Experimental Collision Cross Sections Research Articles

Large-scale prediction of collision cross-section with very deep graph convolutional network for small molecule identification

Ion mobility spectrometry (IMS) is a promising analytical technique for mass spectrometry (MS)-based compound identification by providing collision cross-section (CCS) value as an additional dimension with structural information. Here, GraphCCS was proposed to accurately predict the CCS value and expand the coverage of CCS libraries. A new adduct encoding method was proposed to encode SMILES strings and adduct types of compounds into adduct graphs. GraphCCS extended its predictive capability to ten different adduct types. A very deep graph convolutional network with up to 40 GCN layers was built to predict CCS values from adduct graphs. A curated dataset with 12,775 experimental CCS values was used to train, validate, and test the GraphCCS model. The resulting CCS predictions achieved a median relative error (MedRE) of 0.94 % and a coefficient of determination (R2) of 0.994 on the test set. Results on external test sets showed that GraphCCS outperformed AllCCS2, CCSbase, SigmaCCS, and DeepCCS. Based on the developed GraphCCS method, a large-scale in-silico database was built, including 2,394,468 CCS values. Those CCS values can be used to filter false positives complementary to retention times and tandem mass spectra. Finally, the effectiveness of GraphCCS in assisting compound identification was tested on a mouse adrenal gland lipid dataset with 1,960 lipids. The results demonstrated that the in-silico CCS values combined with MS spectra and retention times can efficiently filter the false positive candidates.

Elucidation of Dithiol-yne Comb Polymer Architectures by Tandem Mass Spectrometry and Ion Mobility Techniques.

Polymers have a wide range of applications depending on their composition, size, and architecture. Varying any of these three characteristics can greatly impact the resulting chemical, physical, and mechanical properties. While many techniques are available to determine polymer composition and size, determining the exact polymer architecture is more challenging. Herein, tandem mass spectrometry (MS/MS) and ion mobility mass spectrometry (IM-MS) methods are utilized to derive crucial architectural information about dithiol-yne comb polymers. Based on their unique fragmentation products and IM drift times, dithiol-yne oligomers with distinct architectures were successfully differentiated and characterized. Additionally, experimental collision cross-sections (Ω) derived via IM-MS were compared to theoretically extracted Ω values from molecular dynamics simulated structures to deduce the architectural motif of these comb oligomers. Overall, this work demonstrates the benefits of combining various mass spectrometry techniques in order to gain a complete understanding of a complex polymer mixture.

Isomerism of Cyclodextrin Tetramer Induced by Alkali Halide Cluster Ions Observed by Ion Mobility Spectrometry-Mass Spectrometry.

Cyclodextrins (CDs) exhibit versatile self-assembly properties due to their hydrophilic and hydrophobic components, with applications such as drug delivery and selective binding. While research on CD self-assembly is extensive, limited studies have explored their aggregation behavior, particularly in interactions with small ionic guests. The present work investigates the structure of β-CD tetramers aggregated with alkali metal chloride clusters using ion mobility spectrometry-mass spectrometry (IMS-MS). The results revealed that diverse structures emerge in the tetramer depending on the alkali metal cluster size. Notably, the doubly charged tetramer exhibits distinct aggregation trends with specific numbers of MCl clusters for Na+ and K+ ions. After initially adopting a bucket-wheel structure with two internal cations, the structure transforms into a new isomer with a tetrahedral configuration upon cluster addition. The formation of the new isomer structure is closely linked to filling the cavity volume with MCl clusters and ionic interactions, which possibly compensate for the weakened hydrogen bonds between CDs. Theoretical calculations further support the structures, showing well-matched collision cross-section (CCS) values compared with the experimental CCS values. This study highlights the role of alkali metal chloride clusters as potential templates, leading to the formation of novel CD assemblies.

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants.

Ion mobility spectrometry (IMS) is a rapid gas-phase separation technique, which can distinguish ions on the basis of their size, shape, and charge. The IMS-derived collision cross section (CCS) can serve as additional identification evidence for the screening of environmental organic micropollutants (OMPs). In this work, we summarize the published experimental CCS values of environmental OMPs, introduce the current CCS prediction tools, summarize the use of IMS and CCS in the analysis of environmental OMPs, and finally discussed the benefits of IMS and CCS in environmental analysis. An up-to-date CCS compendium for environmental contaminants was produced by combining CCS databases and data sets of particular types of environmental OMPs, including pesticides, drugs, mycotoxins, steroids, plastic additives, per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs), as well as their well-known transformation products. A total of 9407 experimental CCS values from 4170 OMPs were retrieved from 23 publications, which contain both drift tube CCS in nitrogen (DTCCSN2) and traveling wave CCS in nitrogen (TWCCSN2). A selection of publicly accessible and in-house CCS prediction tools were also investigated; the chemical space covered by the training set and the quality of CCS measurements seem to be vital factors affecting the CCS prediction accuracy. Then, the applications of IMS and the derived CCS in the screening of various OMPs were summarized, and the benefits of IMS and CCS, including increased peak capacity, the elimination of interfering ions, the separation of isomers, and the reduction of false positives and false negatives, were discussed in detail. With the improvement of the resolving power of IMS and enhancements of experimental CCS databases, the practicability of IMS in the analysis of environmental OMPs will continue to improve.

Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples

The collision cross-sections (CCS) measurement using ion mobility spectrometry (IMS) in combination with mass spectrometry (MS) offers a great opportunity to increase confidence in metabolite identification. However, owing to the lack of sensitivity and resolution, IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites (VLMs ≤ 250 Da). Here, we describe an analytical method using ultrahigh-performance liquid chromatography (UPLC) coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples. The experimental CCS values, along with mass spectral properties, were reported for the 174 metabolites. The experimental data included the mass-to-charge ratio (m/z), retention time (RT), tandem MS (MS/MS) spectra, and CCS values. Among the studied metabolites, 263 traveling wave ion mobility spectrometry (TWIMS)-derived CCS values (TWCCSN2) were reported for the first time, and more than 70% of these were CCS values of VLMs. The TWCCSN2 values were highly repeatable, with inter-day variations of <1% relative standard deviation (RSD). The developed method revealed excellent TWCCSN2 accuracy with a CCS difference (ΔCCS) within ±2% of the reported drift tube IMS (DTIMS) and TWIMS CCS values. The complexity of the urine matrix did not affect the precision of the method, as evidenced by ΔCCS within ±1.92%. According to the Metabolomics Standards Initiative, 55 urinary metabolites were identified with a confidence level of 1. Among these 55 metabolites, 53 (96%) were VLMs. The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values, which clearly increased metabolite identification confidence.

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.

The IMSCal approach to determine collision cross section of multiply charged anions in traveling wave ion mobility spectrometry

The need for appropriate standards to calibrate ion arrival times in traveling wave ion mobility (TWIM) remains an issue for collision cross section (CCS) measurements, particularly in the case of multiply charged anions due to the scarcity of calibrants in the negative ion mode. In order to circumvent constraints raised for standards in the conventional power law calibration, the new approach recently implemented in the IMSCal software (Anal. Chem. 93 (2021) 3542–3550) has been evaluated here to derive CCS of multiply charged anions measured by TWIM. The mathematical model developed in IMSCal to describe ion motion in the TWIM cell was trained with different combinations of phosphoric acid clusters and deprotonated polyalanine standards and performance of so-obtained calibrations was evaluated for multiply deprotonated oligothymidine 10mers used as control analytes. Although optimal composition of the calibrant set could not be fully rationalized, one mandatory condition for best CCS accuracy is to include standards of different charge states to properly model the effects of radial distribution of ions in the TWIM cell. Further improvement of calibration robustness requires that one of these charge states equals that of the analytes to account for the effects of velocity relaxation also incorporated in the IMSCal model. Doing so, experimental CCS values could be readily obtained with relative error below ±5% for anions of charge state up to 6–.

Highly accurate and large-scale collision cross sections prediction with graph neural networks

The collision cross section (CCS) values derived from ion mobility spectrometry can be used to improve the accuracy of compound identification. Here, we have developed the Structure included graph merging with adduct method for CCS prediction (SigmaCCS) based on graph neural networks using 3D conformers as inputs. A model was trained, evaluated, and tested with >5,000 experimental CCS values. It achieved a coefficient of determination of 0.9945 and a median relative error of 1.1751% on the test set. The model-agnostic interpretation method and the visualization of the learned representations were used to investigate the chemical rationality of SigmaCCS. An in-silico database with 282 million CCS values was generated for three different adduct types of 94 million compounds. Its source code is publicly available at https://github.com/zmzhang/SigmaCCS. Altogether, SigmaCCS is an accurate, rational, and off-the-shelf method to directly predict CCS values from molecular structures.

Exploring Isomerism in Isolated Cyclodextrin Oligomers through Trapped Ion Mobility Mass Spectrometry.

Cyclodextrin (CD) macrocycles are used to create a wide range of supramolecular architectures which are also of interest in applications such as selective gas adsorption, drug delivery, and catalysis. However, predicting their assemblies and identifying the possible isomers in CD oligomers have always remained challenging due to their dynamic nature. Herein, we interacted CDs (α, β, and γ) with a divalent metal ion, Cu2+, to create a series of Cu2+-linked CD oligomers, from dimers to pentamers. We characterized these oligomers using electrospray ionization mass spectrometry and probed isomerism in each of these isolated oligomers using high resolution trapped ion mobility spectrometry. Using this technique, we separated multiple isomers for each of the Cu2+-interlinked CD oligomers and estimated their relative population, which was not accessible previously using other characterization techniques. We further carried out structural analysis of the observed isomers by comparing the experimental collision cross sections (CCSs) to that of modeled structures. We infer that the isomeric heterogeneity reflects size-specific packing patterns of individual CDs (e.g., close-packed/linear). In some cases, we also reveal the existence of kinetically trapped structures in the gas phase and study their transformation to thermodynamically controlled forms by examining the influence of activation of the ions on isomer interconversion.

Structures and dissociation of iron porphyrin complexes by ion mobility and collision-induced dissociation mass spectrometry

A combination of ion mobility mass spectrometry (IMS-MS), collision-induced dissociation (CID), Rice–Ramsperger–Kassel–Marcus modeling, and computational chemistry was used to determine the structure and unimolecular chemistry of dimeric and trimeric sulfonated meso-tetraphenylporphyrins with negative charges from −2 to −5. By comparing experimental collision cross sections obtained from calibrated IMS drift times with calculated cross sections for the lowest energy calculated structures, it was confirmed that dimer species have a bridged structure where the two monomers are connected through iron–sulfonic interactions. Dimer species with the charge states −4 and −5 dissociate into two monomer units where the charge is distributed between the monomers. Dimers with lower charge states also lose neutral SO2 and SO3 groups. For trimeric species with charge states of −3 and −4, IMS identifies three and two isomers, respectively. It was confirmed that the −4 charged trimer isomers consist of one with three stacked monomers and one in which the third monomer unit is connected to a stacked dimer via two iron–sulfonic bonds (bridged/stacked). Both yielded the same CID breakdown diagram confirming that the two isomers likely interconvert prior to dissociation. The significantly larger density of states of the bridged–stacked structure compared with the stacked structure means the former is likely the reactive configuration.

Mass Spectrometry, Ion Mobility Separation and Molecular Modelling: A Powerful Combination for the Structural Characterisation of Substituted Cyclodextrins Mixtures

When working on the synthesis of substituted cyclodextrins (CDs), the main challenge remains the analysis of the reaction media content. Our objective in this study was to fully characterise a complex isomers mixture of Lipidyl-βCDs (LipβCD) obtained with a degree of substitution 1 (DS = 1) from a one-step synthesis pathway. The benefit of tandem mass spectrometry (MS/MS) and ion mobility separation hyphenated with mass spectrometry (IM-MS) was investigated. The MS/MS fragment ion's relative intensities were analysed by principal component analysis (PCA) to discriminate isomers. The arrival time distribution (ATD) of each isomer was recorded using a travelling wave ion mobility (TWIM) cell allowing the determination of their respective experimental collision cross section (CCSexp). The comparison with the predicted theoretical CCS (CCSth) obtained from theoretical calculations propose a regioisomer assignment according to the βCD hydroxyl position (2, 3, or 6) involved in the reaction. These results were validated by extensive NMR structural analyses of pure isomers combined with molecular dynamics simulations. This innovative approach seems to be a promising tool to elucidate complex isomer mixtures such as substituted cyclodextrin derivatives.

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.

Revealing the differences in collision cross section values of small organic molecules acquired by different instrumental designs and prediction models

The number of open access databases containing experimental and predicted collision cross section (CCS) values is rising and leads to their increased use for compound identification. However, the reproducibility of reference values with different instrumental designs and the comparison between predicted and experimental CCS values is still under evaluation.This study compared experimental CCS values of 56 small molecules (Contaminants of Emerging Concern) acquired by both drift tube (DT) and travelling wave (TW) ion mobility mass spectrometry (IM-MS). The TWIM-MS included two instrumental designs (Synapt G2 and VION). The experimental TWCCSN2 values obtained by the TWIM-MS systems showed absolute percent errors (APEs) < 2% in comparison to experimental DTIMS data, indicating a good correlation between the datasets. Furthermore, TWCCSN2 values of [M − H]- ions presented the lowest APEs. An influence of the compound class on APEs was observed.The applicability of prediction models based on artificial neural networks (ANN) and multivariate adaptive regression splines (MARS), both built using TWIM-MS data, was investigated for the first time for the prediction of DTCCSN2 values. For [M+H]+ and [M − H]- ions, the 95th percentile confidence intervals of observed APEs were comparable to values reported for both models indicating a good applicability for DTIMS predictions.For the prediction of DTCCSN2 values of [M+Na]+ ions, the MARS based model provided the best results with 73.9% of the ions showing APEs below the threshold reported for [M+Na]+. Finally, recommendations for database transfer and applications of prediction models for future DTIMS studies are made.

Probing topology of supramolecular complexes between cyclodextrins and alkali metals by ion mobility-mass spectrometry

In this study, the size and shape of supramolecular assemblies between cyclo-oligosaccharides and proton, ammonium or a series of alkali metals by electrospray coupled to trapped ion mobility-mass spectrometry (ESI-TIMS) have investigated. Native cyclodextrins (CD) were selected as models, and collision cross section (CCS) values were deducted for the main positive singly and doubly charged species. Experimental CCS values were in good agreement with those obtained from molecular modeling. Due to the high mobility resolving power and resolution, it was possible to highlight the presence of various conformers. Also, TIMS allowed to discriminate and estimate the content of various orientations from non-covalent nanotubes-based CD, involving secondary/secondary rim hydroxyl groups (head-to head), primary/secondary rim (head-to-tail) hydroxyl groups or primary/primary rim (tail-to-tail) hydroxyl groups interactions. Such results pave the way for a better knowledge of the topology of cyclo-oligosaccharides based supramolecular complexes, demonstrating that TIMS can be a particularly attractive molecular descriptor.

Structural Studies of a Stapled Peptide with Native Ion Mobility-Mass Spectrometry and Transition Metal Ion Förster Resonance Energy Transfer in the Gas Phase.

Native mass spectrometry has emerged as an important tool for gas-phase structural biology. However, the conformations that a biomolecular ion adopts in the gas phase can differ from those found in solution. Herein, we report a synergistic, native ion mobility-mass spectrometry (IM-MS) and transition metal ion Förster resonance energy transfer (tmFRET)-based approach to probe the gas-phase ion structures of a nonstapled peptide (nsp; Ac-CAARAAHAAAHARARA-NH2) and a stapled peptide (sp; Ac-CXARAXHAAAHARARA-NH2). The stapled peptide contains a single hydrocarbon chain connecting the peptide backbone in the i and i + 4 positions via a Grubbs ring-closure metathesis. Fluorescence lifetime measurements indicated that the Cu-bound complexes of carboxyrhodamine 6g (crh6g)-labeled stapled peptide (sp-crh6g) had a shorter donor-acceptor distance (rDA) than the labeled nonstapled peptide (nsp-crh6g). Experimental collision cross-section (CCS) values were then determined by native IM-MS, which could separate the conformations of Cu-bound complexes of nsp-crh6g and sp-crh6g. Finally, the experimental CCS (i.e., shape) and rDA (i.e., distance) values were used as constraints for computational studies, which unambiguously revealed how a staple reduces the elongation of the peptide ions in the gas phase. This study demonstrates the superiority of combining native IM-MS, tmFRET, and computational studies to investigate the structure of biomolecular ions.

Structural Characterization of Dendriplexes In Vacuo: A Joint Ion Mobility/Molecular Dynamics Investigation.

The combination between ion mobility mass spectrometry and molecular dynamics simulations is demonstrated for the first time to afford valuable information on structural changes undergone by dendriplexes containing ds-DNA and low-generation dendrimers when transferred from the solution to the gas phase. Dendriplex ions presenting 1:1 and 2:1 stoichiometries are identified using mass spectrometry experiments, and the collision cross sections (CCS) of the 1:1 ions are measured using drift time ion mobility experiments. Structural predictions using Molecular Dynamics (MD) simulations showed that gas-phase relevant structures, i.e., with a good match between the experimental and theoretical CCS, are generated when the global electrospray process is simulated, including the solvent molecule evaporation, rather than abruptly transferring the ions from the solution to the gas phase. The progressive migration of ammonium groups (either NH4+ from the buffer or protonated amines of the dendrimer) into the minor and major grooves of DNA all along the evaporation processes is shown to compact the DNA structure by electrostatic and hydrogen-bond interactions. The subsequent proton transfer from the ammonium (NH4+ or protonated amino groups) to the DNA phosphate groups allows creation of protonated phosphate/phosphate hydrogen bonds within the compact structures. MD simulations showed major structural differences between the dendriplexes in solution and in the gas phase, not only due to the loss of the solvent but also due to the proton transfers and the huge difference between the solution and gas-phase charge states.

Prediction of Collision Cross-Section Values for Extractables and Leachables from Plastic Products

The use of ion mobility separation (IMS) in conjunction with high-resolution mass spectrometry has proved to be a reliable and useful technique for the characterization of small molecules from plastic products. Collision cross-section (CCS) values derived from IMS can be used as a structural descriptor to aid compound identification. One limitation of the application of IMS to the identification of chemicals from plastics is the lack of published empirical CCS values. As such, machine learning techniques can provide an alternative approach by generating predicted CCS values. Herein, experimental CCS values for over a thousand chemicals associated with plastics were collected from the literature and used to develop an accurate CCS prediction model for extractables and leachables from plastic products. The effect of different molecular descriptors and machine learning algorithms on the model performance were assessed. A support vector machine (SVM) model, based on Chemistry Development Kit (CDK) descriptors, provided the most accurate prediction with 93.3% of CCS values for [M + H]+ adducts and 95.0% of CCS values for [M + Na]+ adducts in testing sets predicted with <5% error. Median relative errors for the CCS values of the [M + H]+ and [M + Na]+ adducts were 1.42 and 1.76%, respectively. Subsequently, CCS values for the compounds in the Chemicals associated with Plastic Packaging Database and the Food Contact Chemicals Database were predicted using the SVM model developed herein. These values were integrated in our structural elucidation workflow and applied to the identification of plastic-related chemicals in river water. False positives were reduced, and the identification confidence level was improved by the incorporation of predicted CCS values in the suspect screening workflow.

Enantiomer Differentiation of Amino Acid Stereoisomers by Structural Mass Spectrometry Using Noncovalent Trinuclear Copper Complexes.

Previous work has demonstrated that copper complexation strategies can be used with tandem MS (MS/MS) and, more recently, ion mobility-mass spectrometry (IM-MS) to differentiate chiral isomers based upon enantiomeric-specific binding. In this study, we investigate the separation of chiral amino acids (AAs) forming trinuclear complexes that can be directly resolved by IM-MS analyses. Twenty standard AAs of both d- and l-chirality were investigated. Specific AAs including d/l-histidine, d/l-proline, d/l-glutamine, d/l-tyrosine, and d/l-tryptophan were evaluated as "chiral selectors" that, when combined with copper, were found to promote selective complexation with specific AA enantiomers. Significant enantiomer differentiation was observed in the IM spectra for hydrophobic AAs acids with peak-to-peak resolutions ranging from 0.63 to 1.15. Among the chiral selectors investigated, histidine provided the best enantioselectivity, followed by tryptophan, suggesting the aromatic structure plays an important role in forming chiral-specific ion complexes. Unlike MS/MS methods where chiral selectors with l-stereochemistry enhance the differentiation, the chirality of the selector was found to have no significant effect on observed IM separation with both d- and l-selectors providing similar resolutions but with inverted IM arrival time ordering. To investigate the structural differences between resolvable chiral complexes, a combination of MS/MS, collision cross-section (CCS) measurements, and molecular mechanics techniques was used. Candidate trinuclear structures of the stoichiometry [(Cu2+)3(d/lIle)3(lHis)2 - 5H]+ were constructed with guidance from empirical MS/MS results. Of the 48 theoretical structures generated, one enantiomeric cluster pair yielded close correlation (<1%) with experimental CCS measurements, suggesting the most enantioselective ion complexes observed in this work are bridged by three coppers.

Ion Mobility-Mass Spectrometry Reveals the Structures and Stabilities of Biotherapeutic Antibody Aggregates.

Stability is a key critical quality attribute monitored throughout the development of monoclonal antibody (mAb) therapeutics. Minor changes in their higher order structure (HOS) caused by stress or environment may alter mAb aggregation, immunogenicity, and efficacy. In addition, the structures of the resulting mAb aggregates are largely unknown, as are their dependencies on conditions under which they are created. In this report, we investigate the HOS of mAb monomers and dimers under a variety of forced degradation conditions with ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) technologies. We evaluate two model IgG1 antibodies that differ significantly only in their complementarity-determinant regions: IgG1α and IgG1β. Our data covering both heat- and pH-based forced degradation conditions, aquired on two different IM-MS platforms, show that these mAbs undergo global HOS changes at both monomer and dimer levels upon degradation, but shifts in collision cross section (CCS) differ under pH or heat degradation conditions. In addition, the level of CCS change detected is different between IgG1α and IgG1β, suggesting that differences in the CDR drive differential responses to degradation that influence the antibody HOS. Dramatically different CIU fingerprints are obtained for IgG1α and IgG1β monomers and dimers for both degradation conditions. Finally, we constructed a series of computational models of mAb dimers for comparison with experimental CCS values and found evidence for a compact, overlapped dimer structure under native and heat degradation conditions, possibly adopting an inverted or nonoverlapped quaternary structure when produced through pH degredation. We conclude by discussing the potential impact of our findings on ongoing biotherapeutic discovery and development efforts.