Mass defect filter technique and its applications to drug metabolite identification by high-resolution mass spectrometry

Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry

Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.

Integrated post-acquisition data processing strategy for rapid steroid sulfate characterization in Toad gall-bladder

LC-MS serves as a workhorse for chemical profile characterization of Chinese medicinal materials (CMMs) attributing to the ability of measuring fruitful MS/MS spectral information. However, it is laborious to extract the information belonging to the compounds-of-interest from the massive data matrixes even employing those well-defined post-acquisition data processing strategies. Here, efforts were devoted to propose an integrated strategy allowing rapid chemical homologs-focused data filtering through integrating the fit-for-purpose existing strategies, such as molecular weight imprinting (MWI), diagnostic fragment ion filtering (DFIF), neutral loss filtering (NLF), and isotope pattern filtering (IPF). Homologs-focused chemical characterization of a precious CMM namely Toad gall-bladder (Chinese name: Chandan) that is rich of diverse effective steroid sulfates, particularly bufogenin sulfates, bile acid sulfates and bilichol sulfates, was employed as a proof-of-concept. Recombinant human SULT2A1-catalyzed in vitro metabolism was undertaken to generate eight bufogenin sulfates to facilitate summarizing MS/MS spectral behaviors. After in-house data library construction and MS1 and MS2 spectral acquisition, data filtering was conducted as follows: 1) MWI and IPF was utilized in combination to capture deprotonated molecular ions and the 34S isotopic ions for the sulfates of those reported steroids; 2) m/z 79.9568 (SO3-·) and 96.9596 (HSO4-) were applied to DFIF; and 3) SO3 (79.9568 Da) served as the feature to achieve NLF. Those captured MS/MS information subsequently participated in tentatively structural annotation through applying those empirical mass fragmentation rules. As a result, 71 compounds including 7 bufogenin sulfates, 17 bile acid sulfates, 13 bilichol sulfates and a C-23 steroid sulfate were detected from Toad gall-bladder and thereof, 39 ones received plausible identities assignment. Above all, the steroid sulfates in Toad gall-bladder were profiled in depth, and more importantly, the proposed strategy should be a meaningful option for, but not limited to, submetabolome characterization in CMMs.

Rat Pharmacokinetics and In Vitro Metabolite Identification of KM-819, a Parkinson's Disease Candidate, Using LC-MS/MS and LC-HRMS

FAF1 (FAS-associated factor 1) is involved in the activation of Fas cell surface death receptors and plays a role in apoptosis and necrosis. In patients with Parkinson's disease, FAF1 is overexpressed in dopaminergic neurons in the substantia nigra. KM-819, an FAF1 inhibitor, has shown potential for preventing dopaminergic neuronal cell death, promoting the degradation of α-synuclein and preventing its accumulation. This study aimed to develop and validate a quantitative analytical method for determining KM-819 levels in rat plasma using liquid chromatography-tandem mass spectrometry. This method was then applied to pharmacokinetic (PK) studies in rats. The metabolic stability of KM-819 was assessed in rat, dog, and human hepatocytes. In vitro metabolite identification and metabolic pathways were investigated in rat, dog, and human hepatocytes. The structural analog of KM-819, namely N-[1-(4-bromobenzyl)-3,5-dimethyl-1H-pyrazol-4-yl]-2-(phenylsulfanyl) acetamide, served as the internal standard (IS). Proteins were precipitated from plasma samples using acetonitrile. Analysis was carried out using a reverse-phase C18 column with a mobile phase consisting of 0.1% formic acid in distilled water and 0.1% formic acid in acetonitrile. The analytical method developed for KM-819 exhibited linearity within the concentration range of 0.002-10 μg/mL in rat plasma. The precision and accuracy of the intra- and inter-day measurements were <15% for the lower limit of quantification (LLOQ) and all quality control samples. KM-819 demonstrated stability under various sample storage conditions (6 h at room temperature (25 °C), four weeks at -20 °C, three freeze-thaw cycles, and pretreated samples in the autosampler). The matrix effect and dilution integrity met the criteria set by the Food and Drug Administration and the European Medicines Agency. This sensitive, rapid, and reliable analytical method was successfully applied in pharmacokinetic studies in rats. Pharmacokinetic analysis revealed the dose-independent kinetics of KM-819 at 0.5-5 mg/kg, with a moderate oral bioavailability of ~20% in rats. The metabolic stability of KM-819 was also found to be moderate in rat, dog, and human hepatocytes. Metabolite identification in rat, dog, and human hepatocytes resulted in the discovery of six, six, and eight metabolites, respectively. Glucuronidation and mono-oxidation have been proposed as the major metabolic pathways. Overall, these findings contribute to a better understanding of the pharmacokinetic characteristics of KM-819, thereby aiding future clinical studies.

Rapid and comprehensive metabolites identification of 5-demethylnobiletin in rats using UPLC/Triple-TOF-MS/MS based on multiple mass defect filter and their neuroprotection against ferroptosis

5-Demethylnobiletin (5-deNOB) is a hydroxylated polymethoxyflavone (PMF) from Citrus plants known for its neurotrophic, anti-tumor, and antioxidant bioactivities. An ultra-high performance liquid chromatography coupled with triple-time of flight tandem mass spectrometry (UPLC/Triple-TOF-MS/MS) analysis combining with multiple mass defect filter (MMDF) and MetabolitePilot™ was employed to detect and characterize the metabolites of 5-deNOB in rats. A total of 130 metabolites were identified in rats, with 100, 25, 34, and 52 metabolites found in urine, plasma, bile, and feces, respectively. The major metabolic pathways involved demethylation, hydroxylation, dehydroxylation, glucuronidation, and methylation. In a bioassay of evaluating neuroprotection against ferroptosis in PC12 cells, most of the metabolites exhibited superior activity compared to 5-deNOB. These results provide valuable insights into the in vivo pharmacodynamic properties of 5-deNOB and offer potential active small molecules for neuroprotective therapy. Furthermore, the findings demonstrate the effectiveness of UPLC/Triple-TOF-MS/MS combined with MMDF and MetabolitePilot™ for rapid discovery and identification of the in vivo metabolites of natural products.

Dose-response technique combined with stable isotope tracing for drug metabolite profiling by using high-resolution mass spectrometry

Background: Mass spectrometry metabolomics-based data-processing approaches have been developed for drug metabolite profiling. However, existing approaches cannot be used to comprehensively identify drug metabolites with high efficacy. Methods: Herein, we propose a two-stage data-processing approach for effective and comprehensive drug metabolite identification. The approach combines dose-response experiments with stable isotope tracing (SIT). Rosiglitazone (ROS), commonly used to treat type 2 diabetes, was employed as a model drug. Results: In the first stage of data processing, 1,071 features exhibited a dose-response relationship among 22,597 features investigated. In the second stage, these 1,071 features were screened for isotope pairs, and 200 features with isotope pairs were identified. In time-course experiments, a large proportion of the identified features (69.5%: 137 out of 200 features) were confirmed to be possible ROS metabolites. We compared the validated features identified using our approach with those identified using a previously reported approach [the mass defect filter (MDF) combined with SIT] and discovered that most of the validated features (37 out of 42) identified using the MDF-SIT combination were also successfully identified using our approach. Of the 143 validated features identified by both approaches, 74 had a proposed structure of an ROS-structure-related metabolite; the other 34 features that contained a specific fragment of ROS metabolites were considered possible ROS metabolites. Interestingly, numerous ROS-structure-related metabolites were identified in this study, most of which were novel. Conclusion: The results reveal that the proposed approach can effectively and comprehensively identify ROS metabolites.

Discovery of Modified Metabolites, Secondary Metabolites, and Xenobiotics by Structure-Oriented LC-MS/MS

Exogenous compounds and metabolites derived from therapeutics, microbiota, or environmental exposures directly interact with endogenous metabolic pathways, influencing disease pathogenesis and modulating outcomes of clinical interventions. With few spectral library references, the identification of covalently modified biomolecules, secondary metabolites, and xenobiotics is a challenging task using global metabolomics profiling approaches. Numerous liquid chromatography-coupled mass spectrometry (LC-MS) small molecule analytical workflows have been developed to curate global profiling experiments for specific compound groups of interest. These workflows exploit shared structural moiety, functional groups, or elemental composition to discover novel and undescribed compounds through nontargeted small molecule discovery pipelines. This Review introduces the concept of structure-oriented LC-MS discovery methodology and aims to highlight common approaches employed for the detection and characterization of covalently modified biomolecules, secondary metabolites, and xenobiotics. These approaches represent a combination of instrument-dependent and computational techniques to rapidly curate global profiling experiments to detect putative ions of interest based on fragmentation patterns, predictable phase I or phase II metabolic transformations, or rare elemental composition. Application of these methods is explored for the detection and identification of novel and undescribed biomolecules relevant to the fields of toxicology, pharmacology, and drug discovery. Continued advances in these methods expand the capacity for selective compound discovery and characterization that promise remarkable insights into the molecular interactions of exogenous chemicals with host biochemical pathways.

Identification of Xenobiotic Biotransformation Products Using Mass Spectrometry-Based Metabolomics Integrated with a Structural Elucidation Strategy by Assembling Fragment Signatures

The identification of xenobiotic biotransformation products is crucial for delineating toxicity and carcinogenicity that might be caused by xenobiotic exposures and for establishing monitoring systems for public health. However, the lack of available reference standards and spectral data leads to the generation of multiple candidate structures during identification and reduces the confidence in identification. Here, a UHPLC-HRMS-based metabolomics strategy integrated with a metabolite structure elucidation approach, namely, FragAssembler, was proposed to reduce the number of false-positive structure candidates. biotransformation product candidates were filtered by mass defect filtering (MDF) and multiple-group comparison. FragAssembler assembled fragment signatures from the MS/MS spectra and generated the modified moieties corresponding to the identified biotransformation products. The feasibility of this approach was demonstrated by the three biotransformation products of di(2-ethylhexyl)phthalate (DEHP). Comprehensive identification was carried out, and 24 and 13 biotransformation products of two xenobiotics, DEHP and 4'-Methoxy-α-pyrrolidinopentiophenone (4-MeO-α-PVP), were annotated, respectively. The number of 4-MeO-α-PVP biotransformation product candidates in the FragAssembler calculation results was approximately 2.1 times lower than that generated by BioTransformer 3.0. Our study indicates that the proposed approach has great potential for efficiently and reliably identifying xenobiotic biotransformation products, which is attributed to the fact that FragAssembler eliminates false-positive reactions and chemical structures and distinguishes modified moieties on isomeric biotransformation products. The FragAssembler software and associated tutorial are freely available at https://cosbi.ee.ncku.edu.tw/FragAssembler/ and the source code can be found at https://github.com/YuanChihChen/FragAssembler.

Widespread occurrence of in-source fragmentation in the analysis of natural compounds by liquid chromatography-electrospray ionization mass spectrometry

RATIONALE

The in-source fragmentation (ISF) of analyte or co-eluting substances produces unintentional fragment ions, which hampers identification and quantification by liquid chromatography-mass spectrometry (LC/MS). Natural compounds derived from plants also contain fragile moieties that may undergo ISF. However, the characteristics of ISF of natural compounds in LC/MS are still unclear.

METHODS

The ISF behavior of 214 natural compounds was assayed in LC with Q/orbitrap MS in electrospray ionization (ESI) mode and the extent of ISF was evaluated.

RESULTS

Up to 82% of tested compounds underwent ISF and half of the tested natural compounds that contain more than one fragile moiety underwent successive and severe ISF to generate serial structurally related ISF products. The major ISF-altering moieties for natural compounds were hydroxyl, lactone, glycosyl and ether, resulting in neutral loss of H₂ O or CO, deglycosylation or cleavage of ether bond, respectively. Some compounds such as terpenoids underwent severe ISF and less than 1% parent form can be observed. For natural compounds, ISF products with similar structures are more likely to cause interference in analysis because the ISF products may share identical mass-to-charge ratio and similar MS² fragmentation patterns with precursor ions of the homologs in plants. Furthermore, severe ISF may cause a false negative in the identification of the parent form.

CONCLUSIONS

In summary, ISF was a highly frequent phenomenon for analysis of natural compounds by LC/ESI-MS, and extensive and successive ISF of natural products may cause misannotation and misidentification with homologs in plants. The study should raise awareness of ISF interference during the analysis of natural compounds.

Rapid screening and characterization of 2-(2-phenylethyl)chromones in agarwood by UHPLC-Q-Exactive Orbitrap-MS

The purpose of this study is to develop an improved comprehensive data filtering strategy, which was implemented primarily through the Microsoft Office platform's Excel software for rapid screening of potential 2-(2-phenylethyl)chromone (PEC) monomers and their dimers (PEC dimers) obtained from agarwood. A total of 108 PEC monomers and 30 PEC dimers in agarwood were characterized. In conclusion, the results obtained in this work could provide useful information for the future utilization of agarwood. In particular, it is the first time to conduct an in-depth analysis of the MS/MS fragmentation behavior of a large number of PEC monomers and PEC dimers, including the identification of substituent positions of them. The proposed data filtering strategy could improve the comprehensive characterization efficiency of complex components in spices.

A mass defect filtering combined background subtraction strategy for rapid screening and identification of metabolites in rat plasma after oral administration of Yindan Xinnaotong soft capsule

The absorbed prototypes and metabolites of traditional Chinese medicines (TCMs) serves an important part in pharmacological action and clinical effects. However, the comprehensive characterization of which is facing actual or possible rigorous challenges due to the lack of data mining methods and the complexity of metabolite samples. Yindan Xinnaotong soft capsule (YDXNT), a typical traditional Chinese medicine prescription consisting of extracts from 8 herbal medicines, is widely used for the treatment of angina pectoris and ischemic stroke in the clinic. This study established a systematic data mining strategy based on ultra-high performance liquid chromatography tandem quadrupole-time-of-fight mass spectrometry (UHPLC-Q-TOF MS) for comprehensive metabolite profiling of YDXNT in rat plasma after oral administration. The multi-level feature ion filtration strategy was primarily conducted through the full scan MS data of plasma samples. All potential metabolites were rapidly fileted out from the endogenous background interference based on the background subtract and the chemical type specifically mass defect filter (MDF) windows including flavonoids, ginkgolides, phenolic acids, saponins, and tanshinones. As the MDF windows of certain types were overlapped, the screened-out potential metabolites were deeply characterized and identified according to their retention times (RT), integrating neutral loss filtering (NLF), diagnostic fragment ions filtering (DFIF), and further confirmed by reference standards. Thus, a total of 122 compounds, consisting of 29 prototype components (16 confirmed with reference standards) and 93 metabolites had been identified. This study provides a rapid and robust metabolite profiling method for researching complicated traditional Chinese medicine prescriptions.

A mass balance study of [14C]SHR6390 (dalpiciclib), a selective and potent CDK4/6 inhibitor in humans

SHR6390 (dalpiciclib) is a selective and effective cyclin-dependent kinase (CDK) 4/6 inhibitor and an effective cancer therapeutic agent. On 31 December 2021, the new drug application was approved by National Medical Product Administration (NMPA). The metabolism, mass balance, and pharmacokinetics of SHR6390 in 6 healthy Chinese male subjects after a single oral dose of 150 mg [14C]SHR6390 (150 µCi) in this research. The Tmax of SHR6390 was 3.00 h. In plasma, the t1/2 of SHR6390 and its relative components was approximately 17.50 h. The radioactivity B/P (blood-to-plasma) AUC0-t ratio was 1.81, indicating the preferential distribution of drug-related substances in blood cells. At 312 h after administration, the average cumulative excretion of radioactivity was 94.63% of the dose, including 22.69% in urine and 71.93% in stool. Thirteen metabolites were identified. In plasma, because of the low level of radioactivity, only SHR6390 was detected in pooled AUC0-24 h plasma. Stool SHR6390 was the main component in urine and stool. Five metabolites were identified in urine, and 12 metabolites were identified in stool. Overall, faecal clearance is the main method of excretion.

Critical assessment of the Kendrick mass defect analysis as an innovative approach to process high resolution mass spectrometry data for environmental applications

The growing application of high resolution mass spectrometry (HRMS) over the last decades has dramatically improved our knowledge about the occurrence of environmental contaminants. However, most of the compounds detected remain unknown and the large volume of data generated requires specific processing approaches. Therefore, this study presents the concepts of mass defect (MD), Kendrick mass (KM) and Kendrick mass defect (KMD) to the expert and non-expert reader along with relevant examples of applications in environmental HRMS data processing. A preliminary bibliometric overview indicates that the potential benefits of KMD analysis are rather overlooked in environmental science. In practice, a simple calculation allows transforming a mass from the IUPAC system (normalized so that the mass of ¹²C is exactly 12) to its corresponding KM normalized on a specific moiety such as CH₂ (the mass of CH₂ is exactly 14). Then, plotting the KMD according to the nominal KM allows revealing groups of compounds that differ only by their number of CH₂ moieties. For instance, data processing using KM and KMD was proven particularly useful to characterize natural organic matter in a sample, to reveal the occurrence of polymers as well as poly/perfluorinated alkylated substances (PFASs), and to search for transformation products (TPs) of a given chemical.

High-Throughput Metabolic Soft-Spot Identification in Liver Microsomes by LC/UV/MS: Application of a Single Variable Incubation Time Approach

CYP-mediated fast metabolism may lead to poor bioavailability, fast drug clearance and significant drug interaction. Thus, metabolic stability screening in human liver microsomes (HLM) followed by metabolic soft-spot identification (MSSID) is routinely conducted in drug discovery. Liver microsomal incubations of testing compounds with fixed single or multiple incubation time(s) and quantitative and qualitative analysis of metabolites using high-resolution mass spectrometry are routinely employed in MSSID assays. The major objective of this study was to develop and validate a simple, effective, and high-throughput assay for determining metabolic soft-spots of testing compounds in liver microsomes using a single variable incubation time and LC/UV/MS. Model compounds (verapamil, dextromethorphan, buspirone, mirtazapine, saquinavir, midazolam, amodiaquine) were incubated at 3 or 5 µM with HLM for a single variable incubation time between 1 and 60 min based on predetermined metabolic stability data. As a result, disappearances of the parents were around 20-40%, and only one or a few primary metabolites were generated as major metabolite(s) without notable formation of secondary metabolites. The unique metabolite profiles generated from the optimal incubation conditions enabled LC/UV to perform direct quantitative estimation for identifying major metabolites. Consequently, structural characterization by LC/MS focused on one or a few major primary metabolite(s) rather than many metabolites including secondary metabolites. Furthermore, generic data-dependent acquisition methods were utilized to enable Q-TOF and Qtrap to continuously record full MS and MS/MS spectral data of major metabolites for post-acquisition data-mining and interpretation. Results from analyzing metabolic soft-spots of the seven model compounds demonstrated that the novel MSSID assay can substantially simplify metabolic soft-spot identification and is well suited for high-throughput analysis in lead optimization.

Time-Series-Dependent Global Data Filtering Strategy for Mining and Profiling of Xenobiotic Metabolites in a Dynamic Complex Matrix: Application to Biotransformation of Flavonoids in the Extract of Ginkgo biloba by Gut Microbiota

Efficient characterization of xenobiotic metabolites and their dynamics in a changing complex matrix remains difficult. Herein, we proposed a time-series-dependent global data filtering strategy for the rapid and comprehensive characterization of xenobiotic metabolites and their dynamic variation based on metabolome data. A set of data preprocessing methods was used to screen potential xenobiotic metabolites, considering the differences between the treated and control groups and the fluctuations over time. To further identify metabolites of the target, an in-house accurate mass database was constructed by potential metabolic pathways and applied. Taking the extract of Ginkgo biloba (EGB) co-incubated with gut microbiota as an example, 107 compounds were identified as flavonoid-derived metabolites (including 67 original from EGB and 40 new) from 7468 ions. Their temporal metabolic profiles and regularities were also investigated. This study provided a systematic and feasible method to elucidate and profile xenobiotic metabolism.

Nontargeted screening of veterinary drugs and their metabolites in milk based on mass defect filtering using liquid chromatography-high-resolution mass spectrometry

The development of nontargeted screening strategy for veterinary drugs and their metabolites is very important for food safety. In this study, a nontargeted screening strategy was developed to find the potentially hazardous substances based on mass defect filtering (MDF) using liquid chromatography-high-resolution mass spectrometry. First, the drug metabolites of 112 veterinary drugs from seven classes of antimicrobials were predicted. Second, three MDF models were established, including the traditional rectangular MDF, the enhanced parallelogram MDF, and the polygonal MDF. Finally, the strategy was applied to nontargeted screening of veterinary drugs in 36 milk samples. The polygonal MDF model based on the distribution area of parent drugs and their metabolites showed a better filtering effect. After removing food components and performing MDF, about 10% of the substances remained, and four veterinary drugs and six drug metabolites were discovered and identified, showing the effectiveness of this strategy. The nontargeted screening strategy can rapidly remove interfering substances and find the suspected compounds. It can also be used for nontargeted screening of veterinary drugs and their metabolites in other food matrices.

Generic approach for the discovery of drug metabolites in horses based on data-dependent acquisition by liquid chromatography high-resolution mass spectrometry and its applications to pharmacokinetic study of daprodustat

In drug metabolism studies in horses, non-targeted analysis by means of liquid chromatography coupled with high-resolution mass spectrometry with data-dependent acquisition (DDA) has recently become increasingly popular for rapid identification of potential biomarkers in post-administration biological samples. However, the most commonly encountered problem is the presence of highly abundant interfering components that co-elute with the target substances, especially if the concentrations of these substances are relatively low. In this study, we evaluated the possibility of expanding DDA coverage for the identification of drug metabolites by applying intelligently generated exclusion lists (ELs) consisting of a set of chemical backgrounds and endogenous substances. Daprodustat was used as a model compound because of its relatively lower administration dose (100 mg) compared to other hypoxia-inducible factor stabilizers and the high demand in the detection sensitivity of its metabolites at the anticipated lower concentrations. It was found that the entire DDA process could efficiently identify both major and minor metabolites (flagged beyond the pre-set DDA threshold) in a single run after applying the ELs to exclude 67.7-99.0% of the interfering peaks, resulting in a much higher chance of triggering DDA to cover the analytes of interest. This approach successfully identified 21 metabolites of daprodustat and then established the metabolic pathway. It was concluded that the use of this generic intelligent "DDA + EL" approach for non-targeted analysis is a powerful tool for the discovery of unknown metabolites, even in complex plasma and urine matrices in the context of doping control.

Global analysis of qualitative and quantitative metabolism of Notoginsenoside R1 in rat liver-brain-gut axis based on LC-IT-TOF/MS combing mMDF strategy

BACKGROUND

The metabolism study of active components for traditional Chinese medicine (TCM) in target organs is conducive to clarify the authentic active ingredients. Notoginsenoside R1 (NG-R1), one of the bioactive components of Panax notoginsenoside (PNS), is commonly acknowledged as the characteristic marker of PNS. However, the metabolism of NG-R1 in target organs has not been clarified yet due to the lack of robust technique and approach.

PURPOSE

The present study aimed to develop a reliable and efficient strategy and technology for revealing the qualitative and quantitative metabolism of active components of TCMs in target organs, and to clarify the biotransformation of NG-R1 in liver-brain-intestinal axis.

METHODS

The metabolic transformation of NG-R1 in the brain gut axis was investigated in the in vitro incubation system of fresh rat brain, liver homogenate, and intestinal flora. To quickly lock the target metabolites, we set the mass defect filter (MDF) in different ranges to screen metabolites with different molecular weight (MW). This strategy was defined as multi-stage MDF (mMDF). In addition, we performed relative quantitative analysis on all metabolites according to the peak area acquired by LC-IT-TOF/MS to overcome the challenge that metabolites are difficult to be quantified due to the lack of standards.

RESULTS

When MDF was set at 0.50 to 0.65 to screen metabolites with MW of 900 to 1200 Da, 6 novel metabolites were quickly found, and then identified as glucuronic acid binding, oxidation, dehydrogenation, methylation and hydrogenation products according to their LC and MS characteristics. When setting MDF at 0.42 - 0.52, 6 metabolites with MW of 600 to 900 Da were effectively screened and identified as Rg1, NG-R2, Rh1, Rg1+CH₂+2H and Rg1+CH₂. To screen the metabolites with MW of 300 to 600 Da, MDF was set at 0.25 - 0.42, and 4 novel metabolites were screened rapidly. The results of quantitative metabolism suggested that intestinal flora was the main metabolic site of NG-R1 in rat, and more than 60% of NG-R1 was converted to Rg1 by deglycosylation in the intestinal flora.

CONCLUSION

The mMDF strategy can significantly improve the research efficiency of qualitative metabolism of saponins. Although NG-R1 could be transformed into a variety of metabolites in rat liver and brain homogenate, it still existed mainly in prototype form. In the rat flora, NG-R1 mainly existed in the form of deglycosylated metabolite Rg1.

A Systematic Strategy for the Characterization of 2,3,5,4'-Tetrahydroxystilbene-2-O-β-d-glucoside Metabolites In Vivo by Ultrahigh Performance Liquid Chromatography Coupled with a Q Exactive-Orbitrap Mass System

2,3,5,4'-Tetrahydroxystilbene-2-O-β-d-glucoside (THSG), a polyphenol stilbene compound, is the main active constituent in Polygonum multiflorum. In this study, a comprehensive analytical strategy was developed for the characterization of THSG metabolites in vivo (rat plasma, bile, urine, heart, liver, spleen, lung, kidney, and stomach) utilizing ultrahigh performance liquid chromatography coupled with Q Exactive hybrid quadrupole-Orbitrap mass spectrometry (UHPLC-Q Exactive-Orbitrap MS) based on multiple data-processing techniques. As a result, a total of 75 metabolites were characterized in bio-samples, and calculated Clog P values were further employed to assign the chemical structures of some isomers. Glucoside hydrolysis, hydrogenation, hydroxylation, glucuronide conjugation, and sulfate conjugation would be the major metabolic pathways of THSG. It appeared that most metabolites would generally undergo phase I reactions followed by phase II reactions. These results provided valuable information for in-depth understanding of the safety and efficacy of THSG and showed a valuable methodology for metabolic characterization.

Mass Defect Filtering-Oriented Identification of Resin Glycosides from Root of Convolvulus scammonia Based on Quadrupole-Orbitrap Mass Spectrometer

This work aimed to develop and evaluate a post-acquisition data processing strategy, referred to as a mass defect filter (MDF), for rapid target the resin glycosides in root of Convolvulus scammonia by setting mass rang and mass defect range from high-resolution MS data. The full-scan mass data were acquired by high-performance liquid chromatography coupled with Q Exactive Plus hybrid quadrupole-orbitrap mass spectrometer that featured high resolution, mass accuracy, and sensitivity. To screen resin glycosides, three parent filter m/z 871, m/z 853, and m/z 869 combined with diagnostic fragment ions (DFIs) approach were applied to remove the interference from complex herbal extract. The targeted components were characterized based on detailed fragment ions. Using this approach, 80 targeted components, including 22 glycosidic acids and 58 resin glycosides were tentatively identified. The present results suggested that the proposed MDF strategy would be adaptable to the analysis of complex system in relevant filed.

A database-guided integrated strategy for comprehensive chemical profiling of traditional Chinese medicine

A comprehensive chemical profiling of traditional Chinese medicine is the basic issue for further pharmacological research and quality assessment. To facilitate chemical identification and potential components discovery, the present study proposed an integrated identification strategy guided by a self-built component database constructed from literatures to carry out the global profiling of complex matrixes. Lanqin Oral Liquid was applied as example to validate the feasibility of this strategy. Based on LQL Component Database containing 710 compounds, modified MDF windows was established to extract the interested analogues, isoquinoline alkaloids, flavonoids and iridoid glycosides, according to their regular integral masses and mass defect. For compounds with characteristic substructures, such as quinic acids, crocins and some glycoside derivatives, the associated neutral losses and diagnostic fragment ions were collected to assist in profiling. Directly matching the m/z or formulas in database was proposed to components with limited regularity of accurate masses and substructures, like indole alkaloids, sesquiterpenes and some nucleosides. Eventually, 170 ions of 1038 precursor ions were identified or temporarily deduced, including 59 alkaloids, 36 flavonoids, 48 terpenoids, 24 organic acids and their derivatives, 2 oligosaccharides, and 1 lignans. Among them, 52 putative compounds were confirmed by chemical standards. The results indicated that the database-oriented identification strategy could locate potential components quickly and eliminate interfering ions, which have the potential for in-depth analysis of compounds.

Spectrum-Effect Relationship Analysis of Bioactive Compounds in Zanthoxylum nitidum (Roxb.) DC. by Ultra-High Performance Liquid Chromatography Mass Spectrometry Coupled With Comprehensive Filtering Approaches

Zanthoxylum nitidum (Roxb.) DC. (ZN), with strong effects of anti-inflammation and antioxidant activities is treated as a core herb in traditional Chinese medicine (TCM) preparation for treating stomachache, toothache, and rheumatoid arthritis. However, the active ingredients of ZN are not fully clarified due to its chemical complexity. In the present study, a double spectrum–effect analysis strategy was developed and applied to explore the bioactive components in herbs, and ZN was used as an example. Here, the chemical components in ZN were rapidly and comprehensively profiled based on the mass defect filtering-based structure classification (MDFSC) and diagnostic fragment-ion-based extension approaches. Furthermore, the fingerprints of 20 batches of ZN samples were analyzed by high-performance liquid chromatography, and the anti-inflammatory and antioxidant activities of the 20 batches of ZN samples were studied. Finally, the partial least squares regression (PLSR), gray relational analysis models, and Spearman’s rank correlation coefficient (SRCC) were applied to discover the bioactive compounds in ZN. As a result, a total of 48 compounds were identified or tentatively characterized in ZN, including 35 alkaloids, seven coumarins, three phenolic acids, two flavonoids, and one lignan. The results achieved by three prediction models indicated that peaks 4, 12, and 17 were the potential anti-inflammatory compounds in ZN, whereas peaks 3, 5, 7, 12, and 13 were involved in the antioxidant activity. Among them, peaks 4, 5, 7, and 12 were identified as nitidine, chelerythrine, hesperidin, and oxynitidine by comparison with the standards and other references. The data in the current study achieved by double spectrum–effect analysis strategy had great importance to improve the quality standardization of ZN, and the method might be an efficiency tool for the discovery of active components in a complex system, such as TCMs.

Mass Defect Filter for Removing Noise and Detector Oscillation Artifacts in Centroided Time-of-Flight Mass Spectra

Spurious peaks in centroided mass spectra resulting from detector oscillation or "ringing" can be identified by their unusual mass defects. Mass defect plots (fractional m/z vs measured m/z) for the single-charge mass spectrum of a pure compound show data points falling along lines with well-defined slopes. Detector oscillation and electronic noise peaks were removed from database spectra of pure compounds and mixtures by eliminating points outside two standard deviations of the slope of the major peaks. No loss of chemical information was observed, even for compounds with isobaric fragment peaks.

Investigations into the stability of 17 psychoactive drugs in a "simulated postmortem blood" model

In the postmortem environment some drugs and metabolites may degrade due to microbial activity, even forming degradation products that are not produced in humans. Consequently, under- or over-estimation of perimortem drug concentrations or even false negatives are possible when analyzing postmortem specimens. Therefore, understanding whether medications may be susceptible to microbial degradation is critical in order to ensure that reliable detection and quantitation of drugs and their degradation products is achieved in toxicology screening methods. In this study, a "simulated postmortem blood" model constructed of antemortem human whole blood inoculated with a broad population of human fecal microorganisms was used to investigate the stability of 17 antidepressant and antipsychotic drugs. Microbial communities present in the experiments were determined to be relevant to postmortem blood microorganisms by 16S rRNA sequencing analyses. After 7 days of exposure to the community at 37 °C, drug stability was evaluated using liquid chromatography coupled with diode array detection (LC-DAD) and with quadrupole time of flight mass spectrometry (LC-QTOF-MS). Most of the investigated drugs were found to be stable in inoculated samples and non-inoculated controls. However, the 1,2-benzisothiazole antipsychotics, ziprasidone and lurasidone, were found to degrade at a rate comparable to the known labile control, risperidone. In longer experiments (seven to twelve months), where specimens were stored at -20 °C, 4 °C, and ambient temperature, N-dealkylation degradation products were detected for many of the drugs, with greater formation in specimens stored at -20 °C than at 4 °C.

Developments in high-resolution mass spectrometric analyses of new psychoactive substances

The proliferation of new psychoactive substances (NPS) has necessitated the development and improvement of current practices for the detection and identification of known NPS and newly emerging derivatives. High-resolution mass spectrometry (HRMS) is quickly becoming the industry standard for these analyses due to its ability to be operated in data-independent acquisition (DIA) modes, allowing for the collection of large amounts of data and enabling retrospective data interrogation as new information becomes available. The increasing popularity of HRMS has also prompted the exploration of new ways to screen for NPS, including broad-spectrum wastewater analysis to identify usage trends in the community and metabolomic-based approaches to examine the effects of drugs of abuse on endogenous compounds. In this paper, the novel applications of HRMS techniques to the analysis of NPS is reviewed. In particular, the development of innovative data analysis and interpretation approaches is discussed, including the application of machine learning and molecular networking to toxicological analyses.

Constellation: An Open-Source Web Application for Unsupervised Systematic Trend Detection in High-Resolution Mass Spectrometry Data

The increasing popularity of high-resolution mass spectrometry has led to many custom software solutions to process, interpret, and reveal information from high-resolution mass spectra. Although there are numerous software packages for peak-picking, calibration, and formula-finding, there are additional layers of information available when it comes to detecting repeated motifs from polymers or molecules with repeating structures or products of chemical or biochemical transformations that exhibit systematic, serial chemical changes of mass. Constellation is an open-source, Python-based web application that allows the user first to expand their high-resolution mass data into the mass defect space, after which a trend finding algorithm is used for supervised or unsupervised detection of repeating motifs. Many adjustable parameters allow the user to tailor their trend-search to target particular chemical moieties or repeating units, or search for all potential motifs within certain limits. The algorithm has a built-in optimization routine to provide a good starting point for the main trend finding parameters before user customization. Visualization tools allow interrogation of the data and any trends/patterns to a highly specific degree and save publication-quality images directly from the interface. As Constellation is deployed as a web application, it is easily used by anyone with a web browser; no software download or high-powered computer is required, as computations are performed on a remote high-powered data server run by our group.

Ultra-high pressure liquid chromatography coupled to travelling wave ion mobility-time of flight mass spectrometry for the screening of pharmaceutical metabolites in wastewater samples: Application to antiretrovirals

The presence of pharmaceutical compounds in the aquatic environment is a significant environmental health concern, which is exacerbated by recent evidence of the contribution of drug metabolites to the overall pharmaceutical load. In light of a recent report of the occurrence of metabolites of antiretroviral drugs (ARVDs) in wastewater, we investigate in the present work the occurrence of further ARVD metabolites in samples obtained from a domestic wastewater treatment plant in the Western Cape, South Africa. Pharmacokinetic data indicate that ARVDs are biotransformed into several positional isomeric metabolites, only two of which have been reported wastewater samples. Given the challenges associated with the separation and identification of isomeric species in complex wastewater samples, a method based on liquid chromatography hyphenated to ion mobility spectrometry-high resolution mass spectrometry (LC-IMS-HR-MS) was implemented. Gradient LC separation was achieved on a sub-2 µm reversed phase column, while the quadrupole-time-of-flight MS was operated in data independent acquisition (DIA) mode to increase spectral coverage of detected features. A mass defect filter (MDF) template was implemented to detect ARVD metabolites with known phase I and phase II mass shifts and fractional mass differences and to filter out potential interferents. IMS proved particularly useful in filtering the MS data for co-eluting species according to arrival time to provide cleaner mass spectra. This approach allowed us to confirm the presence of two known hydroxylated efavirenz and nevirapine metabolites using authentic standards, and to tentatively identify a carboxylate metabolite of abacavir previously reported in literature. Furthermore, three hydroxylated-, two sulphated and one glucuronidated metabolite of efavirenz, two hydroxylated metabolites of nevirapine and one hydroxylated metabolite of ritonavir were tentatively or putatively identified in wastewater samples for the first time. Assignment of the metabolites is discussed in terms of high resolution fragmentation data, while collisional cross section (CCS) values measured for the detected analytes are reported to facilitate further work in this area.

Mass spectrometry based approaches and strategies in bioanalysis for qualitative and quantitative analysis of pharmaceutically relevant molecules

Mass spectrometry plays an essential role in qualitative and quantitative analysis of pharmaceutically relevant molecules. The present review summarizes some the most common applications of LC-MS for the characterization of therapeutic low-molecular-weight compounds, peptides and proteins, and oligonucleotides using low-resolution and high-resolution tandem mass spectrometry. In addition, the benefit of multistage MS, differential ion mobility, and data independent acquisition is emphasized. At last, the potential of coupling MS with novel interfaces for high-throughput analysis is discussed.

Review on in vivo profiling of drug metabolites with LC-MS/MS in the past decade

Metabolite profiling is an indispensable part of drug discovery and development, enabling a comprehensive understanding of the drug's metabolic behavior. Liquid chromatography-mass spectrometry facilitates metabolite profiling by reducing sample complexity and providing high sensitivity. This review discusses the in vivo metabolite profiling involving LC-MS/MS and the utilization of QTOF, QQQ mass analyzers with a particular emphasis on a mass filter. Further, a summary of sample extraction procedures in biological matrices such as plasma, urine, feces, serum and hair as in vivo samples are outlined. toward the end, we present 15 case studies in biological matrices and their LC-MS/MS conditions to understand the metabolic disposition.

Pharmacokinetics, mass balance, and metabolism of [14C]vicagrel, a novel irreversible P2Y12 inhibitor in humans

Vicagrel, a novel irreversible P2Y₁₂ receptor inhibitor, is undergoing phase III trials for the treatment of acute coronary syndromes in China. In this study, we evaluated the pharmacokinetics, mass balance, and metabolism of vicagrel in six healthy male Chinese subjects after a single oral dose of 20 mg [¹⁴C]vicagrel (120 µCi). Vicagrel absorption was fast (T_max = 0.625 h), and the mean t_1/2 of vicagrel-related components was ~38.0 h in both plasma and blood. The blood-to-plasma radioactivity AUC_inf ratio was 0.55, suggesting preferential distribution of drug-related material in plasma. At 168 h after oral administration, the mean cumulative excreted radioactivity was 96.71% of the dose, including 68.03% in urine and 28.67% in feces. A total of 22 metabolites were identified, and the parent vicagrel was not detected in plasma, urine, or feces. The most important metabolic spot of vicagrel was on the thiophene ring. In plasma pretreated with the derivatization reagent, M9-2, which is a methylated metabolite after thiophene ring opening, was the predominant drug-related component, accounting for 39.43% of the radioactivity in pooled AUC_0-8 h plasma. M4, a mono-oxidation metabolite upon ring-opening, was the most abundant metabolite in urine, accounting for 16.25% of the dose, followed by M3-1, accounting for 12.59% of the dose. By comparison, M21 was the major metabolite in feces, accounting for 6.81% of the dose. Overall, renal elimination plays a crucial role in vicagrel disposition, and the thiophene ring is the predominant metabolic site.

Recent advances in identifying and utilizing metabolites of selected doping agents in human sports drug testing

Probing for evidence of the administration of prohibited therapeutics, drugs and/or drug candidates as well as the use of methods of doping in doping control samples is a central assignment of anti-doping laboratories. In order to accomplish the desired analytical sensitivity, retrospectivity, and comprehensiveness, a considerable portion of anti-doping research has been invested into studying metabolic biotransformation and elimination profiles of doping agents. As these doping agents include lower molecular mass drugs such as e.g. stimulants and anabolic androgenic steroids, some of which further necessitate the differentiation of their natural/endogenous or xenobiotic origin, but also higher molecular mass substances such as e.g. insulins, growth hormone, or siRNA/anti-sense oligonucleotides, a variety of different strategies towards the identification of employable and informative metabolites have been developed. In this review, approaches supporting the identification, characterization, and implementation of metabolites exemplified by means of selected doping agents into routine doping controls are presented, and challenges as well as solutions reported and published between 2010 and 2020 are discussed.

Improving the Screening Analysis of Pesticide Metabolites in Human Biomonitoring by Combining High-Throughput In Vitro Incubation and Automated LC-HRMS Data Processing

There is a current need to monitor human exposure to a large number of pesticides and other chemicals of emerging concern (CECs). This requires screening analysis with high confidence for these compounds and their metabolites in complex matrices, which is hampered by the fact that no reference standards are available for most metabolites. We address this challenge by a high-throughput workflow based on incubation of pesticides (or other CECs) with human liver S9, followed by solid-phase extraction, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) analysis, and automated data processing to generate a database (retention time, precursor m/z, and MS² spectral library) for the annotation in human samples. The metabolite prioritization consists of statistical comparisons and mass defect and m/z range filtering to obtain a subset of probable phase I metabolites, for which molecular formulas and likely metabolic transformation are retrieved. We tested the workflow on 22 pesticides, for which we could determine 91 metabolite molecular formulas which are only partly covered by the literature and/or predicted by in silico metabolization. Our workflow allows for an efficient generation of metabolite reference information, which can be used directly for annotating LC-HRMS data from human samples. A full structure elucidation of individual metabolites can be limited to those being actually present in human samples.

Insight into chemical basis of traditional Chinese medicine based on the state-of-the-art techniques of liquid chromatography-mass spectrometry

Traditional Chinese medicine (TCM) has been an indispensable source of drugs for curing various human diseases. However, the inherent chemical diversity and complexity of TCM restricted the safety and efficacy of its usage. Over the past few decades, the combination of liquid chromatography with mass spectrometry has contributed greatly to the TCM qualitative analysis. And novel approaches have been continuously introduced to improve the analytical performance, including both the data acquisition methods to generate a large and informative dataset, and the data post-processing tools to extract the structure-related MS information. Furthermore, the fast-developing computer techniques and big data analytics have markedly enriched the data processing tools, bringing benefits of high efficiency and accuracy. To provide an up-to-date review of the latest techniques on the TCM qualitative analysis, multiple data-independent acquisition methods and data-dependent acquisition methods (precursor ion list, dynamic exclusion, mass tag, precursor ion scan, neutral loss scan, and multiple reaction monitoring) and post-processing techniques (mass defect filtering, diagnostic ion filtering, neutral loss filtering, mass spectral trees similarity filter, molecular networking, statistical analysis, database matching, etc.) were summarized and categorized. Applications of each technique and integrated analytical strategies were highlighted, discussion and future perspectives were proposed as well.

A strategy combining solid-phase extraction, multiple mass defect filtering and molecular networking for rapid structural classification and annotation of natural products: characterization of chemical diversity in Citrus aurantium as a case study

Medicinal plants are complex chemical systems containing thousands of secondary metabolites. The rapid classification and characterization of the components in medicinal plants using mass spectrometry (MS) remains an immense challenge. Herein, a novel strategy is presented for MS through the combination of solid-phase extraction (SPE), multiple mass defect filtering (MMDF) and molecular networking (MN). This strategy enables efficient classification and annotation of natural products. When combined with SPE and MMDF, the improved analytical method of MN can perform the rapid annotation of diverse natural products in Citrus aurantium according to the tandem mass spectrometry (MS/MS) fragments. In MN, MS2LDA can be initially applied to recognize substructures of natural products, according to the common fragmentation patterns and neutral losses in multiple MS/MS spectra. MolNetEnhancer was adopted here to obtain chemical classifications provided by ClassyFire. The results suggest that the integrated SPE-MMDF-MN method was capable of rapidly annotating a greater number of natural products from Citrus aurantium than the classical MN strategy alone. Moreover, SPE and MMDF enhanced the effectiveness of MN for annotating, classifying and distinguishing different types of natural products. Our workflow provides the foundation for the automated, high-throughput structural classification and annotation of secondary metabolites with various chemical structures. The developed approach can be widely applied in the analysis of constituents in natural products.

Co-occurring Congeners Reveal the Position of Enantiomeric Amino Acids in Nonribosomal Peptides

The absolute configuration of the constituent amino acids in microbial nonribosomal peptides is typically determined by Marfey's method after total hydrolysis of the peptide. A challenge to structure elucidation arises when both d and l enantiomeric configurations of an amino acid are present. Determining the actual position of each amino acid enantiomer within the peptide sequence typically requires laborious approaches based on peptide partial hydrolysis or even total synthesis of the possible diastereomers. Herein, an alternative solution is discussed based on the homogeneous backbone chirality that governs all peptides biosynthesized by a common nonribosomal peptide synthetase. The information on configuration provided by Marfey's analysis of co-occurring minor congeners can reveal unequivocally the stereochemical sequence of the whole peptide family.

Metabolomics data complemented drug use information in epidemiological databases: pilot study of potential kidney donors

OBJECTIVE

The objective of this study was to investigate whether clinical metabolomics, which is increasingly applied in population-based and epidemiological studies, can be used to provide analytical evidence of exposures, and whether such information can be useful to strengthen and/or complement corresponding clinical database entries, taking drug use as an example.

STUDY DESIGN AND SETTING

Liquid chromatography-mass spectrometry (LC-MS) metabolomics analyses were performed on urine from 100 randomly-selected control subjects (50% females) from the TransplantLines Food and Nutrition Biobank and Cohort Study (NCT identifier 'NCT02811835'), and drugs were identified through spectral library searching and targeted signal extraction.

RESULTS

In 83 subjects for whom drug use information was available, 22 expected and 26 unexpected prescription-only drugs were identified, while 28 expected prescription-only drugs remained undetected. In addition, 7 prescription-only drugs were found in 17 subjects for whom drug use information was unavailable, and 58 over-the-counter drugs were identified in all 100 subjects.

CONCLUSION

Molecular evidence for many drugs could be retrieved from LC-MS metabolomics data, which could be useful to complement and strengthen epidemiological databases given that considerable discrepancies were found between analytically-identified drugs and drugs listed in the available clinical database.

Applications of stable isotopes in MALDI imaging: current approaches and an eye on the future

Matrix-assisted laser desorption/ionisation-imaging mass spectrometry (MALDI-IMS) is now an established imaging modality with particular utility in the study of biological, biomedical and pathological processes. In the first instance, the use of stable isotopically labelled (SIL) compounds in MALDI-IMS has addressed technical barriers to increase the accuracy and versatility of this technique. This has undoubtedly enhanced our ability to interpret the two-dimensional ion intensity distributions produced from biological tissue sections. Furthermore, studies using delivery of SIL compounds to live tissues have begun to decipher cell, tissue and inter-tissue metabolism while maintaining spatial resolution. Here, we review both the technical and biological applications of SIL compounds in MALDI-IMS, before using the uptake and metabolism of glucose in bovine ocular lens tissue to illustrate the current limitations of SIL compound use in MALDI-IMS. Finally, we highlight recent instrumentation advances that may further enhance our ability to use SIL compounds in MALDI-IMS to understand biological and pathological processes. Graphical Abstract.

Determination of drugs and drug metabolites by ion mobility-mass spectrometry: A review

Ion mobility-mass spectrometry (IM-MS) has gained increased applications in the characterization and identification of drugs and drug metabolites, largely owning to the complementary separation of analyte ions based on their gas-phase size and shape in the IM dimension in addition to their mass-to-charge ratios. In this review, we discuss recent advances in such applications. We first introduce various types of IM techniques, focusing on those that allow the measurement of collision cross section (CCS), the physical property of an ion that reflects its gas-phase size and shape. Next, we discuss the IM-MS landscape of the large chemical space of drugs and multimodal distributions of certain drugs in IM separation due to the presence of protomers. We then review drug metabolism reactions and discuss the application of IM-MS in separation and identification of isomeric drug metabolites. Subsequently, we discuss various approaches to generate theoretical and predicted CCS data, including theory-based calculation methods and data-driven prediction models, and currently available resources on these approaches. Finally, current limitations and future directions of application of IM-MS are discussed.

An integrated strategy for comprehensive characterization of metabolites and metabolic profiles of bufadienolides from Venenum Bufonis in rats

Comprehensive characterization of metabolites and metabolic profiles in plasma has considerable significance in determining the efficacy and safety of traditional Chinese medicine (TCM) in vivo. However, this process is usually hindered by the insufficient characteristic fragments of metabolites, ubiquitous matrix interference, and complicated screening and identification procedures for metabolites. In this study, an effective strategy was established to systematically characterize the metabolites, deduce the metabolic pathways, and describe the metabolic profiles of bufadienolides isolated from Venenum Bufonis in vivo. The strategy was divided into five steps. First, the blank and test plasma samples were injected into an ultra-high performance liquid chromatography/linear trap quadrupole-orbitrap-mass spectrometry (MS) system in the full scan mode continuously five times to screen for valid matrix compounds and metabolites. Second, an extension-mass defect filter model was established to obtain the targeted precursor ions of the list of bufadienolide metabolites, which reduced approximately 39% of the interfering ions. Third, an acquisition model was developed and used to trigger more tandem MS (MS/MS) fragments of precursor ions based on the targeted ion list. The acquisition mode enhanced the acquisition capability by approximately four times than that of the regular data-dependent acquisition mode. Fourth, the acquired data were imported into Compound Discoverer software for identification of metabolites with metabolic network prediction. The main in vivo metabolic pathways of bufadienolides were elucidated. A total of 147 metabolites were characterized, and the main biotransformation reactions of bufadienolides were hydroxylation, dihydroxylation, and isomerization. Finally, the main prototype bufadienolides in plasma at different time points were determined using LC-MS/MS, and the metabolic profiles were clearly identified. This strategy could be widely used to elucidate the metabolic profiles of TCM preparations or Chinese patent medicines in vivo and provide critical data for rational drug use.

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Extension-mass defect filter model could reduce about 39% interfering ions.

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The optimized acquisition mode enhanced about 4 times acquisition capability than regular DDA mode.

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147 metabolites were characterized with metabolic network prediction, and the metabolic pathways were deduced in plasmas.

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The quantitative method of 14 prototypes was established by LC-MS/MS for metabolic profiles study.

Identification of the metabolites of ivermectin in humans

Mass drug administration of ivermectin has been proposed as a possible malaria elimination tool. Ivermectin exhibits a mosquito-lethal effect well beyond its biological half-life, suggesting the presence of active slowly eliminated metabolites. Human liver microsomes, primary human hepatocytes, and whole blood from healthy volunteers given oral ivermectin were used to identify ivermectin metabolites by ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry. The molecular structures of metabolites were determined by mass spectrometry and verified by nuclear magnetic resonance. Pure cytochrome P450 enzyme isoforms were used to elucidate the metabolic pathways. Thirteen different metabolites (M1-M13) were identified after incubation of ivermectin with human liver microsomes. Three (M1, M3, and M6) were the major metabolites found in microsomes, hepatocytes, and blood from volunteers after oral ivermectin administration. The chemical structure, defined by LC-MS/MS and NMR, indicated that M1 is 3″-O-demethyl ivermectin, M3 is 4-hydroxymethyl ivermectin, and M6 is 3″-O-demethyl, 4-hydroxymethyl ivermectin. Metabolic pathway evaluations with characterized cytochrome P450 enzymes showed that M1, M3, and M6 were produced primarily by CYP3A4, and that M1 was also produced to a small extent by CYP3A5. Demethylated (M1) and hydroxylated (M3) ivermectin were the main human in vivo metabolites. Further studies are needed to characterize the pharmacokinetic properties and mosquito-lethal activity of these metabolites.

Mass Spectral Filtering by Mass-Remainder Analysis (MARA) at High Resolution and Its Application to Metabolite Profiling of Flavonoids

Flavonoids represent an important class of secondary metabolites because of their potential health benefits and functions in plants. We propose a novel method for the comprehensive flavonoid filtering and screening based on direct infusion mass spectrometry (DIMS) analysis. The recently invented data mining procedure, the multi-step mass-remainder analysis (M-MARA) technique is applied for the effective mass spectral filtering of the peak rich spectra of natural herb extracts. In addition, our flavonoid-filtering algorithm facilitates the determination of the elemental composition. M-MARA flavonoid-filtering uses simple mathematical and logical operations and thus, it can easily be implemented in a regular spreadsheet software. A huge benefit of our method is the high speed and the low demand for computing power and memory that enables the real time application even for tandem mass spectrometric analysis. Our novel method was applied for the electrospray ionization (ESI) DIMS spectra of various herb extract, and the filtered mass spectral data were subjected to chemometrics analysis using principal component analysis (PCA).

An integrated analytical approach based on enhanced fragment ions interrogation and modified Kendrick mass defect filter data mining for in-depth chemical profiling of glucosinolates by ultra-high-pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry

High resolution mass spectrometry (HRMS)-based analytical technique promotes the discovery and development of new bioactive molecules from natural sources. However, challenges for MS analysis of natural products include their structural diversity, numerous trace components, as well as the interference from complex matrices that limits the rapid detection and identification of all target analytes in the extracts. Herein, we presented an integrated analytical approach to obtain chemical profile of glucosinolates (GLSs) in Eutrema yunnanense, a perennial herb, which is used as a condiment (Wasabi), by ultra-high-pressure liquid chromatography coupled with Orbitrap high resolution mass spectrometry (UHPLC-Orbitrap/HRMS). The intelligent AcquireX deep scan greatly improved the detection efficiency and coverage of data-dependent acquisition (DDA) mode, and enhanced structurally significant product ions interrogation by generating exhaustive MS/MS spectra with more informative fragmentation. Massive HRMS data mining for searching GLSs was then achieved by a modified Kendrick mass defect filter (MKMDF), which enabled the visualization of their homologous characteristics and reduced the complicacy of data post-processing. Ultimately, a total of 175 GLSs were tentatively identified or characterized based on the MS fragmentation patterns, including 52 potentially new compounds among which 37 malonylated GLSs were first discovered. These compounds were then applied to analyse the chemical differentiation between the rhizome and leaf of E. yunnanense. This study provides a feasible approach for screening and confident structure characterization of GLSs and has practical implications for profiling other natural bioactive homologous compounds.

Mass spectrometry-based metabolomics for an in-depth questioning of human health

Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.

MASS SPECTROMETRY ANALYSIS OF DRUGS OF ABUSE: CHALLENGES AND EMERGING STRATEGIES

Mass spectrometry has been the "gold standard" for drugs of abuse (DoA) analysis for many decades because of the selectivity and sensitivity it affords. Recent progress in all aspects of mass spectrometry has seen significant developments in the field of DoA analysis. Mass spectrometry is particularly well suited to address the rapidly proliferating number of very high potency, novel psychoactive substances that are causing an alarming number of fatalities worldwide. This review surveys advancements in the areas of sample preparation, gas and liquid chromatography-mass spectrometry, as well as the rapidly emerging field of ambient ionization mass spectrometry. We have predominantly targeted literature progress over the past ten years and present our outlook for the future. © 2020 Periodicals, Inc. Mass Spec Rev.

Finding the proverbial needle: Non-targeted screening of synthetic opioids in equine plasma

Synthetic opioids are a class of compounds that are of particular concern due to their high potency and potential health impacts. With the relentless emergence of new synthetic opioid derivatives, non-targeted screening strategies are required that do not rely on the use of library spectra or reference materials. In this study, product ion searching, and Kendrick mass defect analysis were investigated for non-targeted screening of synthetic opioids. The estimated screening cut-offs for these techniques ranged between 0.05 and 0.1 ng/mL. These techniques were designed to not be reliant on a particular vendor's software, meaning that they can be applied to existing drug screening protocols, without requiring the development and validation of new analytical procedures. The efficacy of the developed techniques was tested through blind trials, with spiked samples inserted amongst authentic plasma samples, which demonstrated the usefulness of these methods for high-throughput screening. The use of a non-targeted screening workflow that contains complementary techniques can increase the likelihood of detecting compounds of interest within a sample, as well as the confidence in detections that are made.

Metabolite Identification of Therapeutic Peptides and Proteins by Top-down Differential Mass Spectrometry and Metabolite Database Matching

As metabolism impacts the efficacy and safety of therapeutic peptides and proteins (TPPs), understanding of the metabolic fate of TPPs is critical for their preclinical and clinical development. Despite the continued increase of new TPPs entering clinical trials, the metabolite identification (MetID) of these emerging modalities remains challenging. In the present study, we report an analytical workflow for MetID of TPPs. Using insulin detemir as an example, we demonstrated that top-down differential mass spectrometry (dMS) was able to distinguish and discover metabolites from complex biological matrices. For structural interpretation, we developed an algorithm to generate a complete and nonredundant theoretical metabolite database for a TPP of any topology (e.g., branched, multicyclic, etc.). Candidate structures of a metabolite were obtained by matching the monoisotopic mass of a dMS feature to the theoretical metabolite database. Finally, the MS/MS sequence tags enabled unambiguous characterization of metabolite structures when isobaric/isomeric candidates were present. This platform is widely applicable to TPPs with complex structures and will ultimately guide the structural optimization of TPPs in pharmaceutical development.