Jean R. N. Haler

Experimental ion mobility–mass spectrometry (IM–MS) results are often correlated to three-dimensional structures based on theoretical chemistry calculations. The bottleneck of this approach is the need for accurate values, both experimentally and theoretically predicted. Here, we continue the development of the trend-based analyses to extract structural information from experimental IM–MS data sets. The experimental collision cross-sections (CCSs) of synthetic systems such as homopolymers and small ionic clusters are investigated in terms of CCS trends as a function of the number of repetitive units (e.g., degree of polymerization (DP) for homopolymers) and for each detected charge state. Then, we computed the projected areas of expanding but perfectly defined geometric objects using an in-house software called MoShade. The shapes were modeled using computer-aided design software where we considered only geometric factors: no atoms, mass, chemical potentials, or interactions were taken into consideration to make the method orthogonal to classical methods for 3D shape assessments using time-consuming computational chemistry. Our modeled shape evolutions favorably compared to experimentally obtained CCS trends, meaning that the apparent volume or envelope of homogeneously distributed mass effectively modeled the ion–drift gas interactions as sampled by IM–MS. The CCSs of convex shapes could be directly related to their surface area. More importantly, this relationship seems to hold even for moderately concave shapes, such as those obtained by geometry-optimized structures of ions from conventional computational chemistry methods. Theoretical sets of expanding beads-on-a-string shapes allowed extracting accurate bead and string dimensions for two homopolymers, without modeling any chemical interactions.

Ion mobility–mass spectrometry (IM-MS) experiments are mostly used hand in hand with computational chemistry to correlate mobility measurements to the shape of the ions. Recently, we developed an automatable method to fit IM data obtained with synthetic homopolymers (i.e., collision cross sections; CCS) without resorting to computational chemistry. Here, we further develop the experimental IM data interpretation to explore physicochemical properties of a series of nine polymers and their monomer units by monitoring the relationship between the CCS and the degree of polymerization (DP). Several remarkable points of the CCS evolutions as a function of the DP were found: the first observed DP of each charge state (ΔDP_{first DP}), the DPs constituting the structural rearrangements (ΔDP_rearr), and the DPs at the half-rearrangement (DP_half-rearr). Given that these remarkable points do not rely on absolute CCS values, but on their relative evolution, they can be extracted from CCS or raw IM data without accurate IM calibration. Properties such as coordination numbers of the cations, steric hindrance, or side chain flexibility can be compared. This leads to fit parameter predictions based on the nature of the monomer unit. The interpretation of the fit parameters, extracted using solely experimental data, allows a rapid screening of the properties of the polymers.

In the past, we developed a method inferring physicochemical properties from ion mobility-mass spectrometry (IM-MS) data from polydisperse synthetic homopolymers. We extend here the method to biomolecules that are generally monodisperse. Similarities in the IM-MS behavior were illustrated on proteins and peptides. This allows to identify ionic species for which intramolecular interactions lead to specific structures.

The two-dimensional shape information yielded by ion mobility-mass spectrometry (IM-MS), usually reported as collision cross-section (CCS), is often correlated to the underlying three-dimensional structures of the ions through computational chemistry. Here, we used theoretical approaches based on molecular mechanics (MM), molecular dynamics (MD) and density functional theory (DFT) to elucidate the structures of sodiated poly(ethoxy phosphate) polymer ions at different degrees of polymerization (DP) for three different charge states (1+, 2+ and 3+) by comparing computational results to experimentally-obtained CCS values. From the calculated structures, we extract several key interaction distances which merge in clusters for all screened charge states and DPs, independently of the three-dimensional structures and the polymer ion structural rearrangements. These distances were also used to extract the minimum coordination numbers in poly(ethoxy phosphate) and to describe the preferred coordination geometries. When comparing sodiated and protonated polymer ions, the experimental CCS evolutions differ at small DP values and merge at higher DPs. We investigated in more depth this difference for two selected species, namely [PEtP₅ + 2Na⁺]²⁺and [PEtP₅ + 2H⁺]²⁺. For the protonated ions, we explored the different protonation sites to extract three-dimensional structure candidates and rationalize the CCS behaviors.

Disulfide bonds between cysteine residues are commonly involved in the stability of numerous peptides and proteins and are crucial for providing biological activities. In such peptides, the appropriate cysteine connectivity ensures the appropriate conformation allowing an efficient binding to their molecular targets. Disulfide bond connectivity characterization is still challenging and is a critical issue in the analysis of structured peptides/proteins targeting pharmaceutical or pharmacological utilizations. This study describes the development of new and fast gas-phase and in-solution electrophoretic methods coupled to mass spectrometry to characterize the connectivity of the disulfide bond. For this purpose, disulfide isomers of three peptides bearing two intra-molecular disulfide bonds but different connections between cysteines have been investigated. Capillary Zone Electrophoresis (CZE) and Ion Mobility (IM) both coupled to Mass Spectrometry (MS) were used to perform the separation in both aqueous and gas phases, respectively. The ability of each technique to separate these isomers has been critically evaluated and compared. Finally, theoretical calculations were performed to support and explain the experimental data based on their predicted physicochemical properties.

Experimental ion mobility-mass spectrometry (IM-MS) results are often correlated to three-dimensional structures owing to theoretical chemistry calculations. The bottleneck of this approach is the need for accurate values, both experimentally and theoretically predicted. Here, we analyze experimental and theoretical collision cross-section (CCS) evolutions instead of interpreting absolute CCS values. Experimentally, the CCS trends of synthetic homopolymers are analyzed as a function of increasing degrees of polymerization (DP) for different charge states. Then, shape evolutions of modeled shape deformations yield theoretical CCS trends, calculated using new software called MoShade (projected area calculations). The shapes are modeled using computer-aided design software where we considered only geometric factors: no atoms, chemical potentials or interactions are taken into consideration to make the method orthogonal to classical methods for 3D shape assessments using time-consuming computational chemistry. We are able to correlate modeled shape evolutions to experimentally-obtained polymer CCS trends. We thus modeled the apparent volume or envelope of their ion-drift gas interactions as sampled by IM-MS. Moreover, the CCS of convex shapes could be directly related to their surface area. The relation seems to hold even for concave shapes which could be correlated to geometry-optimized structures of ions obtained by conventional computational chemistry methods. Modeling beads-on-a-string shape evolutions allows extracting precise dimension relations between two homopolymers, without modeling any chemical interactions.

Lipid screening of biological substrates is an important step during biomarker detection and identification. In this work, a fast workflow is described capable of rapid screening for lipid components from biological tissues at ambient pressure based on liquid microjunction extraction in tandem with nano-electrospray ionization (nESI) with ultra-high resolution mass spectrometry, i.e., liquid extraction surface analysis (LESA) coupled to Fourier-transform ion cyclotron resonance (tandem) mass spectrometry (LESA-FT-ICR-MS/MS). Lipid profiles are presented for thin tissue sections of mouse brain (MB) and liver (ML) samples, analyzed in both positive and negative mode by data-dependent acquisition (DDA) tandem FT-ICR-MS/MS. Candidate assignments were based on fragmentation patterns using mostly SimLipid software and accurate mass using mostly the LipidMaps database (average sub-ppm mass error). A typical, single point surface analysis (m/z values. Despite the biological complexity, this led to unique identifications of distinct lipid molecules (sub-ppm mass error) from 38 different lipid classes, corresponding to 10–30% of the lipid m/z identifications.

When polymer mixtures become increasingly complex, the conventional analysis techniques become insufficient for complete characterization. Mass spectrometric techniques can satisfy this increasing demand for detailed sample characterization. Even though isobaric polymers are indistinguishable using simple mass spectrometry (MS) analyses, more advanced techniques such as tandem MS (MS/MS) or ion mobility (IM) can be used. Here, we report proof of concept for characterizing isomeric polymers, namely poly(2-n-propyl-2-oxazoline) (Pn-PrOx) and poly(2-isopropyl-2-oxazoline) (Pi-PrOx), using MS/MS and IM-MS. Pi-PrOx ions lose in intensity at higher accelerating voltages than Pn-PrOx ions during collision-induced dissociation (CID) MS/MS experiments. A Pn/i-PrOx mixture could also be titrated using survival yield calculations of either precursor ions or cation ejection species. IM-MS yielded shape differences in the degree of polymerization (DP) regions showing the structural rearrangements. Combined MS techniques are thus able to identify and deconvolute the molar mass distributions of the two isomers in a mixture. Finally, the MS/MS and IM-MS behaviors are compared for interpretation.

Polymer characterizations are often performed using mass spectrometry (MS). Aside from MS and different tandem MS (MS/MS) techniques, ion mobility–mass spectrometry (IM-MS) has been recently added to the inventory of characterization technique. However, only few studies have focused on the reproducibility and robustness of polymer IM-MS analyses. Here, we perform collisional and electron-mediated activation of polymer ions before measuring IM drift times, collision cross-sections (CCS), or reduced ion mobilities (K₀). The resulting IM behavior of different activated product ions is then compared to non-activated native intact polymer ions. First, we analyzed collision induced unfolding (CIU) of precursor ions to test the robustness of polymer ion shapes. Then, we focused on fragmentation product ions to test for shape retentions from the precursor ions: cation ejection species (CES) and product ions with m/z and charge state values identical to native intact polymer ions. The CES species are formed using both collision induced dissociation (CID) and electron transfer dissociation (ETD, formally ETnoD) experiments. Only small drift time, CCS, or K₀ deviations between the activated/formed ions are observed compared to the native intact polymer ions. The polymer ion shapes seem to depend solely on their mass and charge state. The experiments were performed on three synthetic homopolymers: poly(ethoxy phosphate) (PEtP), poly(2-n-propyl-2-oxazoline) (Pn-PrOx), and poly(ethylene oxide) (PEO). These results confirm the robustness of polymer ion CCSs for IM calibration, especially singly charged polymer ions. The results are also discussed in the context of polymer analyses, CCS predictions, and probing ion–drift gas interaction potentials.

Ion mobility spectrometry (IMS) is a gas‐phase separation technique based on ion mobility differences in an electric field. It is largely used for the detection of specific ions such as small molecule explosives. IMS detection system includes the use of e. g. a Faraday cupor mass spectrometry (MS). The presence of interfering ion signals in standalone IMS may lead to the detection of false positives or negatives due to e. g. lacking resolving power. In this case, selective mobility shifts obtained using shift reagents (SR), i. e. ligands complexing a specific target, can bring help. The effectiveness of an SR strategy relies on the SR‐target ion selectivity. The crucial step lies in the SR design. The aim of this paper is to present an efficient interplay of experimental ion mobility mass spectrometry (IMMS) and predictive computational chemistry using various levels of computational efforts for rationally designing target‐specific SR. Mass spectrometry is used to evaluate the efficiency of the SR selectivity with identification and semi‐quantification of free and complexed ions. Minimal computational efforts allow the design of the SR, predicting the SR‐target ion relative stabilities, and predicting the ion mobility shifts. We demonstrate our approach using crown ethers and β‐cyclodextrin to selectively shift interfering perchlorate, amino acids and diaminonaphthalene isomers. We also release the software ParsIMoS for the straightforward use of ion mobility calculator IMoS.