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

Ion Mobility Separations Using Cocentric Architecture

Ion mobility separations, especially using drift tube ion mobility spectrometers, are usually performed in linear channels, which can have a large footprint when extended to achieve higher resolving powers. In this work, we explored the performance of an ion mobility device with a curved architecture, which can have a more compact form. The cocentric ion mobility spectrometer (CoCIMS) manipulates ions between two cocentric surfaces containing a serpentine track. The mobility separation inside the CoCIMS is achieved using traveling waveforms (TWs). We initially evaluated the device using ion trajectory simulations using SIMION, which indicated that when ions traveled circularly inside the CoCIMS they resulted in similar resolving powers and transmitted m/z range as traveling in a straight path. We then performed experimental validation of the CoCIMS in conjunction with a TOF MS. The CoCIMS was made of two flexible printed circuit board materials folded into cocentric cylinders separated by a gap of 2.8 mm. The device was about 50 mm diameter ×152 mm long and provided 1.846 m of serpentine path length. Three sets of mixtures (Agilent tune mixture, tetraalkylammonium salts, and an eight-peptide mixture) and four traveling waveform profiles (square, sine, triangle, and sawtooth) were used. The sawtooth TW profile produced a slightly higher resolving power for the Agilent tuning mixture and tetraalkylammonium ions. The average resolving power for Agilent tune mixture ions ranged from 37 (using sawtooth TW) to 27 (using square TW). The average resolving powers ranged from 45 (sawtooth TW) to 31 (square TW) for tetraalkylammonium ions. The resolving power of the peptide mixture ions was similar among the four TW profiles and ranged from 51 to 56. The average percent error in TWCCS for the peptide mixture ions was about 0.4%. The new device showed promising results, but improvements are needed to further increase the resolving power.

Advances of Ion Mobility Platform for Plant Metabolomics

Metabolomics aims to profile the extensive array of metabolites that exists in different types of matrices using modern analytical techniques. These techniques help to separate, identify, and quantify the plethora of chemical compounds at various analytical platforms. Hence, ion mobility spectrometry (IMS) has emerged as an advanced analytical approach, exclusively owing to the 3D separation of metabolites and their isomers. Furthermore, separated metabolites are identified based on their mass fragmentation pattern and CCS (collision cross-section) values. The IMS provides an advanced alternative dimension to separate the isomeric metabolites with enhanced throughput with lesser chemical noise. Thus, the present review highlights the types, factors affecting the resolution, and applications of IMMS (Ion mobility mass spectrometry) for isomeric separations, and ionic contaminants in the plant samples. Furthermore, an overview of IMS-based applications for the identification of plant metabolites (volatile and non-volatile) over the last few decades has been discussed, followed by future assumptions for creating IM-based databases. Such approaches could be significant to accelerate and improve our knowledge of the vast chemical diversity found in plants.

Exploring the Conformational Landscape of Poly(l-lysine) Dendrimers Using Ion Mobility Mass Spectrometry

Ion mobility mass spectrometry (IM-MS) measures the mass, size, and shape of ions in the same experiment, and structural information is provided via collision cross-section (CCS) values. The majority of commercially available IM-MS instrumentation relies on the use of CCS calibrants, and here, we present data from a family of poly(l-lysine) dendrimers and explore their suitability for this purpose. In order to test these compounds, we employed three different IM-MS platforms (Agilent 6560 IM-QToF, Waters Synapt G2, and a home-built variable temperature drift tube IM-MS) and used them to investigate six different generations of dendrimers in two buffer gases (helium and nitrogen). Each molecule gives a highly discrete CCS distribution suggestive of single conformers for each m/z value. The DTCCSN2 values of this series of molecules (molecular weight: 330-16,214 Da) range from 182 to 2941 Å2, which spans the CCS range that would be found by many synthetic molecules including supramolecular compounds and many biopolymers. The CCS values for each charge state were highly reproducible in day-to-day analysis on each instrument, although we found small variations in the absolute CCS values between instruments. The rigidity of each dendrimer was probed using collisionally activated and high-temperature IM-MS experiments, where no evidence for a significant CCS change ensued. Taken together, this data indicates that these polymers are candidates for CCS calibration and could also help to reconcile differences found in CCS measurements on different instrument geometries.

Observation of Solvent-Dependence in the Mechanism of Neutral-Catalyzed Isomerization of para-Aminobenzoic Acid Protomers

Proton-transfer reactions are commonplace during electrospray ionization (ESI) mass spectrometry experiments and are often responsible for imparting charge to analyte molecules. Multiple protonation-site isomers (protomers) can arise for polyfunctional molecules and these isomers can interconvert via solvent-mediated proton transfer reactions during various stages of the ESI process. Studying the populations and interconversion of protonation isomers provides key insight into the ESI process, ion-molecule interactions, and ion dissociation mechanisms. An archetype molecule to study protomer interconversion fundamentals in this context is para-aminobenzoic acid (pABA), where both the amino and carboxylic acid protomers are typically formed under ESI and the mechanisms for interconversion are still under refinement. Using ion-trap mass spectrometry reaction kinetics (2.5 mTorr, 300 K), this study examines gas-phase interconversion catalysis of pABA protomers by seven neutral species, which are commen solvents and additives used for ESI: water, formic acid, methanol, ethanol, propanol, ammonia, and acetonitrile. Three distinct reaction cases are reported: (i) formic acid, methanol, ethanol, propanol, and ammonia each catalyze the interconversion between the amino and carboxylic acid protomers via a n = 1 solvent-molecule vehicle mechanism; (ii) for water, however, a n = 6 adduct complex is detected and this suggests that the observed protomer interconversion occurs through a Grotthuss mechanism, in accord with literature reports; (iii) acetonitrile inhibits proton transfer by the formation of particularly stable n = 1 and 2 adduct complexes. The second-order rate constants for the protomer interconversion are observed to increase in the following order: H2O < HCO2H < MeOH < EtOH < PrOH < NH3. Potential energy schemes are reported for all neutral-catalyzed proton transfer reactions using the DSD-PBEP86-D3(BJ)/aug-cc-pVDZ level of theory. A central transition state, which connects the protonation site adducts, is shown to be the key rate-limiting step. The energy of this transition state is sensitive to the proton affinity of the neutral solvent, and this is supported by the correlation between the reaction rate and the solvent proton affinity.

Innovative direct introduction-ion mobility-mass spectrometry (DI-IM-MS) approach for fast and robust isomer-specific quantification in a complex matrix: Application to 2'-fucosyllactose (2'-FL) in breast milk

Identification and specific quantification of isomers in a complex biological matrix by mass spectrometry alone is not an easy task due to their identical chemical formula and therefore their same mass-to-charge ratio (m/z). Here, the potential of direct introduction combined with ion mobility-mass spectrometry (DI-IM-MS) for rapid quantification of isomers as human milk oligosaccharides (HMOs) was investigated. Differences in HMO profiles between various analyzed breast milk samples were highlighted using the single ion mobility monitoring (SIM2) acquisition for high ion mobility resolution detection. Furthermore, the Se+ (secretor) or Se- (non-secretor) phenotype could be assigned to breast milk samples studied based on their HMO contents, especially on the response of 2'-fucosyllactose (2'-FL) and lacto-N-fucopentaose I (LNFP I). The possibility of quantifying a specific isomer in breast milk by DI-IM-MS was also investigated. The standard addition method allowed the determination of the 2'-FL despite the presence of other oligosaccharides, including 3-fucosyllactose (3-FL) isomer in breast milk. This proof-of-concept study demonstrated the high potential of such an approach for the rapid and convenient quantification of isomers in complex mixtures.

What is the role of current mass spectrometry in pharmaceutical analysis?

The role of mass spectrometry (MS) has become more important in most application domains in recent years. Pharmaceutical analysis is specific due to its stringent regulation procedures, the need for good laboratory/manufacturing practices, and a large number of routine quality control analyses to be carried out. The role of MS is, therefore, very different throughout the whole drug development cycle. While it dominates within the drug discovery and development phase, in routine quality control, the role of MS is minor and indispensable only for selected applications. Moreover, its role is very different in the case of analysis of small molecule pharmaceuticals and biopharmaceuticals. Our review explains the role of current MS in the analysis of both small-molecule chemical drugs and biopharmaceuticals. Important features of MS-based technologies being implemented, method requirements, and related challenges are discussed. The differences in analytical procedures for small molecule pharmaceuticals and biopharmaceuticals are pointed out. While a single method or a small set of methods is usually sufficient for quality control in the case of small molecule pharmaceuticals and MS is often not indispensable, a large panel of methods including extensive use of MS must be used for quality control of biopharmaceuticals. Finally, expected development and future trends are outlined.

Gas Phase Reactivity of Isomeric Hydroxylated Polychlorinated Biphenyls

Identification of stereo- and positional isomers detected with high-resolution mass spectrometry (HRMS) is often challenging due to near-identical fragmentation spectra (MS2), similar retention times, and collision cross-section values (CCS). Here we address this challenge on the example of hydroxylated polychlorinated biphenyls (OH-PCBs) with the aim to (1) distinguish between isomers of OH-PCBs using two-dimensional ion mobility spectrometry (2D-IMS) and (2) investigate the structure of the fragments of OH-PCBs and their fragmentation mechanisms by ion mobility spectrometry coupled to high-resolution mass spectrometry (IMS-HRMS). The MS2 spectra as well as CCS values of the deprotonated molecule and fragment ions were measured for 18 OH-PCBs using flow injections coupled to a cyclic IMS-HRMS. The MS2 spectra as well as the CCS values of the parent and fragment ions were similar between parent compound isomers; however, ion mobility separation of the fragment ions is hinting at the formation of isomeric fragments. Different parent compound isomers also yielded different numbers of isomeric fragment mobilogram peaks giving new insights into the fragmentation of these compounds and indicating new possibilities for identification. For spectral interpretation, Gibbs free energies and CCS values for the fragment ions of 4'-OH-CB35, 4'-OH-CB79, 2-OH-CB77 and 4-OH-CB107 were calculated and enabled assignment of structures to the isomeric mobilogram peaks of [M-H-HCl]- fragments. Finally, further fragmentation of the isomeric fragments revealed different fragmentation pathways depending on the isomeric fragment ions.

Formation of halogenated forms of bisphenol A (BPA) in water: Resolving isomers with ion mobility - mass spectrometry and the role of halogenation position in cellular toxicity

Halogenated BPA (XBPA) forms resulting from water chlorination can lead to increased toxicity and different biological effects. While previous studies have reported the occurrence of different XBPAs, analytical limitation have hindered the analysis and differentiation of the many potential isomeric forms. Using online solid-phase extraction - liquid chromatography - ion-mobility - high-resolution mass spectrometry (OSPE-LC-IM-HRMS), we demonstrated a rapid analysis method for the analysis of XBPA forms after water chlorination, with a total analysis time of less than 10 min including extraction and concentration and low detection limits (∼5-80 ng/L range). A multi in-vitro bioassay testing approach for the identified products revealed that cytotoxicity and bioenergetics impacts were largely associated with the presence of halogen atoms at positions 2 or 2' and the overall number of halogens incorporated into the BPA molecule. Different XBPA also showed distinct impacts on oxidative stress, peroxisome proliferator-activated receptor gamma - PPARγ, and inflammatory response. While increased DNA damage was observed for chlorinated water samples (4.14 ± 1.21-fold change), the additive effect of the selected 20 XBPA studied could not explain the increased DNA damage observed, indicating that additional species or synergistic effects might be at play.

Hydroxylated transformation products of pharmaceutical active compounds: Generation from processes used in wastewater treatment plants and its environmental monitoring

Pharmaceutical active compounds (PhACs) are organic pollutants detected in wastewater and aquatic environments worldwide in concentrations ranging from ng L-1 to μg L-1. Wastewater effluents containing PhACs residues is discharged in municipal sewage and, subsequently collected in municipal wastewater treatment plants (WWTPs) where are not entirely removed. Thus, PhACs and its transformation products (TPs) are discharged into water bodies. In the current work, the transformation of PhACs under treatments used in municipal WWTPs such as biological, photolysis, chlorination, and ozonation processes was reviewed. Data set of the major transformation pathways were obtained of studies that performed the PhACs removal and TPs monitoring during batch-scale experiments using gas and liquid chromatography coupled with tandem mass spectrometry (GC/LC-MS/MS). Several transformation pathways as dealkylation, hydroxylation, oxidation, acetylation, aromatic ring opening, chlorination, dehalogenation, photo-substitution, and ozone attack reactions were identified during the transformation of PhACs. Especially, hydroxylation reaction was identified as transformation pathway in all the processes. During the elucidation of hydroxylated TPs several isobaric compounds as monohydroxylated and dihydroxylated were identified. However, hydroxylated TPs monitoring in wastewater and aquatic environments is a topic scarcely studied due to that has no environmental significance, lack of available analytic standars of hydroxylated TPs and lack of analytic methods for their identification. Thus, screening strategy for environmental monitoring of hydroxylated TPs was proposed through target and suspect screening using GC/LC-MS/MS systems. In the next years, more studies on the hydroxylated TPs monitoring are necessary for its detection in WWTPs effluents as well as studies on their environmental effects in aquatic environments.

Identification and quantification of bipyridyl dicarboxylic acid isomers by ion mobility spectrometry

The identification of positional isomers is of interest because different isomers have different chemical or biological functions and applications. The analysis of positional isomers is sometimes challenging since they have similar chemical structures and properties. For example, the analysis of mass cannot identify different positional isomers because they have identical mass-to-charge ratios and show a single mass peak in mass spectrometry. In this study, an efficient and simple qualitative and quantitative analytical method for differentiating 2,2'-bipyridine-3,3'-dicarboxylic acid (3,3'-BDA), 2,2'-bipyridine-4,4'-dicarboxylic acid (4,4'-BDA), and 2,2'-bipyridine-5,5'-dicarboxylic acid (5,5'-BDA) was developed by using ion mobility spectrometry (IMS). The results revealed that the three BDA isomers formed non-covalent complexes with cyclodextrins (CDs) and Mg2+ ions in the gas phase: [β-CD+3,3'/4,4'/5,5'-BDA+Mg]2+ and [γ-CD+3,3'/4,4'/5,5'-BDA+Mg]2+, which were distinguished by measuring the mobility of the complexes because of their spatial conformational differences. The peak-to-peak resolution (Rp-p) values of the three isomers of [γ-CD+3,3'/4,4'/5,5'-BDA+Mg]2+ reached 2.983 and 2.892, respectively. The conformations of the ternary complexes simulated by the theoretical calculations revealed the different interactions and shapes of the stereoisomers, and the predicted results agreed with the experimental results. Simultaneously, further studies on the collisional dissociation of the ternary complexes revealed that the dissociation energies of the different complex ions varied were different owing to the diverse different conformations. Finally, the relative quantitative analysis of the different isomers in mixed samples was performed and satisfactory linearity results (R2 > 0.99) were obtained. Thus, an effective analytical method was proposed for the identification and quantification of BDA isomers without chemical derivatization, offering a promising approach for the identification of similar derivatives or positional isomers that could be applied in various fields including chemicals and pharmaceuticals.

Potential of measured relative shifts in collision cross section values for biotransformation studies

Ion mobility spectrometry-mass spectrometry (IMS-MS) separates gas phase ions due to differences in drift time from which reproducible and analyte-specific collision cross section (CCS) values can be derived. Internally conducted in vitro and in vivo metabolism (biotransformation) studies indicated repetitive shifts in measured CCS values (CCSmeas) between parent drugs and their metabolites. Hence, the purpose of the present article was (i) to investigate if such relative shifts in CCSmeas were biotransformation-specific and (ii) to highlight their potential benefits for biotransformation studies. First, mean CCSmeas values of 165 compounds were determined (up to n = 3) using a travelling wave IMS-MS device with nitrogen as drift gas (TWCCSN2, meas). Further comparison with their predicted values (TWCCSN2, pred, Waters CCSonDemand) resulted in a mean absolute error of 5.1%. Second, a reduced data set (n = 139) was utilized to create compound pairs (n = 86) covering eight common types of phase I and II biotransformations. Constant, discriminative, and almost non-overlapping relative shifts in mean TWCCSN2, meas were obtained for demethylation (- 6.5 ± 2.1 Å2), oxygenation (hydroxylation + 3.8 ± 1.4 Å2, N-oxidation + 3.4 ± 3.3 Å2), acetylation (+ 13.5 ± 1.9 Å2), sulfation (+ 17.9 ± 4.4 Å2), glucuronidation (N-linked: + 41.7 ± 7.5 Å2, O-linked: + 38.1 ± 8.9 Å2), and glutathione conjugation (+ 49.2 ± 13.2 Å2). Consequently, we propose to consider such relative shifts in TWCCSN2, meas (rather than absolute values) as well for metabolite assignment/confirmation complementing the conventional approach to associate changes in mass-to-charge (m/z) values between a parent drug and its metabolite(s). Moreover, the comparison of relative shifts in TWCCSN2, meas significantly simplifies the mapping of metabolites into metabolic pathways as demonstrated.

Test method for vapor collection and ion mobility detection of explosives with low vapor pressure

RATIONALE

Ion mobility spectrometry (IMS) has been widely used for on-site detection of explosives. Air sampling method is applicable only when the concentration of explosive vapor is considerably high in the air, but vapor pressures of common explosives such as 2,4,6-trinitrotoluene (TNT), 1,3,5-trinitro-1,3,5-triazacyclohexane (RDX), and pentaerythritol tetranitrate (PETN) are very low. A test method for analyzing the vapor detection efficiency of explosives with low vapor pressure via IMS was developed using artificial vapor and collection matrices.

METHODS

Artificial explosive vapor was produced by spraying an explosive solution in acetone. Fifteen collection matrices of various materials with woven or nonwoven structures were tested. Two arrangements of horizontal and vertical positions of the collection matrices were employed. Explosive vapor collected in the matrix was analyzed using IMS.

RESULTS

Only three collection matrices of stainless steel mesh (SSM), polytetrafluoroethylene sheet (PFS), and lens cleansing paper (LCP) showed the TNT and/or RDX ion peaks at an explosive vapor concentration of 49 ng/L. There was no collection matrix to detect PETN vapor at or lower than 49 ng/L. For the PFS, TNT and RDX were detected at a vapor concentration of 49 ng/L. For the LCP, TNT and RDX were detected at vapor concentrations of 14 and 49 ng/L, irrespectively.

CONCLUSIONS

The difference in the explosive vapor detection efficiencies could be explained by the adsorption and desorption capabilities of the collection matrices. The proposed method can be used for evaluating the vapor detection efficiency of hazardous materials with low vapor pressure.

Sliding Windows in Ion Mobility (SWIM): A New Approach to Increase the Resolving Power in Trapped Ion Mobility-Mass Spectrometry Hyphenated with Chromatography

Over the past decade, the separation efficiency achieved by linear IMS instruments has increased substantially, with state-of-the-art IM technologies, such as the trapped ion mobility (TIMS), the cyclic traveling wave ion mobility (cTWIMS), and the structure for lossless ion manipulation (SLIM) platforms commonly demonstrating resolving powers in excess of 200. However, for complex sample analysis that require front end separation, the achievement of such high resolving power in TIMS is significantly hampered, since the ion mobility range must be broad enough to analyze all the classes of compounds of interest, whereas the IM analysis time must be short enough to cope with the time scale of the preseparation technique employed. In this paper, we introduce the concept of sliding windows in ion mobility (SWIM) for chromatography hyphenated TIMS applications that bypasses the need to use a wide and fixed IM range by using instead narrow and mobile ion mobility windows that adapt to the analytes' ion mobility during chromatographic separation. GC-TIMS-MS analysis of a mixture of 174 standards from several halogenated persistent organic pollutant (POP) classes, including chlorinated and brominated dioxins, biphenyls, and PBDEs, demonstrated that the average IM resolving power could be increased up to 40% when the SWIM mode was used, thereby greatly increasing the method selectivity for the analysis of complex samples.

A structural similarity networking assisted collision cross-section prediction interval filtering strategy for multi-compound identification of complex matrix by ion-mobility mass spectrometry

Ion mobility coupled with mass spectrometry (IM-MS), an emerging technology for analysis of complex matrix, has been facing challenges due to the complexities of chemical structures and original data, as well as low-efficiency and error-proneness of manual operations. In this study, we developed a structural similarity networking assisted collision cross-section prediction interval filtering (SSN-CCSPIF) strategy. We first carried out a structural similarity networking (SSN) based on Tanimoto similarities among Morgan fingerprints to classify the authentic compounds potentially existing in complex matrix. By performing automatic regressive prediction statistics on mass-to-charge ratios (m/z) and collision cross-sections (CCS) with a self-built Python software, we explored the IM-MS feature trendlines, established filtering intervals and filtered potential compounds for each SSN classification. Chemical structures of all filtered compounds were further characterized by interpreting their multidimensional IM-MS data. To evaluate the applicability of SSN-CCSPIF, we selected Ginkgo biloba extract and dripping pills. The SSN-CCSPIF subtracted more background interferences (43.24%∼43.92%) than other similar strategies with conventional ClassyFire criteria (10.71%∼12.13%) or without compound classification (35.73%∼36.63%). Totally, 229 compounds, including eight potential new compounds, were characterized. Among them, seven isomeric pairs were discriminated with the integration of IM-separation. Using SSN-CCSPIF, we can achieve high-efficient analysis of complex IM-MS data and comprehensive chemical profiling of complex matrix to reveal their material basis.

Mass Spectrometry-Based Proteomics: Analyses Related to Drug-Resistance and Disease Biomarkers

Mass spectrometry-based proteomics is a key player in research efforts to characterize aberrant epigenetic alterations, including histone post-translational modifications and DNA methylation. Data generated by this approach complements and enrich datasets generated by genomic, epigenetic and transcriptomics approaches. These combined datasets can provide much-needed information on various mechanisms responsible for drug resistance, the discovery and validation of potential biomarkers for different diseases, the identification of signaling pathways, and genes and enzymes to be targeted by future therapies. The increasing use of high-resolution, high-accuracy mass spectrometers combined with more refined protein labeling and enrichment procedures enhanced the role of this approach in the investigation of these epigenetic modifications. In this review, we discuss recent MS-based studies, which are contributing to current research efforts to understand certain mechanisms behind drug resistance to therapy. We also discuss how these MS-based analyses are contributing to biomarkers discovery and validation.

AllCCS2: Curation of Ion Mobility Collision Cross-Section Atlas for Small Molecules Using Comprehensive Molecular Representations

The development of ion mobility-mass spectrometry (IM-MS) has revolutionized the analysis of small molecules, such as metabolomics, lipidomics, and exposome studies. The curation of comprehensive reference collision cross-section (CCS) databases plays a pivotal role in the successful application of IM-MS for small-molecule analysis. In this study, we presented AllCCS2, an enhanced version of AllCCS, designed for the universal prediction of the ion mobility CCS values of small molecules. AllCCS2 incorporated newly available experimental CCS data, including 10,384 records and 7713 unified values, as training data. By leveraging a neural network trained on diverse molecular representations encompassing mass spectrometry features, molecular descriptors, and graph features extracted using a graph convolutional network, AllCCS2 achieved exceptional prediction accuracy. AllCCS2 achieved median relative error (MedRE) values of 0.31, 0.72, and 1.64% in the training, validation, and testing sets, respectively, surpassing existing CCS prediction tools in terms of accuracy and coverage. Furthermore, AllCCS2 exhibited excellent compatibility with different instrument platforms (DTIMS, TWIMS, and TIMS). The prediction uncertainties in AllCCS2 from the training data and the prediction model were comprehensively investigated by using representative structure similarity and model prediction variation. Notably, small molecules with high structural similarities to the training set and lower model prediction variation exhibited improved accuracy and lower relative errors. In summary, AllCCS2 serves as a valuable resource to support applications of IM-MS technologies. The AllCCS2 database and tools are freely accessible at http://allccs.zhulab.cn/.

Collision cross section measurement and prediction methods in omics

Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant-independent and calibrant-dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.

Trapped ion mobility mass spectrometry of new psychoactive substances: Isomer-specific identification of ring-substituted cathinones

New psychoactive substances (NPS) are synthetic derivatives of illicit drugs designed to mimic their psychoactive effects. NPS are typically not controlled under drug acts or their legal status depends on their molecular structure. Discriminating isomeric forms of NPS is therefore crucial for forensic laboratories. In this study, a trapped ion mobility spectrometry time-of-flight mass spectrometry (TIMS-TOFMS) approach was developed for the identification of ring-positional isomers of synthetic cathinones, a class of compounds representing two-third of all NPS seized in Europe in 2020. The optimized workflow features narrow ion-trapping regions, mobility calibration by internal reference, and a dedicated data-analysis tool, allowing for accurate relative ion-mobility assessment and high-confidence isomer identification. Ortho-, meta- and para-isomers of methylmethcathinone (MMC) and bicyclic ring isomers of methylone were assigned based on their specific ion mobilities within 5 min, including sample preparation and data analysis. The resolution of two distinct protomers per cathinone isomer added to the confidence in identification. The developed approach was successfully applied to the unambiguous assignment of MMC isomers in confiscated street samples. These findings demonstrate the potential of TIMS-TOFMS for forensic case work requiring fast and highly-confident assignment cathinone-drug isomers in confiscated samples.

Collision Cross Section Prediction Based on Machine Learning

Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.

Single drop analysis of mercury ions by rational design of peptide coated gold nanoparticles integrated with MALDI-MS measurement

In this study, a novel and rapid method for specific identification and accurate quantification of Hg²⁺ in environmental water was developed by using laser cleavable cysteine containing peptides modified gold nanoparticles coupled with high resolution matrix-assisted laser desorption ionization time-of-flight mass spectrometer (MALDI-TOF MS) measurement. First, gold nanoparticles were prepared by the reduction of tetrachloroauric (III) acid (HAuCl₄) solution. Various cysteine containing peptides, photolabile linkers, including mercury ion binding motif with a proper molecular mass and amino acids were synthesized by solid phase peptide synthesis (SPPS). Subsequently, thiol-containing peptides were coated onto the surface of gold nanoparticles via the formation of gold-thiol (Au-S) bond. The resulting cysteine containing peptides modified gold nanoparticles were designed to specifically capture Hg²⁺ in water samples. After conjugated complex formation, ions of Hg²⁺-peptide complex were directly liberated by ultraviolet laser radiation by way of MALDI-MS using α-Cyano-4-hydroxycinnamic acid (CHCA) as matrix. The linear dynamic range of Hg²⁺ concentration in this study was 1-100 pmol/μL with coefficient of determination 0.9987. The limit of detection (LOD) and limit of quantification (LOQ) were 0.19 and 0.63 pmol/μL, respectively. Notably, the developed method allows rapid quantification of Hg²⁺ in 5 min and the desired sample volume was down to few μL.

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network

As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probability of invasive alien species. A major pathway for invasive alien species is agricultural quarantine materials (AQMs) in travelers' baggage. Thus, it is meaningful to develop efficient methods for early detection and prompt action against AQMs. In this study, a method based on the combination of odor detection of AQMs using ion mobility spectroscopy (IMS) and convolutional neural network (CNN) analysis for the identification of AQM species in luggage was developed. Two different ways were investigated to feed the IMS data of AQMs into the CNN, either as one-dimensional data (1D) (as a spectrum) or as two-dimensional data (2D) (as an IMS topographic map). The performances of CNN models were also compared to those of the commonly used classification algorithms: partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA). By doing gradient-weighted class activation mapping (Grad-CAM), the essential IMS feature regions from the CNN models to predict different AQM species were also identified. The results of this research demonstrated that the application of the CNN to the IMS data of AQMs yielded superior classification performance compared to PLS-DA and SIMCA. Especially, the CNN-2D model which utilized the IMS topographic map as input achieved the best classification accuracy both on the calibration and validation sets. In addition, the Grad-CAM method had an ability to detect critical discriminating spectral regions for different types of AQM samples, and could provide explanation for the CNNs' decision-making. Despite the inherent limitations of the present analytical protocol, the results showed that the method of IMS in combination with a CNN has great potential to be a complement for sniffer dogs and X-ray imaging techniques to detect AQMs.

Collision Cross Section Prediction with Molecular Fingerprint Using Machine Learning

High-resolution mass spectrometry is a promising technique in non-target screening (NTS) to monitor contaminants of emerging concern in complex samples. Current chemical identification strategies in NTS experiments typically depend on spectral libraries, chemical databases, and in silico fragmentation tools. However, small molecule identification remains challenging due to the lack of orthogonal sources of information (e.g., unique fragments). Collision cross section (CCS) values measured by ion mobility spectrometry (IMS) offer an additional identification dimension to increase the confidence level. Thanks to the advances in analytical instrumentation, an increasing application of IMS hybrid with high-resolution mass spectrometry (HRMS) in NTS has been reported in the recent decades. Several CCS prediction tools have been developed. However, limited CCS prediction methods were based on a large scale of chemical classes and cross-platform CCS measurements. We successfully developed two prediction models using a random forest machine learning algorithm. One of the approaches was based on chemicals’ super classes; the other model was direct CCS prediction using molecular fingerprint. Over 13,324 CCS values from six different laboratories and PubChem using a variety of ion-mobility separation techniques were used for training and testing the models. The test accuracy for all the prediction models was over 0.85, and the median of relative residual was around 2.2%. The models can be applied to different IMS platforms to eliminate false positives in small molecule identification.

High-Throughput Measurement and Machine Learning-Based Prediction of Collision Cross Sections for Drugs and Drug Metabolites

Drug metabolite identification is a bottleneck of drug metabolism studies due to the need for time-consuming chromatographic separation and structural confirmation. Ion mobility-mass spectrometry (IM-MS), on the other hand, separates analytes on a rapid (millisecond) time scale and enables the measurement of collision cross section (CCS), a unique physical property related to an ion's gas-phase size and shape, which can be used as an additional parameter for identification of unknowns. A current limitation to the application of IM-MS to the identification of drug metabolites is the lack of reference CCS values. In this work, we assembled a large-scale database of drug and drug metabolite CCS values using high-throughput in vitro drug metabolite generation and a rapid IM-MS analysis with automated data processing. Subsequently, we used this database to train a machine learning-based CCS prediction model, employing a combination of conventional 2D molecular descriptors and novel 3D descriptors, achieving high prediction accuracies (0.8-2.2% median relative error on test set data). The inclusion of 3D information in the prediction model enables the prediction of different CCS values for different protomers, conformers, and positional isomers, which is not possible using conventional 2D descriptors. The prediction models, dmCCS, are available at https://CCSbase.net/dmccs_predictions.

A Rapid and Sensitive Method for the Simultaneous Determination of Multipolar Compounds in Plant Tea by Supercritical Fluid Chromatography Coupled to Ion Mobility Quadrupole Time-of-Flight Mass Spectrometry

In this study, matrix solid phase dispersion (MSPD) microextraction combined with supercritical fluid chromatography-ion mobility quadrupole time-of-flight mass spectrometry (SFC/IM-QTOF-MS) was used to analyze the multipolar compounds in plant tea. The parameters of stationary phase, mobile phase, make-up solution, temperature, and back pressure were optimized. The target analytes were gradient eluted in 8 min by supercritical CO₂ on a Zorbax RX-SIL column. Collisional Cross Section (CCS) values for single and multiple fields were measured. A series of validation studies were carried out under the optimal conditions, and the linear relationship and reproducibility were good. The limits of detection were 1.4 (Scoparone (1))~70 (Naringenin (4)) ng/mL, and the limits of quantification were 4.7 (Scoparone (1))~241 (Naringenin (4)) ng/mL. The recoveries of most compounds ranged from 60.7% to 127%. As a consequence, the proposed method was used for the separation and quantitative analysis of active ingredients in caulis dendrobii.

Large-Scale Evaluation of Collision Cross Sections to Investigate Blood-Brain Barrier Permeation of Drugs

Successful drug administration to the central nervous system requires accurate adjustment of the drugs’ molecular properties. Therefore, structure-derived descriptors of potential brain therapeutic agents are essential for an early evaluation of pharmacokinetics during drug development. The collision cross section (CCS) of molecules was recently introduced as a novel measurable parameter to describe blood-brain barrier (BBB) permeation. This descriptor combines molecular information about mass, structure, volume, branching and flexibility. As these chemical properties are known to influence cerebral pharmacokinetics, CCS determination of new drug candidates may provide important additional spatial information to support existing models of BBB penetration of drugs. Besides measuring CCS, calculation is also possible; but however, the reliability of computed CCS values for an evaluation of BBB permeation has not yet been fully investigated. In this work, prediction tools based on machine learning were used to compute CCS values of a large number of compounds listed in drug libraries as negative or positive with respect to brain penetration (BBB⁺ and BBB⁻ compounds). Statistical evaluation of computed CCS and several other descriptors could prove the high value of CCS. Further, CCS-deduced maximum molecular size of BBB⁺ drugs matched the dimensions of BBB pores. A threshold for transcellular penetration and possible permeation through pore-like openings of cellular tight-junctions is suggested. In sum, CCS evaluation with modern in silico tools shows high potential for its use in the drug development process.

A comprehensive UHPLC-MS/MS screening method for the analysis of 98 New Psychoactive Substances and related compounds in human hair

In this study, a rapid liquid chromatography-tandem mass spectrometry (LC-MS/MS) method has been developed and validated for the targeted analysis of 98 New Psychoactive Substances (NPS) from the hair matrix. The monitored compounds included various chemical classes (7 phenethylamines, 10 tryptamines, 18 cathinones, 24 synthetic opioids, and 38 synthetic cannabinoids) with emphasis given to newly emerged NPS. The method employed a direct extraction process through the incubation of hair samples (25 mg) and internal standards with M3® reagent at 100 °C for 60 min, followed by extract purification through acid and basic liquid-liquid micro-extraction (LLME). Extracted compounds were analyzed through LC-MS/MS system operating in multiple reaction monitoring mode. NPS were separated in 9.5 min with a Poroshell 120 EC-C18 column (2.7 μm, 4.6 × 50 mm) using a gradient eluting mobile phase composed of water and acetonitrile/water (95:5) both containing 0.1 % of formic acid. The developed and validated method shows a good precision (≤ 15 %), linearity (R² between 0.993 and 0.999), selectivity, and sensitivity (LOD: 0.6-10.3 pg mg^-1 and LOQ: 2.1-34.4 pg mg^-1). The method showed also reduced matrix effect and acceptable recovery for most of the targeted compounds. Our results showed that this method is suitable for quantifying NPS in hair matrix and could be employed in the context of routine analyses in analytical laboratories.

Investigation into Small Molecule Isomeric Glucuronide Metabolite Differentiation Using In Silico and Experimental Collision Cross-Section Values

Identifying isomeric metabolites remains a challenging and time-consuming process with both sensitivity and unambiguous structural assignment typically only achieved through the combined use of LC-MS and NMR. Ion mobility mass spectrometry (IMMS) has the potential to produce timely and accurate data using a single technique to identify drug metabolites, including isomers, without the requirement for in-depth interpretation (cf. MS/MS data) using an automated computational pipeline by comparison of experimental collision cross-section (CCS) values with predicted CCS values. An ion mobility enabled Q-Tof mass spectrometer was used to determine the CCS values of 28 (14 isomeric pairs of) small molecule glucuronide metabolites, which were then compared to two different in silico models; a quantum mechanics (QM) and a machine learning (ML) approach to test these approaches. The difference between CCS values within isomer pairs was also assessed to evaluate if the difference was large enough for unambiguous structural identification through in silico prediction. A good correlation was found between both the QM- and ML-based models and experimentally determined CCS values. The predicted CCS values were found to be similar between ML and QM in silico methods, with the QM model more accurately describing the difference in CCS values between isomer pairs. Of the 14 isomeric pairs, only one (naringenin glucuronides) gave a sufficient difference in CCS values for the QM model to distinguish between the isomers with some level of confidence, with the ML model unable to confidently distinguish the studied isomer pairs. An evaluation of analyte structures was also undertaken to explore any trends or anomalies within the data set.

Quantification of SARS-CoV-2 spike and nucleocapsid proteins using isotope dilution tandem mass spectrometry

The emergence and subsequent global outbreak of the novel coronavirus SARS-CoV-2 prompted our laboratory to launch efforts to develop methods for SARS-CoV-2 antigen detection and quantification. We present an isotope dilution mass spectrometry method (IDMS) for rapid and accurate quantification of the primary antigens, spike and nucleocapsid proteins. This IDMS method utilizes liquid chromatography-tandem mass spectrometry (LC-MS/MS) to analyze sample tryptic digests for detection and quantification of selected conserved peptides of SARS-CoV-2 spike and nucleocapsid proteins. The IDMS method has the necessary attributes to be successfully utilized for accurate quantification in SARS-CoV-2 protein-based vaccines and as targets of rapid diagnostic tests. Absolute quantification was achieved by quantifying and averaging 5 peptides for spike protein (3 peptides in the S1 subunit and 2 peptides in the S2 subunit) and 4 peptides for nucleocapsid protein. The overall relative standard deviation of the method was 3.67% for spike protein and 5.11% for nucleocapsid protein. IDMS offers speed (5 h total analysis time), sensitivity (LOQ; 10 fmol/µL) and precision for quantification of SARS-CoV-2 spike and nucleocapsid proteins.