CoSIMS: An Optimized Trajectory-Based Collision Simulator for Ion Mobility Spectrometry

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.

MassCCS: A High-Performance Collision Cross-Section Software for Large Macromolecular Assemblies

Ion mobility mass spectrometry (IM-MS) techniques have become highly valued as a tool for structural characterization of biomolecular systems since they yield accurate measurements of the rotationally averaged collision cross-section (CCS) against a buffer gas. Despite its enormous potential, IM-MS data interpretation is often challenging due to the conformational isomerism of metabolites, lipids, proteins, and other biomolecules in the gas phase. Therefore, reliable and fast CCS calculations are needed to help interpret IM-MS data. In this work, we present MassCCS, a parallelized open-source code for computing CCS of molecules ranging from small organic compounds to massive protein assemblies at the trajectory method level of description using atomic and molecular buffer gas particles. The performance of the code is comparable to other available software for small molecules and proteins but is significantly faster for larger macromolecular assemblies. We performed extensive tests regarding accuracy, performance, and scalability with system size and number of CPU cores. MassCCS has proven highly accurate and efficient, with execution times under a few minutes, even for large (84.87 MDa) virus capsid assemblies with very modest computational resources. MassCCS is freely available at https://github.com/cces-cepid/massccs.

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.

Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section

The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field of structural biology over the past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, and all three of these can be used to discern structural information. While mass and charge are determined in mass spectrometry (MS), it is the addition of ion mobility that enables the separation of isomeric and isobaric ions and the direct elucidation of conformation, which has reaped huge benefits for structural biology. In this review, where we focus on the analysis of proteins and their complexes, we outline the typical features of an IM-MS experiment from the preparation of samples, the creation of ions, and their separation in different mobility and mass spectrometers. We describe the interpretation of ion mobility data in terms of protein conformation and how the data can be compared with data from other sources with the use of computational tools. The benefit of coupling mobility analysis to activation via collisions with gas or surfaces or photons photoactivation is detailed with reference to recent examples. And finally, we focus on insights afforded by IM-MS experiments when applied to the study of conformationally dynamic and intrinsically disordered proteins.

Molecular Dynamics-Assisted Interpretation of Experimentally Determined Intrinsically Disordered Protein Conformational Components: The Case of Human α-Synuclein

Mass spectrometry and single molecule force microscopy are two experimental approaches able to provide structural information on intrinsically disordered proteins (IDPs). These techniques allow the dissection of conformational ensembles in their main components, although at a low-resolution level. In this work, we interpret the results emerging from these experimental approaches on human alpha synuclein (AS) by analyzing a previously published 73 μs-long molecular-dynamics (MD) simulation of the protein in explicit solvent. We further compare MD-based predictions of single molecule Förster resonance energy transfer (smFRET) data of AS in solution with experimental data. The combined theoretical and experimental data provide a description of AS main conformational ensemble, shedding light into its intramolecular interactions and overall structural compactness. This analysis could be easily transferred to other IDPs.

Cyclosporin A: Conformational Complexity and Chameleonicity

The chameleonic behavior of cyclosporin A (CsA) was investigated through conformational ensembles employing multicanonical molecular dynamics simulations that could sample the cis and trans isomers of N-methylated amino acids; these assessments were conducted in explicit water, dimethyl sulfoxide, acetonitrile, methanol, chloroform, cyclohexane (CHX), and n-hexane (HEX) using AMBER ff03, AMBER10:EHT, AMBER12:EHT, and AMBER14:EHT force fields. The conformational details were discussed employing the free-energy landscapes (FELs) at T = 300 K; it was observed that the experimentally determined structures of CsA were only a part of the conformational space. Comparing the ROESY measurements in CHX-d12 and HEX-d14, the major conformations in those apolar solvents were essentially the same as that in CDCl₃ except for the observation of some sidechain rotamers. The effects of the metal ions on the conformations, including the cis/trans isomerization, were also investigated. Based on the analysis of FELs, it was concluded that the AMBER ff03 force field best described the experimentally derived conformations, indicating that CsA intrinsically formed membrane-permeable conformations and that the metal ions might be the key to the cis/trans isomerization of N-methylated amino acids before binding a partner protein.

Predicting ion mobility as a function of the electric field for small ions in light gases

High resolution mobility devices such as Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) and Differential Mobility spectrometers (DMS) use strong electric fields to gas concentration ratios, E/N, to separate ions in the gas phase. While extremely successful, their empirical results show a non-linear, ion-dependent relation between mobility K and E/N that is difficult to characterize. The one-temperature theory Mason-Schamp equation, which is the most widely used ion mobility equation, unfortunately, cannot capture this behavior. When the two-temperature theory is used, it can be shown that the K-E/N behavior can be followed quite closely numerically by equating the effect of increasing the field to an increase in the ion temperature. This is attempted here for small ions in a Helium gas environment showing good agreement over the whole field range. To improve the numerical characterization, the Lennard-Jones (L-J) potentials may be optimized. This is attempted for Carbon, Hydrogen, Oxygen and Nitrogen at different degrees of theory up to the fourth approximation, which is assumed to be exact. The optimization of L-J improves the accuracy yielding errors of about 3% on average. The fact that a constant set of L-J potentials work for the whole range of E/N and for several molecules, also suggests that inelastic collisions can be circumvented in calculations for He. The peculiar K-E/N hump behaviors are studied, and whether mobility increases or decreases with E/N is shown to derive from a competition between relative kinetic energy and the interaction potentials.