Can IM-MS Collision Cross Sections of Biomolecules Be Rationalized Using Collision Cross-Section Trends of Polydisperse Synthetic Homopolymers?

Intramolecular Ring-Chain Equilibrium Elimination Strategy for Pinpointing C═C Positional and Geometric Isomers of N-Alkylpyridinium Unsaturated Fatty Acid Derivatives via Ion Mobility-Mass Spectrometry

Free unsaturated fatty acids (UFA) are key intermediates of lipid metabolism and participate in many metabolic pathways with specific biological functions. Although various fragmentation-based methods for pinpointing C═C locations in UFA were developed, the current mass spectrometry methods are difficult to simultaneously differentiate geometric isomers and positional isomers in trace samples due to low ionization efficiency, low conversion, and low resolution. Herein, an intramolecular ring-chain equilibrium elimination strategy via 4-plex stable isotope labeling dual derivatization-assisted ion mobility-mass spectrometry was developed, thereby one-pot specifically labeling C═C and carboxyl groups among the trace and unstable UFA with high sensitivity, high efficiency, and good substrate generality. It achieved fast separation of both C═C positional and geometric isomers with high resolution, which benefited from eliminating the intramolecular ring-chain equilibrium by suppressing the formation of salt bridges between free carboxyl groups and pyridine cations. 4-plex stable isotope labeling reagents showed similar reactivity, enabling high-throughput quantitative analysis of omics. This method was successfully applied for accurate and rapid identification of the UFA composition in olive oil extract. These results suggest that the developed method provides new insight for rapid characterization of UFA C═C positional and geometric isomers in complex samples to explore disease biomarkers and food quality control indicators.

Gas-phase structure of polymer ions: Tying together theoretical approaches and ion mobility spectrometry

An increasing number of studies take advantage of ion mobility spectrometry (IMS) coupled to mass spectrometry (IMS-MS) to investigate the spatial structure of gaseous ions. Synthetic polymers occupy a unique place in the field of IMS-MS. Indeed, due to their intrinsic dispersity, they offer a broad range of homologous ions with different lengths. To help rationalize experimental data, various theoretical approaches have been described. First, the study of trend lines is proposed to derive physicochemical and structural parameters. However, the evaluation of data fitting reflects the overall behavior of the ions without reflecting specific information on their conformation. Atomistic simulations constitute another approach that provide accurate information about the ion shape. The overall scope of this review is dedicated to the synergy between IMS-MS and theoretical approaches, including computational chemistry, demonstrating the essential role they play to fully understand/interpret IMS-MS data.

Geometric Analysis of Shapes in Ion Mobility-Mass Spectrometry

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.

Powerful Steroid-Based Chiral Selector for High-Throughput Enantiomeric Separation of α-Amino Acids Utilizing Ion Mobility-Mass Spectrometry

Stereospecific recognition of amino acids (AAs) plays a crucial role in chiral biomarker-based diagnosis and prognosis. Separation of AA enantiomers is a long and tedious task due to the requirement of AA derivatization prior to the chromatographic or electrophoretic steps which are also time-consuming. Here, a mass-tagged chiral selector named [d₀]/[d₅]-estradiol-3-benzoate-17β-chloroformate ([d₀]/[d₅]-17β-EBC) with high reactivity and good enantiomeric resolution in regard to AAs was developed. After a quick and easy chemical derivatization step of AAs using 17β-EBC as the single chiral selector before ion mobility-mass spectrometry analysis, good enantiomer separation was achieved for 19 chiral proteinogenic AAs in a single analytical run (∼2 s). A linear calibration curve of enantiomeric excess was also established using [d₀]/[d₅]-17β-EBC. It was demonstrated to be capable of determining enantiomeric ratios down to 0.5% in the nanomolar range. 17β-EBC was successfully applied to investigate the absolute configuration of AAs among peptide drugs and detect trace levels of d-AAs in complex biological samples. These results indicated that [d₀]/[d₅]-17β-EBC may contribute to entail a valuable step forward in peptide drug quality control and discovering chiral disease biomarkers.

Using Ion Mobility-Mass Spectrometry to Extract Physicochemical Enthalpic and Entropic Contributions from Synthetic Polymers

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.

Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches

In structural biology, collision cross sections (CCSs) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.