UV-A-Induced Photoisomerization and Photodimerization of Curcumin: An Ion Mobility Mass Spectrometry Study

Curcumin, the bioactive compound present in spice plant turmeric, has been shown to exhibit selective phototoxic activities toward mammalian cancer cells, and it is being used extensively as a photosensitizer (PS) in photodynamic therapies (PDT). However, so far, the fate of curcumin toward photochemical transformations is not well understood. Here we report our findings of a number of novel photochemical reaction channels of curcumin in water-methanol mixture, like photoisomerization, photodimerization, and photooxidation (H2-loss). The reaction was performed by irradiating the curcumin solution with ultraviolet (UV) light of wavelength 350 nm, which is abundant in the earth's troposphere. Product identification and structure elucidation are done by employing an integrated method of drift tube ion mobility mass spectrometry (DTIMS) in combination with high-performance liquid chromatography (HPLC) and collision-induced dissociation (CID) of the mass-selected molecular ions. Two photoisomers of curcumin produced as a result of trans-cis configurational changes about C═C double bonds in the excited state have been identified, and it has been shown that they could serve as the precursors for formation of isomeric dimers via [2 + 2] cycloaddition and H2-loss products. Comparisons of the experimentally measured collision cross-section (CCS) values of the reactant and product ions obtained by the DTIMS method with those predicted by the electronic structure theory are found to be very effective for the discrimination of the produced photoisomers. The observed photochemical reaction channels are potentially significant toward uses of curcumin as a photosensitizer in photodynamic therapy.

Evaluation of Hydrogen-Deuterium Exchange during Transient Vapor Binding of MeOD with Model Peptide Systems Angiotensin II and Bradykinin

The advancement of hybrid mass spectrometric tools as an indirect probe of molecular structure and dynamics relies heavily upon a clear understanding between gas-phase ion reactivity and ion structural characteristics. This work provides new insights into gas-phase ion-neutral reactions of the model peptides (i.e., angiotensin II and bradykinin) on a per-residue basis by integrating hydrogen/deuterium exchange, ion mobility, tandem mass spectrometry, selective vapor binding, and molecular dynamics simulations. By comparing fragmentation patterns with simulated probabilities of vapor uptake, a clear link between gas-phase hydrogen/deuterium exchange and the probabilities of localized vapor association is established. The observed molecular dynamics trends related to the sites and duration of vapor binding track closely with experimental observation. Additionally, the influence of additional charges and structural characteristics on exchange kinetics and ion-neutral cluster formation is examined. These data provide a foundation for the analysis of solvation dynamics of larger, native-like conformations of proteins in the gas phase.

Tracking Isomerizations of High-Energy Adenine Cation Radicals by UV-Vis Action Spectroscopy and Cyclic Ion Mobility Mass Spectrometry

We report experimental and computational studies of protonated adenine C-8 σ-radicals that are presumed yet elusive reactive intermediates of oxidative damage to nucleic acids. The radicals were generated in the gas phase by the collision-induced dissociation of C-8-Br and C-8-I bonds in protonated 8-bromo- and 8-iodoadenine as well as by 8-bromo- and 8-iodo-9-methyladenine. Protonation by electrospray of 8-bromo- and 8-iodoadenine was shown by cyclic-ion mobility mass spectrometry (c-IMS) to form the N-1-H, N-9-H and N-3-H, N-7-H protomers in 85:15 and 81:19 ratios, respectively, in accordance with the equilibrium populations of these protomers in water-solvated ions that were calculated by density functional theory (DFT). Protonation of 8-halogenated 9-methyladenines yielded single N-1-H protomers, which was consistent with their thermodynamic stability. The radicals produced from the 8-bromo and 8-iodo adenine cations were characterized by UV-vis photodissociation action spectroscopy (UVPD) and c-IMS. UVPD revealed the formation of C-8 σ-radicals along with N-3-H, N-7-H-adenine π-radicals that arose as secondary products by hydrogen atom migrations. The isomers were identified by matching their action spectra against the calculated vibronic absorption spectra. Deuterium isotope effects were found to slow the isomerization and increase the population of C-8 σ-radicals. The adenine cation radicals were separated by c-IMS and identified by their collision cross sections, which were measured relative to the canonical N-9-H adenine cation radical that was cogenerated in situ as an internal standard. Ab initio CCSD(T)/CBS calculations of isomer energies showed that the adenine C-8 σ-radicals were local energy minima with relative energies at 76-79 kJ mol^-1 above that of the canonical adenine cation radical. Rice-Ramsperger-Kassel-Marcus calculations of unimolecular rate constants for hydrogen and deuterium migrations resulting in exergonic isomerizations showed kinetic shifts of 10-17 kJ mol^-1, stabilizing the C-8 σ-radicals. C-8 σ-radicals derived from N-1-protonated 9-methyladenine were also thermodynamically unstable and readily isomerized upon formation.

MobCal-MPI 2.0: an accurate and parallelized package for calculating field-dependent collision cross sections and ion mobilities

Ion mobility spectrometry (IMS), which can be employed as either a stand-alone instrument or coupled to mass spectrometry, has become an important tool for analytical chemistry. Because of the direct relation between an ion's mobility and its structure, which is intrinsically related to its collision cross section (CCS), IMS techniques can be used in tandem with computational tools to elucidate ion geometric structure. Here, we present MobCal-MPI 2.0, a software package that demonstrates excellent accuracy (RMSE 2.16%) and efficiency in calculating low-field CCSs via the trajectory method (≤30 minutes on 8 cores for ions with ≤70 atoms). MobCal-MPI 2.0 expands on its predecessor by enabling the calculation of high-field mobilities through the implementation of the 2^nd order approximation to two-temperature theory (2TT). By further introducing an empirical correction to account for deviations between 2TT and experiment, MobCal-MPI 2.0 can compute accurate high-field mobilities that exhibit a mean deviation of <4% from experimentally measured values. Moreover, the velocities used to sample ion-neutral collisions were updated from a weighted to a linear grid, enabling the near-instantaneous evaluation of mobility/CCS at any effective temperature from a single set of N₂ scattering trajectories. Several enhancements made to the code are also discussed, including updates to the statistical analysis of collision event sampling and benchmarking of overall performance.

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.

Understanding of protomers/deprotomers by combining mass spectrometry and computation

Multifunctional compounds may form different prototropic isomers under different conditions, which are known as protomers/deprotomers. In biological systems, these protomer/deprotomer isomers affect the interaction modes and conformational landscape between compounds and enzymes and thus present different biological activities. Study on protomers/deprotomers is essentially the study on the acidity/basicity of each intramolecular functional group and its effect on molecular structure. In recent years, the combination of mass spectrometry (MS) and computational chemistry has been proven to be a powerful and effective means to study prototropic isomers. MS-based technologies are developed to discriminate and characterize protomers/deprotomers to provide structural information and monitor transformations, showing great superiority than other experimental methods. Computational chemistry is used to predict the thermodynamic stability of protomers/deprotomers, provide the simulated MS/MS spectra, infrared spectra, and calculate collision cross-section values. By comparing the theoretical data with the corresponding experimental results, the researchers can not only determine the protomer/deprotomer structure, but also investigate the structure-activity relationship in a given system. This review covers various MS methods and theoretical calculations and their devotion to isomer discrimination, structure identification, conformational transformation, and phase transition investigation of protomers/deprotomers.

Prediction of Retention Time and Collision Cross Section (CCSH+, CCSH-, and CCSNa+) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Ultra-high performance liquid chromatography coupled to ion mobility separation and high-resolution mass spectrometry instruments have proven very valuable for screening of emerging contaminants in the aquatic environment. However, when applying suspect or nontarget approaches (i.e., when no reference standards are available), there is no information on retention time (RT) and collision cross-section (CCS) values to facilitate identification. In silico prediction tools of RT and CCS can therefore be of great utility to decrease the number of candidates to investigate. In this work, Multiple Adaptive Regression Splines (MARS) were evaluated for the prediction of both RT and CCS. MARS prediction models were developed and validated using a database of 477 protonated molecules, 169 deprotonated molecules, and 249 sodium adducts. Multivariate and univariate models were evaluated showing a better fit for univariate models to the experimental data. The RT model (R² = 0.855) showed a deviation between predicted and experimental data of ±2.32 min (95% confidence intervals). The deviation observed for CCS data of protonated molecules using the CCS_H model (R² = 0.966) was ±4.05% with 95% confidence intervals. The CCS_H model was also tested for the prediction of deprotonated molecules, resulting in deviations below ±5.86% for the 95% of the cases. Finally, a third model was developed for sodium adducts (CCS_Na, R² = 0.954) with deviation below ±5.25% for 95% of the cases. The developed models have been incorporated in an open-access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data.

Prediction of Structures of Compounds Encountered in Complex Organic Matter with Highly Flexible Alkyl Chains Using Ion Mobility-Mass Spectrometry

The chemical structure of an organic molecule has a direct influence on its three-dimensional conformation. One way to obtain information on this conformation is to use ion mobility spectrometry. This technique allows the separation of different isomers according to their collision cross section (CCS) with an inert gas. Smaller or more compact molecules will have lower collision cross section values than larger molecules. The CCS is an intrinsic ion parameter for a specific gas and is thus predictable. Today, calculations of rigid molecules are commonly performed to obtain additional structural information on an ion. However, calculations are more complex with very flexible molecules. In particular, molecules presenting long alkyl chains can yield a high number of conformers. Each conformer is then associated with a CCS value that is specific to it. We report, here, a methodology to predict CCS of flexible molecules. The used approach is based on automatic conformers research followed by geometry optimization and CCS calculations. Determination of theoretical and experimental CCS values for a rigid polycyclic aromatic hydrocarbons (PAHs) standard was used to calibrate the Mobcal software. Then, 13 standard molecules ranging from 4 to 19 carbon alkyl chains, including three long alkyl chain isomers of C₂₂H₃₈, were analyzed on a TWIMS-ToF and calculated using our methodology. CCS deviations between experimental and theoretical values were found to be less than 1.5% over the whole studied CCS range. This method was finally applied for structural analysis of petroleum compounds refractory to the hydro-denitrogenation process.

The hitchhiker's guide to dynamic ion-solvent clustering: applications in differential ion mobility spectrometry

This article highlights the fundamentals of ion-solvent clustering processes that are pertinent to understanding an ion's behaviour during differential mobility spectrometry (DMS) experiments. We contrast DMS with static-field ion mobility, where separation is affected by mobility differences under the high-field and low-field conditions of an asymmetric oscillating electric field. Although commonly used in mass spectrometric (MS) workflows to enhance signal-to-noise ratios and remove isobaric contaminants, the chemistry and physics that underpins the phenomenon of differential mobility has yet to be fully fleshed out. Moreover, we are just now making progress towards understanding how the DMS separation waveform creates a dynamic clustering environment when the carrier gas is seeded with the vapour of a volatile solvent molecule (e.g., methanol). Interestingly, one can correlate the dynamic clustering behaviour observed in DMS experiments with gas-phase and solution-phase molecular properties such as hydrophobicity, acidity, and solubility. However, to create a generalized, global model for property determination using DMS data one must employ machine learning. In this article, we provide a first-principles description of differential ion mobility in a dynamic clustering environment. We then discuss the correlation between dynamic clustering propensity and analyte physicochemical properties and demonstrate that analytes exhibiting similar ion-solvent interactions (e.g., charge-dipole) follow well-defined trends with respect to DMS clustering behaviour. Finally, we describe how supervised machine learning can be used to create predictive models of molecular properties using DMS data. We additionally highlight open questions in the field and provide our perspective on future directions that can be explored.

Tautomers and Rotamers of Curcumin: A Combined UV Spectroscopy, High-Performance Liquid Chromatography, Ion Mobility Mass Spectrometry, and Electronic Structure Theory Study

The structures of tautomers and rotameric forms of curcumin, the bioactive compound present in spice plant turmeric, have been investigated using ion mobility mass spectrometry (IMMS) in conjunction with high-performance liquid chromatography (HPLC) and UV-visible spectroscopy. Two tautomeric forms of this β-diketone compound, keto-enol and diketo, have been chromatographically separated, and the electronic absorption spectra for these two tautomeric forms in methanol solution have been recorded separately for the first time. The molecular identity of the HPLC-separated solution fractions is established unambiguously by recording the mass and fragmentation spectra simultaneously. The ion mobility spectrum for the deprotonated curcumin anion, [Cur-H]^-, corresponding to the diketo tautomer, displays only one peak (P), and the collision cross-section (CCS) value is measured to be 185.9 Ų. However, the ion mobility spectrum corresponding to the HPLC-separated keto-enol tautomer shows three distinctly separated peaks, P, Q, and R, with CCS values of 185.9, 194.8, and 203.4 Ų, respectively, whereby peak R appears to be the most intense one, followed by peaks P and Q. The theoretically calculated CCS values of different isomers of [Cur-H]^-, optimized by electronic structure theory methods, display satisfactory correlation with the experimentally observed values, corroborating our assignments. The spectral attributes also indicate the occurrence of structural rearrangements in the electrospray ionization process. With the aid of the electronic structure calculation, low-energy pathways for the occurrence of the structural isomerization to surpass the energy barrier are suggested, which are consistent with the assignments of the peaks observed in the IM spectra.

Improved First-Principles Model of Differential Mobility Using Higher Order Two-Temperature Theory

Differential mobility spectrometry is a separation technique that may be applied to a variety of analytes ranging from small molecule drugs to peptides and proteins. Although rudimentary theoretical models of differential mobility exist, these models are often only applied to small molecules and atomic ions without considering the effects of dynamic microsolvation. Here, we advance our theoretical description of differential ion mobility in pure N₂ and microsolvating environments by incorporating higher order corrections to two-temperature theory (2TT) and a pseudoequilibrium approach to describe ion-neutral interactions. When comparing theoretical predictions to experimentally measured dispersion plots of over 300 different compounds, we find that higher order corrections to 2TT reduce errors by roughly a factor of 2 when compared to first order. Model predictions are accurate especially for pure N₂ environments (mean absolute error of 4 V at SV = 4000 V). For strongly clustering environments, accurate thermochemical corrections for ion-solvent clustering are likely required to reliably predict differential ion mobility behavior. Within our model, general trends associated with clustering strength, solvent vapor concentration, and background gas temperature are well reproduced, and fine structure visible in some dispersion plots is captured. These results provide insight into the dynamic ion-solvent clustering process that underpins the phenomenon of differential ion mobility.

Least absolute shrinkage and selection operator-based prediction of collision cross section values for ion mobility mass spectrometric analysis of lipids

A least absolute shrinkage and selection operator (LASSO)-based prediction method was developed for the prediction of lipids’ CCS values.

Ion Mobility Mass Spectrometry Analysis of Oxygen Affinity-Associated Structural Changes in Hemoglobin

Hemoglobin (Hb) is a major oxygen-transporting protein with allosteric properties reflected in the structural changes that accompany binding of O₂. Glycated hemoglobin (GHb), which is a minor component of human red cell hemolysate, is generated by a nonenzymatic reaction between glucose and hemoglobin. Due to the long lifetime of human erythrocytes (∼120 days), GHb is widely used as a reliable biomarker for monitoring long-term glucose control in diabetic patients. Although the structure of GHb differs from that of Hb, structural changes relating to the oxygen affinity of these proteins remain incompletely understood. In this study, the oxygen-binding kinetics of Hb and GHb are evaluated, and their structural dynamics are investigated using solution small-angle X-ray scattering (SAXS), electrospray ionization mass spectrometry equipped with ion mobility spectrometry (ESI-IM-MS), and molecular dynamic (MD) simulations to understand the impact of structural alteration on their oxygen-binding properties. Our results show that the oxygen-binding kinetics of GHb are diminished relative to those of Hb. ESI-IM-MS reveals structural differences between Hb and GHb, which indicate the preference of GHb for a more compact structure in the gas phase relative to Hb. MD simulations also reveal an enhancement of intramolecular interactions upon glycation of Hb. Therefore, the more rigid structure of GHb makes the conformational changes that facilitate oxygen capture more difficult creating a delay in the oxygen-binding process. Our multiple biophysical approaches provide a better understanding of the allosteric properties of hemoglobin that are reflected in the structural alterations accompanying oxygen binding.

The relevant role of ion mobility separation in LC-HRMS based screening strategies for contaminants of emerging concern in the aquatic environment

Ion mobility separation (IMS) coupled to high resolution mass spectrometry (IMS-HRMS) is a promising technique for (non-)target/suspect analysis of micropollutants in complex matrices. IMS separates ionized compounds based on their charge, shape and size facilitating the removal of co-eluting isomeric/isobaric species. Additionally, IMS data can be translated into collision cross-section (CCS) values, which can be used to increase the identification reliability. However, IMS-HRMS for the screening of contaminants of emerging concern (CECs) have been scarcely explored. In this study, the role of IMS-HRMS for the identification of CECs in complex matrices is highlighted, with emphasis on when and with which purpose is of use. The utilization of IMS can result in much cleaner mass spectra, which considerably facilitates data interpretation and the obtaining of reliable identifications. Furthermore, the robustness of IMS measurements across matrices permits the use of CCS as an additional relevant parameter during the identification step even when reference standards are not available. Moreover, an effect on the number of true and false identifications could be demonstrated by including IMS restrictions within the identification workflow. Data shown in this work is of special interest for environmental researchers dealing with the detection of CECs with state-of-the-art IMS-HRMS instruments.

Modular Ion Mobility Calibrants for Organometallic Anions Based on Tetraorganylborate Salts

Organometallics are widely used in catalysis and synthesis. Their analysis relies heavily on mass spectrometric methods, among which traveling-wave ion mobility spectrometry (TWIMS) has gained increasing importance. Collision cross sections (CCS) obtainable by TWIMS significantly aid the structural characterization of ions in the gas phase, but for organometallics, their accuracy has been limited by the lack of appropriate calibrants. Here, we propose tetraorganylborates and their alkali-metal bound oligomers [M_n-1(BR₄)_n]^- (M = Li, Na, K, Rb, Cs; R = aryl, Et; n = 1-6) as calibrants for electrospray ionization (ESI) TWIMS. These species chemically resemble typical organometallics and readily form upon negative-ion mode ESI of solutions of alkali-metal tetraorganylborates. By combining different tetraorganylborate salts, we have generated a large number of anions in a modular manner and determined their CCS values by drift-tube ion mobility spectrometry (DTIMS) (^DTCCS_He = 81-585, ^DTCCS_N2 = 130-704 Ų). In proof-of-concept experiments, we then applied these ^DTCCS values to the calibration of a TWIMS instrument and analyzed phenylcuprate and argentate anions, [Li_n-1M_nPh_2n]^- and [M_nPh_n+1]^- (M = Cu, Ag), as prototypical reactive organometallics. The ^TWCCS_N2 values derived from TWIMS measurements are in excellent agreement with those determined by DTIMS (<2% relative difference), demonstrating the effectiveness of the proposed calibration scheme. Moreover, we used theoretical methods to predict the structures and CCS values of the anions considered. These predictions are in good agreement with the experimental results and give further insight into the trends governing the assembly of tetraorganylborate, cuprate, and argentate oligomers.

In situ antioxidation-assisted matrix solid-phase dispersion microextraction and discrimination of chiral flavonoids from citrus fruit via ion mobility quadrupole time-of-flight high-resolution mass spectrometry

A simple and sensitive in situ antioxidation process assisted with a matrix solid-phase dispersion method for extracting chiral flavonoids in citrus fruit was established, and samples were further analyzed using ion mobility quadrupole time-of-flight high-resolution mass spectrometry. The collision cross-sections of the target compounds were studied using single-field and stepped-field methods. The optimal conditions were obtained using 30 mg of C₁₈ as a dispersant, methanol as an elution solvent and 0.6 mM 1,1-diphenyl-2-picrylhydrazyl (DPPH) as a radical solution. Additionally, the method showed satisfactory limits of detection (3.70-6.52 ng/mL) and good recoveries (96.78-104.67%) for four flavonoids in citrus fruit. The IC₅₀ values of DPPH radical-scavenging activities ranged from 817.8 to 981.55 μg/mL for tested samples. The method was a good alternative for the microextraction and determination of antioxidant capacity and chiral differentiation of narirutin, naringin, hesperidin and neohesperidin in citrus fruit.

Isomers and Rotamers of DCM in Methanol and in Gas Phase Probed by Ion Mobility Mass Spectrometry in Combination with High Performance Liquid Chromatography

An integrated method of ion mobility mass spectrometry and high-performance liquid chromatography (HPLC) has been used to investigate the isomeric distribution of a popular fluorescent dye DCM (4-(dicyanomethylene)-2-methyl-6-(4-dimethylaminostyryl)-4H-pyran) in methanol solution. Chromatographic separation of DCM isomers in methanol has been performed by probing the molecular mass (DCMH⁺), and two distinctly separated peaks are observed at retention times 3.73 (peak-I) and 3.87 (peak-II) min, where the latter one appears nearly twice as intense as the former. However, peak-I appears much weaker compared to peak-II if the chromatogram is recorded by optical probing at the absorption maximum of this dye (467 nm). The ion mobility (IM) spectra of DCMH⁺ ions corresponding to each of the LC-separated factions show three common peaks A, B, and C, with collision cross-section (CCS) values of 174, 185, and 197 Ų, respectively, but their relative intensities in the two IM spectra appear in opposite sequences. The three IM peaks have been assigned by considering the theoretically calculated CCS values of 13 possible isomers of DCMH⁺ ions. The IM spectral features also reveal that isomeric interconversions occur during the ESI process. Electronic structure calculations have been used to optimize the geometries of the four isomers of solvated DCM and the corresponding protomeric structures of DCMH⁺. The isomerization pathways and associated energy barriers have also been calculated. The gas-phase protomers are found to follow a completely different sequence of stability as compared to the neutral isomers. The analysis reveals that peak-I corresponds to one of the cis isomers, whereas peak-II arises due to cumulative contributions of the other three isomers. The absorption spectrum of DCM in methanol is simulated from the computed spectral profiles of the isomers which indicates a distribution of trans1, trans2, cis1, and cis2 isomers as 33.5, 61.5, 2.0, and 3.0%, respectively. The fragmentation behavior of DCMH⁺ ions in a collision-induced dissociation experiment has been found to be isomer dependent.

Breaking Down Structural Diversity for Comprehensive Prediction of Ion-Neutral Collision Cross Sections

Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or drug metabolite identification. Ion mobility-mass spectrometry (IM-MS) provides rapid two-dimensional separation of ions based on their mobility through a neutral buffer gas. The mobility of an ion is related to its collision cross section (CCS) with the buffer gas, a physical property that is determined by the size and shape of the ion. This structural dependency makes CCS a promising characteristic for compound identification, but this utility is limited by the availability of high-quality reference CCS values. CCS prediction using machine learning (ML) has recently shown promise in the field, but accurate and broadly applicable models are still lacking. Here we present a novel ML approach that employs a comprehensive collection of CCS values covering a wide range of chemical space. Using this diverse database, we identified the structural characteristics, represented by molecular quantum numbers (MQNs), that contribute to variance in CCS and assessed the performance of a variety of ML algorithms in predicting CCS. We found that by breaking down the chemical structural diversity using unsupervised clustering based on the MQNs, specific and accurate prediction models for each cluster can be trained, which showed superior performance than a single model trained with all data. Using this approach, we have robustly trained and characterized a CCS prediction model with high accuracy on diverse chemical structures. An all-in-one web interface (https://CCSbase.net) was built for querying the CCS database and accessing the predictive model to support unknown compound identifications.

Liquid chromatography-drift tube ion mobility-mass spectrometry as a new challenging tool for the separation and characterization of silymarin flavonolignans

Silymarin, milk thistle (Silybum marianum) extract, contains a mixture of mostly isomeric bioactive flavonoids and flavonolignans that are extensively studied, especially for their possible liver-protective and anticancer effects. Because of the differing bioactivities of individual isomeric compounds, characterization of their proportion in a mixture is highly important for predicting its effect on health. However, because of silymarin's complexity, this is hardly feasible by common analytical techniques. In this work, ultraperformance liquid chromatography coupled with drift tube ion mobility spectrometry and quadrupole time-of-flight mass spectrometry was used. Eleven target silymarin compounds (taxifolin, isosilychristin, silychristins A and B, silydianin, silybins A and B, 2,3-cis-silybin B, isosilybins A and B and 2,3-dehydrosilybin) and five unknown flavonolignan isomers detected in the milk thistle extract were fully separated in a 14.5-min analysis run. All the compounds were characterized on the basis of their accurate mass, retention time, drift time, collision cross section and fragmentation spectra. The quantitative approach based on evaluation of the ion mobility data demonstrated lower detection limits, an extended linear range and total separation of interferences from the compounds of interest compared with the traditional approach based on evaluation of liquid chromatography-quadrupole time-of-flight mass spectrometry data. The following analysis of a batch of milk thistle-based food supplements revealed significant variability in the silymarin pattern, especially in the content of silychristin A and silybins A and B. This newly developed method might have high application potential, especially for the characterization of materials intended for bioactivity studies in which information on the exact silymarin composition plays a crucial role. Graphical Abstract.

A First Principle Model of Differential Ion Mobility: the Effect of Ion-Solvent Clustering

The use of differential mobility spectrometry (DMS) as a separation tool prior to mass analysis has increased in popularity over the years. However, the fundamental principles behind the difference between high- and low-field mobility is still a matter of debate-especially regarding the strong impact of solvent molecules added to the gas phase in chemically modified DMS environments. In this contribution, we aim to present a thorough model for the determination of the ion mobility over a wide range of field strengths and subsequent calculation of DMS dispersion plots. Our model relies on first principle calculations only, incorporating the modeling of the "hard-sphere" mobility, the change in CCS with field strength, and the degree of clustering of solvent molecules to the ion. We show that all three factors have to be taken into account to qualitatively predict dispersion plots. In particular, type A behavior (i.e., strong clustering) in DMS can only be explained by a significant change of the mean cluster size with field strengths. The fact that our model correctly predicts trends between differently strong binding solvents, as well as the solvent concentration and the background gas temperature, highlights the importance of clustering for differential mobility.

ISiCLE: A Quantum Chemistry Pipeline for Establishing in Silico Collision Cross Section Libraries

High-throughput, comprehensive, and confident identifications of metabolites and other chemicals in biological and environmental samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent technological advances, metabolomics studies still result in the detection of a disproportionate number of features that cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics, the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers (i.e., conformational isomers) using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs first-principles simulation, distinguished by the use of molecular dynamics, quantum chemistry, and ion mobility calculations, to generate structures and chemical property libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over 2 orders of magnitude. Calculated CCS values were validated against 1983 experimentally measured CCS values and compared to previously reported CCS calculation approaches. Average calculated CCS error for the validation set is 3.2% using standard parameters, outperforming other density functional theory (DFT)-based methods and machine learning methods (e.g., MetCCS). An online database is introduced for sharing both calculated and experimental CCS values ( metabolomics.pnnl.gov ), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described, including providing evidence for the presence of an environmental degradation product, the separation of molecular isomers, and an initial characterization of complex blinded mixtures of exposure chemicals. This work represents a method to address the limitations of small molecule identification and offers an alternative to generating chemical identification libraries experimentally by analyzing authentic reference materials. All code is available at github.com/pnnl .

A Cl- Hinge for Cyclen Macrocycles: Ionic Interactions and Tweezer-Like Complexes

The supramolecular networks derived from the complexation of polyazamacrocycles with halide anions constitute fundamental building blocks of a broad range of modern materials. This study provides insights into the conformational framework that supports the binding of protonated cyclen macrocyles (1,4,7,10-Tetraazacyclododecane) by chloride anions through NHδ+···Cl- interactions. The isolated complex comprised of two cyclen hosts linked by one Cl- anion is characterized by means of infrared action spectroscopy and ion mobility mass spectrometry, in combination with quantum chemical computations. The Cl- anion is found to act as a hinge that bridges the protonatedNH 2 + moieties of the two macrocycles leading to a molecular tweezer configuration. Different types of conformations emerge, depending on whether the trimer adopts an open arrangement, with significant freedom for internal rotation of the cyclen moieties, or it locks in a folded conformation with intermolecular H-bonds between the two cyclen backbones. The ion mobility collision cross section supports that folded configurations of the complex are dominant under isolated conditions in the gas phase. The IRMPD spectroscopy experiments suggest that two qualitatively different families of folded conformations coexist at room temperature, featuring either peripheral or inner positions of the anion with respect to the macrocycle cavities, These findings should have implications in the growth of extended networks in the nanoscale and in sensing applications.

A parallelized molecular collision cross section package with optimized accuracy and efficiency

A new parallelized calculation package predicts collision cross sections with high accuracy and efficiency.

Chiral differentiation of d- and l-isoleucine using permethylated β-cyclodextrin: infrared multiple photon dissociation spectroscopy, ion-mobility mass spectrometry, and DFT calculations

Chiral differentiation of protonated isoleucine (Ile) using permethylated β-cyclodextrin (perCD) in the gas-phase was studied using infrared multiple photon dissociation (IRMPD) spectroscopy, ion-mobility, and density functional theory (DFT) calculations. The gaseous protonated non-covalent complexes of perCD and d-Ile or l-Ile produced by electrospray ionization were interrogated by laser pulses in the wavenumber region of 2650 to 3800 cm-1. The IRMPD spectra showed remarkably different IR spectral features for the d-Ile or l-Ile and perCD non-covalent complexes. However, drift-tube ion-mobility experiments provided only a small difference in their collision cross-sections, and thus a limited separation of the d- and l-Ile complexes. DFT calculations revealed that the chiral distinction of the d- and l-complexes by IRMPD spectroscopy resulted from local interactions of the protonated Ile with perCD. Furthermore, the theoretical results showed that the IR absorption spectra of higher energy conformers (by ∼13.7 kcal mol-1) matched best with the experimentally observed IRMPD spectra. These conformers are speculated to be formed from kinetic-trapping of the solution-phase conformers. This study demonstrated that IRMPD spectroscopy provides an excellent platform for differentiating the subtle chiral difference of a small amino acid in a cyclodextrin-complexation environment; however, drift-tube ion-mobility did not have sufficient resolution to distinguish the chiral difference.

Comparison of Peptide Ion Conformers Arising from Non-Helical and Helical Peptides Using Ion Mobility Spectrometry and Gas-Phase Hydrogen/Deuterium Exchange

The dominant gas-phase conformer of [M+3H]³⁺ ions of the model peptide acetyl-PSSSSKSSSSKSSSSKSSSSK has been examined with ion mobility spectrometry (IMS), gas-phase hydrogen deuterium exchange (HDX), and mass spectrometry (MS) techniques. The [M+3H]³⁺ peptide ions are observed predominantly as a relatively compact conformer type. Upon subjecting these ions to electron transfer dissociation (ETD), the level of protection for each amino acid residue in the peptide sequence is assessed. The overall per-residue deuterium uptake is observed to be relatively more efficient for the neutral residues than for the model peptide acetyl-PAAAAKAAAAKAAAAKAAAAK. In comparison, the N-terminal and C-terminal regions of the serine peptide show greater relative protection compared with interior residues. Molecular dynamics (MD) simulations have been used to generate candidate structures for collision cross section and HDX reactivity matching. Hydrogen accessibility scoring (HAS) for select structural candidates from MD simulations has been used to suggest conformer types that could contribute to the observed HDX patterns. The results are discussed with respect to recent studies employing extensive MD simulations of gas-phase structure establishment of a peptide system. Graphical Abstract ᅟ.