupole time‐of‐flight mass spectrometry method for simultaneous separation and determination of febuxostat and its metabolites in rat serum and urine was developed at various time points after oral administration to the rats. The febuxostat metabolites were predicted by biotransformation software and transformed to a personal compound database to quickly determine the possible metabolites from the MS1 data. The possibility of the MS/MS fragmentation was calculated by the Molecular Structure Correlator software. As a result, five phase I and two phase II metabolites in rat serum, and seven phase I and three phase II metabolites in rat urine were identified, of which four metabolites (M2, M5, M6, M7) have not been reported before. The metabolite toxicities are predicted, and the results are helpful for the design of new xanthine oxidoreductase inhibitors.     

Identification of new phase II metabolites of xanthohumol in rat in vivo biotransformation of hop extracts using high-performance liquid chromatography electrospray ionization tandem mass spectrometry

Polyphenolic compounds occurring in hop extracts and their phases I and II metabolites formed during in vivo rat biotransformation have been analyzed using HPLC/MS/MS with electrospray ionization (ESI). Two main groups of polyphenolics are present in the hops, i.e., xanthohumol related compounds and so called α- and β-bitter acids (humulones and lupulones). In our study, hybrid quadrupole-time-of-flight (QqTOF) analyzer is used for the identification of both natural phenolics and their metabolites due to the possibility of accurate mass measurements in full scan and tandem mass spectra supported by MSⁿ data obtained with the ion trap analyzer. Both ESI polarity modes are used for the determination of molecular weights based on [M+H]⁺ and [M−H]⁻ ions in the full scan spectra and the structural information in subsequent tandem mass spectra. The emphasis is given on the elemental composition determination of individual metabolites based on accurate masses typically better than 5 ppm even with the external calibration. Advanced software tools are used for the metabolite identification using the comparison of the blank chromatogram with the real incubation sample together with the software prediction and detection of possible metabolites. Chromatograms of rat incubations are also compared with chromatograms of pure rat feed, rat feed enriched with hop extracts and the placebo experiment. More than ten compounds originating from the hops are identified in rat feces, two of them belong to phase I metabolites and five compounds are phase II metabolites.     

In vivo metabolite detection and identification in drug discovery via LC-MS/MS with data-dependent scanning and postacquisition data mining

An important aspect in drug discovery is the early structural identification of the metabolites of potential new drugs. This gives information on the metabolically labile points in the molecules under investigation, suggesting structural modifications to improve their metabolic stability, and allowing an early safety assessment via the identification of metabolic activation products. From an analytical point of view, metabolite identification still remains a challenging task, especially for in vivo samples, in which they occur at trace levels together with high amounts of endogenous compounds. Here we describe a method, based on LC-ion trap tandem MS, for the rapid in vivo metabolite identification. It is based on the automatic, data-dependent acquisition of multiple product ion MS/MS scans, followed by a postacquisition search, within the entire MS/MS data set obtained, for specific neutral losses or marker ions in the tandem mass spectra of parent molecule and putative metabolites. One advantage of the method is speed, since it requires minimum sample preparation and all the necessary data can be obtained in one chromatographic run. In addition, it is highly sensitive and selective, allowing detection of trace metabolites even in the presence of a complex matrix. As an example of application, we present the studies of the in vivo metabolism of the compound MEN 15916 (1). The method allowed identification of monohydroxy ([M + H](+) = m/z 655), dihydroxy ([M + H](+) = m/z 671), and trihydroxy ([M + H](+) = m/z 687) metabolites, as well as some unexpected biotransformation products such as a carboxylic acid ([M + H](+) = m/z 669), a N-dealkylated metabolite ([M + H](+) = m/z 541), and its hydroxy-analog ([M + H](+) = m/z 557).     

High-throughput, accurate mass liquid chromatography/tandem mass spectrometry on a quadrupole time-of-flight system as a 'first-line' approach for metabolite identification studies

Throughput for drug metabolite identification studies has been increased significantly by the combined use of accurate mass liquid chromatography/tandem mass spectrometry (LC/MS/MS) data on a quadrupole time-of-flight (QTOF) system and targeted data analysis procedures. Employed in concert, these tools have led to the implementation of a semi-automated high-throughput metabolite identification strategy that has been incorporated successfully into lead optimization efforts in drug discovery. The availability of elemental composition data on precursor and all fragment ions in each spectrum has greatly enhanced confidence in ion structure assignments, while computer-based algorithms for defining sites of biotransformation based upon mass shifts of diagnostic fragment ions have facilitated identification of positions of metabolic transformation in drug candidates. Adoption of this technology as the 'first-line' approach for in vitro metabolite profiling has resulted in the analysis of as many as 21 new chemical entities on one day from diverse structural classes and therapeutic programs.     

Two‐injection workflow for a liquid chromatography/LTQ‐Orbitrap system to complete in vivo biotransformation characterization: demonstration with buspirone metabolite identification

The relatively high background matrix in in vivo samples typically poses difficulties in drug metabolite identification, and causes repeated analytical runs on unit resolution liquid chromatography/mass spectrometry (LC/MS) systems before the completion of biotransformation characterization. Ballpark parameter settings for the LTQ‐Orbitrap are reported herein that enable complete in vivo metabolite identification within two HPLC/MS injections on the hybrid LTQ‐Orbitrap data collection system. By setting the FT survey full scan at 60K resolution to trigger five dependent LTQ MS² scans, and proper parameters of Repeat Duration, Exclusion Duration and Repeat Count for the first run (exploratory), the Orbitrap achieved the optimal parallel data acquisition capability and collected maximum number of product ion scans. Biotransformation knowledge based prediction played the key role in exact mass ion extraction and multiple mass defect filtration when the initial data was processed. Meanwhile, product ion extraction and neutral loss extraction of the initial dependent data provided additional bonus in identifying metabolites. With updated parent mass list and the data‐dependent setting to let only the ions on the parent mass list trigger dependent scans, the second run (confirmatory) ensures that all precursor ions of identified metabolites trigger not only dependent product ion scans, but also at or close to the highest concentration of the eluted metabolite peaks. This workflow has been developed for metabolite identification of in vivo or ADME studies, of which the samples typically contain a high level of complex matrix. However, due to the proprietary nature of the in vivo studies, this workflow is presented herein with in vitro buspirone sample incubated with human liver microsomes (HLM). The major HLM‐mediated biotransformation on buspirone was identified as oxidation or hydroxylation since five mono‐ (+16 Da), seven di‐ (+32 Da) and at least three tri‐oxygenated (+48 Da) metabolites were identified. Besides the metabolites 1‐pyrimidinylpiperazine (1‐PP) and hydroxylated 1‐PP that formed by N‐dealkylation, a new metabolite M308 was identified as the result of a second N‐dealkylation of the pyrimidine unit. Two new metabolites containing the 8‐butyl‐8‐azaspiro[4,5]decane‐7,9‐dione partial structure, M240 and M254, were also identified that were formed apparently due to the first N‐dealkylation of the 1‐PP moiety. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantification of azoxystrobin and identification of two novel metabolites in lettuce via liquid chromatography–quadrupole-linear ion trap (QTRAP) mass spectrometry

Pesticide metabolite identification is gaining increased attention because of the interest in potential metabolite toxicity. Azoxystrobin is one of the most prevalent pesticide residues in foods in Europe. The majority of azoxystrobin metabolites have been identified using radiolabelled standards, which are either expensive or not readily available. Thus, alternative approaches for metabolite identification are desirable. Here, an LC-MS/MS method for quantifying azoxystrobin and identifying its metabolites using quadrupole-linear ion trap mass spectrometry is reported. Seven metabolites of azoxystrobin were identified 2 and 4 weeks after spraying lettuce with azoxystrobin. Among them, two metabolites are reported for the first time. The hydrolysis, reduction, hydroxylation, photoisomerisation and hydrolytic cleavage of ether bonds are identified as biotransformation processes involved in azoxystrobin metabolism in lettuce.     

In vitro interaction cocktail assay for nine major cytochrome P450 enzymes with 13 probe reactions and a single LC/MSMS run: analytical validation and testing with monoclonal anti-CYP antibodies

A sensitive and rugged LC/MSMS method was developed for a comprehensive in vitro metabolic interaction screening assay with N-in-1 approach reported earlier. A cocktail consisting of ten cytochrome P450 (CYP)-selective probe substrates with known kinetic, metabolic and interaction properties in vivo was incubated in a pool of human liver microsomes, and metabolites of melatonin (CYP1A2), coumarin (CYP2A6), bupropion (CYP2B6), amodiaquine (CYP2C8) tolbutamide (CYP2C9), omeprazole (CYP2C19 and CYP3A4), dextromethorphan (CYP2D6), chlorzoxazone (CYP2E1), midazolam (CYP3A4) and testosterone (CYP3A4) were simultaneously analysed with a single LC/MSMS run. Altogether, 13 metabolites and internal standard phenacetin were analysed in multiple reaction mode. Polarity switching mode was utilized to acquire negative ion mode electrospray data for hydroxychlorzoxazone and positive ionization data for the rest of the analytes. Fast gradient elution was applied, giving total injection cycle of 8 min. The method was modified for two different LC/MSMS systems, and was validated for linear range, detection limit, accuracy and precision for each metabolite. In addition, cocktail inhibition system was further tested using monoclonal anti-CYP antibodies as inhibitors for each probe reaction.     

Use of liquid chromatography/time-of-flight mass spectrometry and multivariate statistical analysis shows promise for the detection of drug metabolites in biological fluids

The process of metabolite identification is essential to the drug discovery and development process; this is usually achieved by liquid chromatography/tandem mass spectrometry (LC/MS/MS) or a combination of liquid chromatography/mass spectrometry (LC/MS) and nuclear magnetic resonance (NMR) spectroscopy. Metabolite identification is, however, a time-consuming process requiring an experienced skilled scientist. Multivariate statistical analysis has been used in the field of metabonomics to elucidate differences in endogenous biological profiling due to a toxic effect or a disease state. In this paper we show how a combination of liquid chromatography/time-of-flight mass spectrometry (LC/TOFMS) and multivariate statistical analysis can be used to detect drug metabolites in a biological fluid with no prior knowledge of the compound administered.     

Quantitative monitoring of tamoxifen in human plasma extended to 40 metabolites using liquid-chromatography high-resolution mass spectrometry: new investigation capabilities for clinical pharmacology

Liquid-chromatography (LC) high-resolution (HR) mass spectrometry (MS) analysis can record HR full scans, a technique of detection that shows comparable selectivity and sensitivity to ion transitions (SRM) performed with triple-quadrupole (TQ)-MS but that allows de facto determination of “all” ions including drug metabolites. This could be of potential utility in in vivo drug metabolism and pharmacovigilance studies in order to have a more comprehensive insight in drug biotransformation profile differences in patients. This simultaneous quantitative and qualitative (Quan/Qual) approach has been tested with 20 patients chronically treated with tamoxifen (TAM). The absolute quantification of TAM and three metabolites in plasma was realized using HR- and TQ-MS and compared. The same LC-HR-MS analysis allowed the identification and relative quantification of 37 additional TAM metabolites. A number of new metabolites were detected in patients’ plasma including metabolites identified as didemethyl-trihydroxy-TAM-glucoside and didemethyl-tetrahydroxy-TAM-glucoside conjugates corresponding to TAM with six and seven biotransformation steps, respectively. Multivariate analysis allowed relevant patterns of metabolites and ratios to be associated with TAM administration and CYP2D6 genotype. Two hydroxylated metabolites, α-OH-TAM and 4′-OH-TAM, were newly identified as putative CYP2D6 substrates. The relative quantification was precise (<20 %), and the semiquantitative estimation suggests that metabolite levels are non-negligible. Metabolites could play an important role in drug toxicity, but their impact on drug-related side effects has been partially neglected due to the tremendous effort needed with previous MS technologies. Using present HR-MS, this situation should evolve with the straightforward determination of drug metabolites, enlarging the possibilities in studying inter- and intra-patients drug metabolism variability and related effects.

Identification of new minor metabolites of penicillin G in human serum by multiple-stage tandem mass spectrometry

Liquid chromatography/mass spectrometry (LC/MS) and liquid chromatography/tandem mass spectrometry (LC/MS/MS) were applied to characterize drug metabolites. Although these two methods have overcome the identification and structural characterization of metabolites analysis, they remain time‐consuming processes. In this study, a novel multiple‐stage tandem mass spectrometric method (MSⁿ) was evaluated for identification and characterization of new minor metabolism profiling of penicillin G, one of the β‐lactam antibiotics, in human serum. Seven minor metabolites including five phase I metabolites and two phase II metabolites of penicillin G were identified by using data‐dependent LC/MSⁿ screening in one chromatographic run. The accuracy masses of seven identified metabolites of penicillin G were also confirmed by mass spectral calibration software (MassWorks?). The proposed data‐dependent LC/MSⁿ method is a powerful tool to provide large amounts of the necessary structural information to characterize minor metabolite in metabolism profiling. Copyright © 2010 John Wiley & Sons, Ltd.     

Metabolite identification of triptolide by data-dependent accurate mass spectrometric analysis in combination with online hydrogen/deuterium exchange and multiple data-mining techniques

Triptolide (TP), the primary active component of the herbal medicine Tripterygium wilfordii Hook F, has shown promising antileukemic and anti‐inflammatory activity. The pharmacokinetic profile of TP indicates an extensive metabolic elimination in vivo; however, its metabolic data is rarely available partly because of the difficulty in identifying it due to the absence of appropriate ultraviolet chromophores in the structure and the presence of endogenous interferences in biological samples. In the present study, the biotransformation of TP was investigated by improved data‐dependent accurate mass spectrometric analysis, using an LTQ/Orbitrap hybrid mass spectrometer in conjunction with the online hydrogen (H)/deuterium (D) exchange technique for rapid structural characterization. Accurate full‐scan MS and MS/MS data were processed with multiple post‐acquisition data‐mining techniques, which were complementary and effective in detecting both common and uncommon metabolites from biological matrices. As a result, 38 phase I, 9 phase II and 8 N‐acetylcysteine (NAC) metabolites of TP were found in rat urine. Accurate MS/MS data were used to support assignments of metabolite structures, and online H/D exchange experiments provided additional evidence for exchangeable hydrogen atoms in the structure. The results showed the main phase I metabolic pathways of TP are hydroxylation, hydrolysis and desaturation, and the resulting metabolites subsequently undergo phase II processes. The presence of NAC conjugates indicated the capability of TP to form reactive intermediate species. This study also demonstrated the effectiveness of LC/HR‐MSⁿ in combination with multiple post‐acquisition data‐mining methods and the online H/D exchange technique for the rapid identification of drug metabolites. Copyright © 2011 John Wiley & Sons, Ltd.     

Tentative identification of new metabolites of epimedin C by liquid chromatography-mass spectrometry

Epimedin C is one of the major bioactive constituents of Herba Epimedii. The aim of this study is to characterize and elucidate the structure of metabolites in the rat after administration of epimedin C. Metabolite identification was performed using a predictive multiple reaction monitoring-information dependent acquisition-enhanced product ion (pMRM-IDA-EPI) scan in positive ion mode on a hybrid triple quadrupole-linear ion trap mass spectrometer. A total of 18 metabolites were characterized by the changes in their protonated molecular masses, their MS/MS spectrum and their retention times compared with those of the parent drug. The results reveal possible metabolite profiles of epimedin C in rats; the metabolic pathways including hydrolysis, hydroxylation, dehydrogenation, demethylation and conjugation with glucuronic acid and different sugars were observed. This study provides a practical approach for rapidly identifying complicated metabolites, a methodology that could be widely applied for the structural characterization of metabolites of other compounds.     

Metabolite Profiling and Characterization of LW6, a Novel HIF-1α Inhibitor,as an Antitumor Drug Candidate in Mice

A novel HIF (hypoxia-inducible factor)-1α inhibitor, the (aryloxyacetylamino)benzoic acid derivative LW6, is an anticancer agent that inhibits the accumulation of HIF-1α. The aim of this study was to characterize and determine the structures of the metabolites of LW6 in ICR mice. Metabolite identification was performed using a predictive multiple reaction monitoring-information dependent acquisition-enhanced product ion (pMRM-IDA-EPI) method in negative ion mode on a hybrid triple quadrupole-linear ion trap mass spectrometer (QTRAP). A total of 12 metabolites were characterized based on their MS/MS spectra, and the retention times were compared with those of the parent compound. The metabolites were divided into five structural classes based on biotransformation reactions: amide hydrolysis, ester hydrolysis, mono-oxidation, glucuronidation, and a combination of these reactions. From this study, 2-(4-((3r,5r,7r)-adamantan-1-yl)phenoxy)acetic acid (APA, M7), the metabolite produced via amide hydrolysis, was found to be a major circulating metabolite of LW6 in mice. The results of this study can be used to improve the pharmacokinetic profile by lowering the clearance and increasing the exposure relative to LW6.     

Investigation of the biotransformation of melarsoprol by electrochemistry coupled to complementary LC/ESI–MS and LC/ICP–MS analysis

Melarsoprol is the only currently available drug for treatment of the late stage of African trypanosomiasis (sleeping sickness). Unfortunately, the arsenic-containing drug causes serious side effects, for which the mechanisms have not been elucidated so far. This investigation describes the study of the melarsoprol biotransformation processes by electrochemical (EC) techniques. Based on EC, potential oxidation reactions of melarsoprol are examined. Moreover, the reactivity of melarsoprol, its metabolite melarsen oxide, and their oxidation products toward the tripeptide glutathione and the proteins hemoglobin and human serum albumin is evaluated. The combination of different analytical techniques allows the identification as well as the quantification of the biotransformation products. The hyphenation of liquid chromatography (LC) and electrospray ionization mass spectrometry (ESI–MS) is applied for identification and structure elucidation, which implies the determination of exact masses and fragmentation patterns. For the selective detection of arsenic containing metabolites, LC coupled to inductively coupled plasma mass spectrometry is utilized. Based on the obtained data, the oxidative biotransformation of melarsoprol can be predicted, revealing novel species which have been suspected, but not been identified up to now. The results of the protein studies prove that melarsen oxide, the active derivative of melarsoprol, strongly binds to human hemoglobin and forms different adducts via the free cysteinyl groups of the hemoglobin α- and β-chain.