Collision Cross Sections for Structural Proteomics

Evaluation of Membrane Mimetics for the Native Ion Mobility─Mass Spectrometry Analysis of Membrane Proteins

Membrane protein (MP) structures and functions are intricately linked to their surrounding membrane environments and their respective lipid compositions in addition to influences exerted by unique membrane microdomains (i.e., lipid rafts). Owing to the complexity of their native environments, MPs pose significant challenges to structural biology due to their intrinsic hydrophobic nature rendering them incompatible with aqueous conditions commonly deployed during sample preparation. To overcome these solubility issues, MP studies commonly utilize detergent micelles. In recent years, numerous efforts have been directed toward developing membrane mimetics to facilitate successful solubilization and stabilization of MPs. Collision-induced dissociation (CID) can be employed to remove surrounding molecules from MPs during native mass spectrometry (nMS) experiments, and such methods can be used to evaluate previously inaccessible MPs. However, the differential effects of various membrane mimetics on MP structure and stability remain largely unexplored. In this study, we evaluate a range of MPs, including both transmembrane and monotopic variants, solubilized in detergent micelles, mixed lipid bicelles, and nanodisc mimetics. Our findings reveal significant differences in collision induced unfolding (CIU) features, stabilities, collision cross sections (CCS), and RMSD comparisons with values exceeding 26%. These results underscore the importance of considering the choice of membrane mimetics when studying MP structure.

X-ray spectroscopy meets native mass spectrometry: probing gas-phase protein complexes

Gas-phase activation and dissociation studies of biomolecules, proteins and their non-covalent complexes using X-rays hold great promise for revealing new insights into the structure and function of biological samples. This is due to the unique properties of X-ray molecular interactions, such as site-specific and rapid ionization. In this perspective, we report and discuss the promise of first proof-of-principle studies of X-ray-induced dissociation of native (structurally preserved) biological samples ranging from small 17 kDa monomeric proteins up to large 808 kDa non-covalent protein assemblies conducted at a synchrotron (PETRA III) and a free-electron laser (FLASH2). A commercially available quadrupole time-of-flight mass spectrometer (Q-Tof Ultima US, Micromass/Waters), modified for high-mass analysis by MS Vision, was further adapted for integration with the open ports at the corresponding beamlines. The protein complexes were transferred natively into the gas phase via nano-electrospray ionization and subsequently probed by extreme ultraviolet (FLASH2) or soft X-ray (PETRA III) radiation, in either their folded state or following collision-induced activation in the gas phase. Depending on the size of the biomolecule and the activation method, protein fragmentation, dissociation, or enhanced ionization were observed. Additionally, an extension of the setup by ion mobility is described, which can serve as a powerful tool for structural separation of biomolecules prior to X-ray probing. The first experimental results are discussed in the broader context of current and upcoming X-ray sources, highlighting their potential for advancing structural biology in the future.

Charging of DNA Complexes in Positive-Mode Native Electrospray Ionization Mass Spectrometry

Native mass spectrometry (nMS) provides insights into the structures and dynamics of biomacromolecules in their native-like states by preserving noncovalent interactions through "soft" electrospray ionization (ESI). For native proteins, the number of charges that are acquired scales with the surface area and mass. Here, we explore the effect of highly negatively charged DNA on the ESI charge of protein complexes and find a reduction of the mass-to-charge ratio as well as a greater variation. The charge state distributions of pure DNA assemblies show a lower mass-to-charge ratio than proteins due to their greater density in the gas phase, whereas the charge of protein-DNA complexes can additionally be influenced by the distribution of the ESI charges, ion pairing events, and collapse of the DNA components. Our findings suggest that structural features of protein-DNA complexes can result in lower charge states than expected for proteins.

A Conformation-Specific Approach to Native Top-down Mass Spectrometry

Native top-down mass spectrometry is a powerful approach for characterizing proteoforms and has recently been applied to provide similarly powerful insights into protein conformation. Current approaches, however, are limited such that structural insights can only be obtained for the entire conformational landscape in bulk or without any direct conformational measurement. We report a new ion-mobility-enabled method for performing native top-down MS in a conformation-specific manner. Our approach identified conformation-linked differences in backbone dissociation for the model protein calmodulin, which simultaneously informs upon proteoform variations and provides structural insights. We also illustrate that our method can be applied to protein-ligand complexes, either to identify components or to probe ligand-induced structural changes.

Dimerization of the Aβ42 under the Influence of the Gold Nanoparticle: A REMD Study

Advances in Alzheimer's disease (AD) are related to the oligomerization of Amyloid β (Aβ) peptides. Therefore, alteration of the process can prevent AD. We investigated the Aβ42 dimerization under the effects of gold nanoparticles using temperature replica-exchange molecular dynamics (REMD) simulations. The structural change of dimers in the presence and absence of the gold nanoparticle, Au55, was monitored over stable intervals. Physical insights into the oligomerization of Aβ were thus clarified. The computed metrics indicate that Au55 affects the progress of oligomerization. Specifically, the presence of the gold nanoparticle significantly modifies the structure of dimeric Aβ42. The β-content experienced a substantial decrease with the induction of Au55. The turn and coil-contents are also decreased under the effects of the gold nanoparticle. However, the α-content of the dimer exhibited a rigid increase. The influence of gold nanoparticles on the dimeric Aβ42 differs significantly from that of silver nanoparticles, which reduce β-content but increase coil-, turn-, and α-contents. The nature of inhibition will be discussed, in which the vdW interaction plays a driving force for the interaction between the Aβ42 dimer and the gold nanoparticle.

Elucidating Protein Structures in the Gas Phase: Traversing Configuration Space with Biasing Methods

Achieving accurate characterization of protein structures in the gas phase continues to be a formidable challenge. To tackle this issue, the present study employs Molecular Dynamics (MD) simulations in tandem with enhanced sampling techniques (methods designed to efficiently explore protein conformations). The objective is to identify suitable structures of proteins by contrasting their calculated Collision Cross-Section (CCS) with those observed experimentally. Significant discrepancies were observed between the initial MD-simulated and experimentally measured CCS values through Ion Mobility-Mass Spectrometry (IMS-MS). To bridge this gap, we employed two distinct enhanced sampling methods, Harmonic Biasing Potential and Adaptive Biasing Force, which help the proteins overcome energy barriers to adopt more compact configurations. These techniques leverage the radius of gyration as a reaction coordinate (guiding parameter), guiding the system toward compressed states that potentially match experimental configurations more closely. The guiding forces are only employed to overcome existing barriers and are removed to allow the protein to naturally arrive at a potential gas phase configuration. The results demonstrated close alignment (within ∼4%) between simulated and experimental CCS values despite using different strengths and/or methods, validating their efficacy. This work lays the groundwork for future studies aimed at optimizing biasing methods and expanding the collective variables used for more accurate gas-phase structural predictions.

High-Performance Molecular Dynamics Simulations for Native Mass Spectrometry of Large Protein Complexes with the Fast Multipole Method

Native mass spectrometry (MS) is widely employed to study the structures and assemblies of proteins ranging from small monomers to megadalton complexes. Molecular dynamics (MD) simulation is a useful complement as it provides the spatial detail that native MS cannot offer. However, MD simulations performed in the gas phase have suffered from rapidly increasing computational costs with the system size. The primary bottleneck is the calculation of electrostatic forces, which are effective over long distances and must be explicitly computed for each atom pair, precluding efficient use of methods traditionally used to accelerate condensed-phase simulations. As a result, MD simulations have been unable to match the capacity of MS in probing large multimeric protein complexes. Here, we apply the fast multipole method (FMM) for computing the electrostatic forces, recently implemented by Kohnke et al. (J. Chem. Theory Comput., 2020, 16, 6938-6949), showing that it significantly enhances the performance of gas-phase simulations of large proteins. We assess how to achieve adequate accuracy and optimal performance with FMM, finding that it expands the accessible size range and time scales dramatically. Additionally, we simulate a 460 kDa ferritin complex over microsecond time scales, alongside complementary ion mobility (IM)-MS experiments, uncovering conformational changes that are not apparent from the IM-MS data alone.

Time-Resolved Ion Mobility-Mass Spectrometry Reveals Structural Transitions in the Disassembly of Modular Polyketide Syntheses

The type 1 polyketide synthase (PKS) assembly line uses its modular structure to produce polyketide natural products that form the basis of many pharmaceuticals. Currently, several cryoelectron microscopy (cryo-EM) structures of a multidomain PKS module have been constructed, but much remains to be learned. Here we utilize ion-mobility mass spectrometry (IM-MS) to record size and shape information and detect different conformational states of a 207 kDa didomain dimer comprised of ketosynthase (KS) and acyl transferase (AT), excised from full-length module. Furthermore, gas-phase stability differences between these different conformations are captured by collision induced unfolding (CIU) technology. Additionally, through tracking these forms as a function of time, we elucidate a detailed disassembly pathway for KS-AT dimers for the first time.

Understanding the structural dynamics of human islet amyloid polypeptide: Advancements in and applications of ion-mobility mass spectrometry

Human islet amyloid polypeptide (hIAPP) forms amyloid deposits that contribute to β-cell death in pancreatic islets and are considered a hallmark of Type II diabetes Mellitus (T2DM). Evidence suggests that the early oligomers of hIAPP formed during the aggregation process are the primary pathological agent in islet amyloid induced β-cell death. The self-assembly mechanism of hIAPP, however, remains elusive, largely due to limitations in conventional biophysical techniques for probing the distribution or capturing detailed structures of the early, structurally dynamic oligomers. The advent of Ion-mobility Mass Spectrometry (IM-MS) has enabled the characterisation of hIAPP early oligomers in the gas phase, paving the way towards a deeper understanding of the oligomerisation mechanism and the correlation of structural information with the cytotoxicity of the oligomers. The sensitivity and the rapid structural characterisation provided by IM-MS also show promise in screening hIAPP inhibitors, categorising their modes of inhibition through "spectral fingerprints". This review delves into the application of IM-MS to the dissection of the complex steps of hIAPP oligomerisation, examining the inhibitory influence of metal ions, and exploring the characterisation of hetero-oligomerisation with different hIAPP variants. We highlight the potential of IM-MS as a tool for the high-throughput screening of hIAPP inhibitors, and for providing insights into their modes of action. Finally, we discuss advances afforded by recent advancements in tandem IM-MS and the combination of gas phase spectroscopy with IM-MS, which promise to deliver a more sensitive and higher-resolution structural portrait of hIAPP oligomers. Such information may help facilitate a new era of targeted therapeutic strategies for islet amyloidosis in T2DM.

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

Silver nanoparticles alter the dimerization of Aβ42 studied by REMD simulations

The aggregation of amyloid beta (Aβ) peptides is associated with the development of Alzheimer's disease (AD). However, there has been a growing belief that the oligomerization of Aβ species in different environments has a neurotoxic effect on the patient's brain, causing damage. It is necessary to comprehend the compositions of Aβ oligomers in order to develop medications that may effectively inhibit these neurotoxic forms that affect the nervous system of AD patients. Thus, dissociation or inhibition of Aβ aggregation may be able to prevent AD. To date, the search for traditional agents and biomolecules has largely been unsuccessful. In this context, nanoparticles have emerged as potential candidates to directly inhibit the formation of Aβ oligomers. The oligomerization of the dimeric Aβ peptides with or without the influence of a silver nanoparticle was thus investigated using temperature replica-exchange molecular dynamics (REMD) simulations. The physical insights into the dimeric Aβ oligomerization were clarified by analyzing intermolecular contact maps, the free energy landscape of the dimeric oligomer, secondary structure terms, etc. The difference in obtained metrics between Aβ with or without a silver nanoparticle provides a picture of the influence of silver nanoparticles on the oligomerization process. The underlying mechanisms that are involved in altering Aβ oligomerization will be discussed. The obtained results may play an important role in searching for Aβ inhibitor pathways.

Structural studies of supramolecular complexes and assemblies by ion mobility mass spectrometry

Recent advances in instrumentation and development of computational strategies for ion mobility mass spectrometry (IM-MS) studies have contributed to an extensive growth in the application of this analytical technique to comprehensive structural description of supramolecular systems. Apart from the benefits of IM-MS for interrogation of intrinsic properties of noncovalent aggregates in the experimental gas-phase environment, its merits for the description of native structural aspects, under the premises of having maintained the noncovalent interactions innate upon the ionization process, have attracted even more attention and gained increasing interest in the scientific community. Thus, various types of supramolecular complexes and assemblies relevant for biological, medical, material, and environmental sciences have been characterized so far by IM-MS supported by computational chemistry. This review covers the state-of-the-art in this field and discusses experimental methods and accompanying computational approaches for assessing the reliable three-dimensional structural elucidation of supramolecular complexes and assemblies by IM-MS.

Collision induced unfolding and molecular dynamics simulations of norovirus capsid dimers reveal strain-specific stability profiles

Collision induced unfolding (CIU) is a method used with ion mobility mass spectrometry to examine protein structures and their stability. Such experiments yield information about higher order protein structures, yet are unable to provide details about the underlying processes. That information can however be provided using molecular dynamics simulations. Here, we investigate the gas-phase unfolding of norovirus capsid dimers from the Norwalk and Kawasaki strains by employing molecular dynamics simulations over a range of temperatures, representing different levels of activation, together with CIU experiments. The dimers have highly similar structures, but their CIU reveals different stability that can be explained by the different dynamics that arises in response to the activation seen in the simulations, including a part of the sequence with previously observed strain-specific dynamics in solution. Our findings show how similar protein variants can be examined using mass spectrometric techniques in conjunction with atomistic molecular dynamics simulations to reveal differences in stability as well as differences in how and where unfolding takes place upon activation.

Ion Mobility Mass Spectrometry for Large Synthetic Molecules: Expanding the Analytical Toolbox

Understanding the composition, structure and stability of larger synthetic molecules is crucial for their design, yet currently the analytical tools commonly used do not always provide this information. In this perspective, we show how ion mobility mass spectrometry (IM-MS), in combination with tandem mass spectrometry, complementary techniques and computational methods, can be used to structurally characterize synthetic molecules, make and predict new complexes, monitor disassembly processes and determine stability. Using IM-MS, we present an experimental and computational framework for the analysis and design of complex molecular architectures such as (metallo)supramolecular cages, nanoclusters, interlocked molecules, rotaxanes, dendrimers, polymers and host-guest complexes.

The catalytic domain of free or ligand bound histone deacetylase 4 occurs in solution predominantly in closed conformation

Human histone deacetylase 4 (HDAC4) is a key epigenetic regulator involved in a number of important cellular processes. This makes HDAC4 a promising target for the treatment of several cancers and neurodegenerative diseases, in particular Huntington's disease. HDAC4 is highly regulated by phosphorylation and oxidation, which determine its nuclear or cytosolic localization, and exerts its function through multiple interactions with other proteins, forming multiprotein complexes of varying composition. The catalytic domain of HDAC4 is known to interact with the SMRT/NCOR corepressor complex when the structural zinc-binding domain (sZBD) is intact and forms a closed conformation. Crystal structures of the HDAC4 catalytic domain have been reported showing an open conformation of HDAC4 when bound to certain ligands. Here, we investigated the relevance of this HDAC4 conformation under physiological conditions in solution. We show that proper zinc chelation in the sZBD is essential for enzyme function. Loss of the structural zinc ion not only leads to a massive decrease in enzyme activity, but it also has serious consequences for the overall structural integrity and stability of the protein. However, the Zn2+ free HDAC4 structure in solution is incompatible with the open conformation. In solution, the open conformation of HDAC4 was also not observed in the presence of a variety of structurally divergent ligands. This suggests that the open conformation of HDAC4 cannot be induced in solution, and therefore cannot be exploited for the development of HDAC4-specific inhibitors.

A druggable conformational switch in the c-MYC transactivation domain

The c-MYC oncogene is activated in over 70% of all human cancers. The intrinsic disorder of the c-MYC transcription factor facilitates molecular interactions that regulate numerous biological pathways, but severely limits efforts to target its function for cancer therapy. Here, we use a reductionist strategy to characterize the dynamic and structural heterogeneity of the c-MYC protein. Using probe-based Molecular Dynamics (MD) simulations and machine learning, we identify a conformational switch in the c-MYC amino-terminal transactivation domain (termed coreMYC) that cycles between a closed, inactive, and an open, active conformation. Using the polyphenol epigallocatechin gallate (EGCG) to modulate the conformational landscape of coreMYC, we show through biophysical and cellular assays that the induction of a closed conformation impedes its interactions with the transformation/transcription domain-associated protein (TRRAP) and the TATA-box binding protein (TBP) which are essential for the transcriptional and oncogenic activities of c-MYC. Together, these findings provide insights into structure-activity relationships of c-MYC, which open avenues towards the development of shape-shifting compounds to target c-MYC as well as other disordered transcription factors for cancer treatment.

Structure and dynamics of endogenous cardiac troponin complex in human heart tissue captured by native nanoproteomics

Protein complexes are highly dynamic entities that display substantial diversity in their assembly, post-translational modifications, and non-covalent interactions, allowing them to play critical roles in various biological processes. The heterogeneity, dynamic nature, and low abundance of protein complexes in their native states present challenges to study using conventional structural biology techniques. Here we develop a native nanoproteomics strategy for the enrichment and subsequent native top-down mass spectrometry (nTDMS) analysis of endogenous cardiac troponin (cTn) complex directly from human heart tissue. The cTn complex is enriched and purified using peptide-functionalized superparamagnetic nanoparticles under non-denaturing conditions to enable the isotopic resolution of cTn complex, revealing their complex structure and assembly. Moreover, nTDMS elucidates the stoichiometry and composition of the cTn complex, localizes Ca2+ binding domains, defines cTn-Ca2+ binding dynamics, and provides high-resolution mapping of the proteoform landscape. This native nanoproteomics strategy opens a paradigm for structural characterization of endogenous native protein complexes.

Advances in mass spectrometry to unravel the structure and function of protein condensates

Membrane-less organelles assemble through liquid-liquid phase separation (LLPS) of partially disordered proteins into highly specialized microenvironments. Currently, it is challenging to obtain a clear understanding of the relationship between the structure and function of phase-separated protein assemblies, owing to their size, dynamics and heterogeneity. In this Perspective, we discuss recent advances in mass spectrometry (MS) that offer several promising approaches for the study of protein LLPS. We survey MS tools that have provided valuable insights into other insoluble protein systems, such as amyloids, and describe how they can also be applied to study proteins that undergo LLPS. On the basis of these recent advances, we propose to integrate MS into the experimental workflow for LLPS studies. We identify specific challenges and future opportunities for the analysis of protein condensate structure and function by MS.

Variation of CI-2 Conformers upon Addition of Methanol to Water: An IMS-MS-Based Thermodynamic Analysis

Chymotrypsin inhibitor 2 (CI-2) is a well-studied, textbook example of a cooperative, two-state, native ↔ denatured folding transition. A recent hybrid ion mobility spectrometry (IMS)/mass spectrometry (MS) thermal denaturation study of CI-2 (the well-studied truncated 64-residue model) in water reported evidence that this two-state transition involves numerous (∼41) unique native and non-native (denatured) solution conformations. The characterization of so many, often low-abundance, states is possible because of the very high dynamic range of IMS-MS measurements of ionic species that are produced upon electrospraying CI-2 solutions from a variable temperature electrospray ionization source. A thermodynamic analysis of these states revealed large changes in enthalpy (ΔH) and entropy (ΔS) at different temperatures, and it was suggested that such variation might arise because of temperature-dependent conformational changes of the protein in response to changes in the conformational entropy and the dielectric permeability of water, which drops from a value of ε ∼ 79 at 24 °C to ∼ 60 at 82 °C. Herein, we examine how adding methanol to water influences the distributions of CI-2 conformers and their ensuing stabilities. The dielectric constant of a 60:40 water:methanol (MeOH) drops from ε ∼ 60 at 24 °C to ∼ 51 at 64 °C. Although the same set of conformers observed in water appears to be present in 60:40 water:MeOH, the abundance of each is substantially altered by the presence of methanol. Relative free energy values (ΔG) and thermodynamic values [ΔH and ΔS and heat capacities (ΔCp)] are derived from a Gibbs-Helmholtz analysis. A comparison of these data from water and water:MeOH systems allows rare insight into how variations in solvation and temperature affect many-state protein equilibria. While these studies confirm that variations in solvent dielectric constant with temperature affect the distributions of conformers that are observed, our findings suggest that other solvent differences may also affect abundances.

Development of an Automated, High-Throughput Methodology for Native Mass Spectrometry and Collision-Induced Unfolding

Native ion mobility mass spectrometry (nIM-MS) has emerged as a useful technology for the rapid evaluation of biomolecular structures. When combined with collisional activation in a collision-induced unfolding (CIU) experiment, nIM-MS experimentation can be leveraged to gain greater insight into biomolecular conformation and stability. However, nIM-MS and CIU remain throughput limited due to nonautomated sample preparation and introduction. Here, we explore the use of a RapidFire robotic sample handling system to develop an automated, high-throughput methodology for nMS and CIU. We describe native RapidFire-MS (nRapidFire-MS) capable of performing online desalting and sample introduction in as little as 10 s per sample. When combined with CIU, our nRapidFire-MS approach can be used to collect CIU fingerprints in 30 s following desalting by using size exclusion chromatography cartridges. When compared to nMS and CIU data collected using standard approaches, ion signals recorded by nRapidFire-MS exhibit identical ion collision cross sections, indicating that the same conformational populations are tracked by the two approaches. Our data further suggest that nRapidFire-MS can be extended to study a variety of biomolecular classes, including proteins and protein complexes ranging from 5 to 300 kDa and oligonucleotides. Furthermore, nRapidFire-MS data acquired for biotherapeutics suggest that nRapidFire-MS has the potential to enable high-throughput nMS analyses of biopharmaceutical samples. We conclude by discussing the potential of nRapidFire-MS for enabling the development of future CIU assays capable of catalyzing breakthroughs in protein engineering, inhibitor discovery, and formulation development for biotherapeutics.

Oxidized and Reduced Dimeric Protein Complexes Illustrate Contrasting CID and SID Charge Partitioning

Charge partitioning during the dissociation of protein complexes in the gas phase is influenced by many factors, such as interfacial interactions, protein flexibility, protein conformation, and dissociation methods. In the present work, two cysteine-containing homodimer proteins, β-lactoglobulin and α-lactalbumin, with the disulfide bonds intact and reduced, were used to gain insight into the charge partitioning behaviors of collision-induced dissociation (CID) and surface-induced dissociation (SID) processes. For these proteins, we find that restructuring dominates with CID and dissociation with symmetric charge partitioning dominates with SID, regardless of whether intramolecular disulfide bonds are oxidized or reduced. CID of the charge-reduced dimeric protein complex leads to a precursor with a slightly smaller collision cross section (CCS), greater stability, and more symmetrically distributed charges than the significantly expanded form produced by CID of the higher charged dimer. Collision-induced unfolding plots demonstrate that the unfolding-restructuring of the protein complexes initiates the charge migration of higher charge-state precursors. Overall, gas collisions reveal the charge-dependent restructuring/unfolding properties of the protein precursor, while surface collisions lead predominantly to more charge-symmetric monomer separation. CID's multiple low-energy collisions sequentially reorganize intra- and intermolecular bonds, while SID's large-step energy jump cleaves intermolecular interfacial bonds in preference to reorganizing intramolecular bonds. The activated population of precursors that have taken on energy without dissociating (populated in CID over a wide range of collision energies, populated in SID for only a narrow distribution of collision energies near the onset of dissociation) is expected to be restructured, regardless of the activation method.

Predicting ion mobility collision cross sections using projection approximation with ROSIE-PARCS webserver

Ion mobility coupled to mass spectrometry informs on the shape and size of protein structures in the form of a collision cross section (CCSIM). Although there are several computational methods for predicting CCSIM based on protein structures, including our previously developed projection approximation using rough circular shapes (PARCS), the process usually requires prior experience with the command-line interface. To overcome this challenge, here we present a web application on the Rosetta Online Server that Includes Everyone (ROSIE) webserver to predict CCSIM from protein structure using projection approximation with PARCS. In this web interface, the user is only required to provide one or more PDB files as input. Results from our case studies suggest that CCSIM predictions (with ROSIE-PARCS) are highly accurate with an average error of 6.12%. Furthermore, the absolute difference between CCSIM and CCSPARCS can help in distinguishing accurate from inaccurate AlphaFold2 protein structure predictions. ROSIE-PARCS is designed with a user-friendly interface, is available publicly and is free to use. The ROSIE-PARCS web interface is supported by all major web browsers and can be accessed via this link (https://rosie.graylab.jhu.edu).

Studying Membrane Protein-Lipid Specificity through Direct Native Mass Spectrometric Analysis from Tunable Proteoliposomes

Native mass spectrometry (nMS) has emerged as a key analytical tool to study the organizational states of proteins and their complexes with both endogenous and exogenous ligands. Specifically, for membrane proteins, it provides a key analytical dimension to determine the identity of bound lipids and to decipher their effects on the observed structural assembly. We recently developed an approach to study membrane proteins directly from intact and tunable lipid membranes where both the biophysical properties of the membrane and its lipid compositions can be customized. Extending this, we use our liposome-nMS platform to decipher the lipid specificity of membrane proteins through their multiorganelle trafficking pathways. To demonstrate this, we used VAMP2 and reconstituted it in the endoplasmic reticulum (ER), Golgi, synaptic vesicle (SV), and plasma membrane (PM) mimicking liposomes. By directly studying VAMP2 from these customized liposomes, we show how the same transmembrane protein can bind to different sets of lipids in different organellar-mimicking membranes. Considering that the cellular trafficking pathway of most eukaryotic integral membrane proteins involves residence in multiple organellar membranes, this study highlights how the lipid-specificity of the same integral membrane protein may change depending on the membrane context. Further, leveraging the capability of the platform to study membrane proteins from liposomes with curated biophysical properties, we show how we can disentangle chemical versus biophysical properties, of individual lipids in regulating membrane protein assembly.

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.

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.

Structure and dynamics of endogenous protein complexes in human heart tissue captured by native nanoproteomics

Protein complexes are highly dynamic entities that display substantial diversity in their assembly, post-translational modifications, and non-covalent interactions, allowing them to play critical roles in various biological processes. The heterogeneity, dynamic nature, and low abundance of protein complexes in their native states present tremendous challenges to study using conventional structural biology techniques. Here we develop a "native nanoproteomics" strategy for the native enrichment and subsequent native top-down mass spectrometry (nTDMS) of low-abundance protein complexes. Specifically, we demonstrate the first comprehensive characterization of the structure and dynamics of cardiac troponin (cTn) complexes directly from human heart tissue. The endogenous cTn complex is effectively enriched and purified using peptide-functionalized superparamagnetic nanoparticles under non-denaturing conditions to enable the isotopic resolution of cTn complexes, revealing their complex structure and assembly. Moreover, nTDMS elucidates the stoichiometry and composition of the heterotrimeric cTn complex, localizes Ca2+ binding domains (II-IV), defines cTn-Ca2+ binding dynamics, and provides high-resolution mapping of the proteoform landscape. This native nanoproteomics strategy opens a new paradigm for structural characterization of low-abundance native protein complexes.

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.

Determining the gas-phase structures of α-helical peptides from shape, microsolvation, and intramolecular distance data

Mass spectrometry is a powerful technique for the structural and functional characterization of biomolecules. However, it remains challenging to accurately gauge the gas-phase structure of biomolecular ions and assess to what extent native-like structures are maintained. Here we propose a synergistic approach which utilizes Förster resonance energy transfer and two types of ion mobility spectrometry (i.e., traveling wave and differential) to provide multiple constraints (i.e., shape and intramolecular distance) for structure-refinement of gas-phase ions. We add microsolvation calculations to assess the interaction sites and energies between the biomolecular ions and gaseous additives. This combined strategy is employed to distinguish conformers and understand the gas-phase structures of two isomeric α-helical peptides that might differ in helicity. Our work allows more stringent structural characterization of biologically relevant molecules (e.g., peptide drugs) and large biomolecular ions than using only a single structural methodology in the gas phase.

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.

The Structure of Cyclic Neuropeptide Somatostatin and Octapeptide Octreotide in the Presence of Copper Ions: Insights from Transition Metal Ion FRET and Native Ion Mobility-Mass Spectrometry

The conformation and function of somatostatin (SST), a cyclic neuropeptide, was recently found to be altered in the presence of Cu(II) ions, which leads to self-aggregation and loss of biological function as a neurotransmitter. However, the impact of Cu(II) ions on the structure and function of SST is not fully understood. In this work, transition metal ion Förster resonance energy transfer (tmFRET) and native ion mobility-mass spectrometry (IM-MS) were utilized to study the structures of well-defined gas-phase ions of SST and of a smaller analogue, octreotide (OCT). The tmFRET results suggest two binding sites of Cu(II) ions in both native-like SST and OCT ions, either in close proximity to the disulfide bond or complexed by two aromatic residues, consistent with results obtained from collision-induced dissociation (CID). The former binding site was reported to initiate aggregation of SST, while the latter binding site could directly affect the essential motif for receptor binding and therefore impair the biological function of SST and OCT when bound to SST receptors. Our results demonstrate that tmFRET is capable of locating transition metal ion binding sites in neuropeptides. Furthermore, multiple distance constraints (tmFRET) and global shape (IM-MS) provide additional structural insights of SST and OCT ions upon metal binding, which is related to the self-aggregation mechanisms and overall biological functions.

Ion mobility mass spectrometry and molecular dynamics simulations unravel the conformational stability of zinc metallothionein-2 species

Ion mobility-mass spectrometry (IM-MS) unraveled different conformational stability in Zn4-7-metallothionein-2. We introduced a new molecular dynamics simulation approach that permitted the exploration of all of the conformational space confirming the experimental data, and revealed that not only the Zn-S bonds but also the α-β domain interactions modulate protein unfolding.

Rehydration Post-orientation: Investigating Field-Induced Structural Changes via Computational Rehydration

Proteins can be oriented in the gas phase using strong electric fields, which brings advantages for structure determination using X-ray free electron lasers. Both the vacuum conditions and the electric-field exposure risk damaging the protein structures. Here, we employ molecular dynamics simulations to rehydrate and relax vacuum and electric-field exposed proteins in aqueous solution, which simulates a refinement of structure models derived from oriented gas-phase proteins. We find that the impact of the strong electric fields on the protein structures is of minor importance after rehydration, compared to that of vacuum exposure and ionization in electrospraying. The structures did not fully relax back to their native structure in solution on the simulated timescales of 200 ns, but they recover several features, including native-like intra-protein contacts, which suggests that the structures remain in a state from which the fully native structure is accessible. Our findings imply that the electric fields used in native mass spectrometry are well below a destructive level, and suggest that structures inferred from X-ray diffraction from gas-phase proteins are relevant for solution and in vivo conditions, at least after in silico rehydration.

Structural mass spectrometry approaches to understand multidrug efflux systems

Multidrug efflux pumps are ubiquitous across both eukaryotes and prokaryotes, and have major implications in antimicrobial and multidrug resistance. They reside within cellular membranes and have proven difficult to study owing to their hydrophobic character and relationship with their compositionally complex lipid environment. Advances in structural mass spectrometry (MS) techniques have made it possible to study these systems to elucidate critical information on their structure-function relationships. For example, MS techniques can report on protein structural dynamics, stoichiometry, connectivity, solvent accessibility, and binding interactions with ligands, lipids, and other proteins. This information proving powerful when used in conjunction with complementary structural biology methods and molecular dynamics (MD) simulations. In the present review, aimed at those not experts in MS techniques, we report on the current uses of MS in studying multidrug efflux systems, practical considerations to consider, and the future direction of the field. In the first section, we highlight the importance of studying multidrug efflux proteins, and introduce a range of different MS techniques and explain what information they yield. In the second section, we review recent studies that have utilised MS techniques to study and characterise a range of different multidrug efflux systems.

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.

Toward an Integrated Machine Learning Model of a Proteomics Experiment

In recent years machine learning has made extensive progress in modeling many aspects of mass spectrometry data. We brought together proteomics data generators, repository managers, and machine learning experts in a workshop with the goals to evaluate and explore machine learning applications for realistic modeling of data from multidimensional mass spectrometry-based proteomics analysis of any sample or organism. Following this sample-to-data roadmap helped identify knowledge gaps and define needs. Being able to generate bespoke and realistic synthetic data has legitimate and important uses in system suitability, method development, and algorithm benchmarking, while also posing critical ethical questions. The interdisciplinary nature of the workshop informed discussions of what is currently possible and future opportunities and challenges. In the following perspective we summarize these discussions in the hope of conveying our excitement about the potential of machine learning in proteomics and to inspire future research.

Landing Proteins on Graphene Trampoline Preserves Their Gas-Phase Folding on the Surface

Molecule-surface collisions are known to initiate dynamics that lead to products inaccessible by thermal chemistry. These collision dynamics, however, have mostly been examined on bulk surfaces, leaving vast opportunities unexplored for molecular collisions on nanostructures, especially on those that exhibit mechanical properties radically different from those of their bulk counterparts. Probing energy-dependent dynamics on nanostructures, particularly for large molecules, has been challenging due to their fast time scales and high structural complexity. Here, by examining the dynamics of a protein impinging on a freestanding, single-atom-thick membrane, we discover molecule-on-trampoline dynamics that disperse the collision impact away from the incident protein within a few picoseconds. As a result, our experiments and ab initio calculations show that cytochrome c retains its gas-phase folded structure when it collides onto freestanding single-layer graphene at low energies (∼20 meV/atom). The molecule-on-trampoline dynamics, expected to be operative on many freestanding atomic membranes, enable reliable means to transfer gas-phase macromolecular structures onto freestanding surfaces for their single-molecule imaging, complementing many bioanalytical techniques.

Efficient protein conformation dynamics characterization enabled by mobility-mass spectrometry

Protein structure dynamics in solution and from solution to gas phase are important but challenging topics. Great efforts and advances have been made especially since the wide application of ion mobility mass spectrometry (IM-MS), by which protein collision cross section (CCS) in gas phase could be measured. Due to the lack of efficient experimental methods, protein structures in protein databank are typically referred as their structures in solution. Although conventional structural biology techniques provide high-resolution protein structures, complicated and stringent processes also limit their applicability under different solvent conditions, thus preventing the capture of protein dynamics in solution. Enabled by the combination of mobility capillary electrophoresis (MCE) and IM-MS, an efficient experimental protocol was developed to characterize protein conformation dynamics in solution and from solution to gas phase. As a first attempt, key factors that affecting protein conformations were distinguished and evaluated separately, including pH, temperature, softness of ionization process, presence and specific location of disulfide bonds. Although similar extent of unfolding could be observed for different proteins, in-depth analysis reveals that pH decrease from 7.0 to 3.0 dominates the unfolding of proteins without disulfide bonds in conventional ESI-MS experiments; while harshness of the ionization process dominates the unfolding of proteins with disulfide bonds. Second, disulfide bonds show capability of preserving protein conformations in acidic solution environments. However, by monitoring protein conformation dynamics and comparing results from different proteins, it is also found that their capability is position dependent. Surprisingly, disulfide bonds did not show the capability of preserving protein conformations during ionization processes.

Performance evaluation of in-source ion activation hardware for collision-induced unfolding of proteins and protein complexes on a drift tube ion mobility-mass spectrometer

Native ion mobility-mass spectrometry (IM-MS) has emerged as an information-rich technique for gas phase protein structure characterization; however, IM resolution is currently insufficient for the detection of subtle structural differences in large biomolecules. This challenge has spurred the development of collision-induced unfolding (CIU) which utilizes incremental gas phase activation to unfold a protein in order to expand the number of measurable descriptors available for native protein ions. Although CIU is now routinely used in native mass spectrometry studies, the interlaboratory reproducibility of CIU has not been established. Here we evaluate the reproducibility of the CIU data produced across three laboratories (University of Michigan, Texas A&M University, and Vanderbilt University). CIU data were collected for a variety of protein ions ranging from 8.6-66 kDa. Within the same laboratory, the CIU fingerprints were found to be repeatable with root mean square deviation (RMSD) values of less than 5%. Collision cross section (CCS) values of the CIU intermediates were consistent across the laboratories, with most features exhibiting an interlaboratory reproducibility of better than 1%. In contrast, the activation potentials required to induce protein CIU transitions varied between the three laboratories. To address these differences, three source assemblies were constructed with an updated ion activation hardware design utilizing higher mechanical tolerance specifications. The production-grade assemblies were found to produce highly consistent CIU data for intact antibodies, exhibiting high precision ion CCS and CIU transition values, thus opening the door to establishing databases of CIU fingerprints to support future biomolecular classification efforts.

Gas-Phase Unfolding of Protein Complexes Distinguishes Conformational Isomers

Proteins can adopt different conformational states that are important for their biological function and, in some cases, can be responsible for their dysfunction. The essential roles that proteins play in biological systems make distinguishing the structural differences between these conformational states both fundamentally and practically important. Here, we demonstrate that collision-induced unfolding (CIU), in combination with ion mobility-mass spectrometry (IM-MS) measurements, distinguish subtly different conformational states for protein complexes. Using the open and closed states of the β-lactoglobulin (βLG) dimer as a model, we show that these two conformational isomers unfold during collisional activation to generate distinct states that are readily separated by IM-MS. Extensive molecular modeling of the CIU process reproduces the distinct unfolding intermediates and identifies the molecular details that explain why the two conformational states unfold in distinct ways. Strikingly, the open conformational state forms new electrostatic interactions upon collisional heating, while the closed state does not. These newly formed electrostatic interactions involve residues on the loop differentially positioned in the two βLG conformational isomers, highlighting that gas-phase unfolding pathways reflect aspects of solution structure. This combination of experiment and theory provides a path forward for distinguishing subtly different conformational isomers for protein complexes via gas-phase unfolding experiments. Our results also have implications for understanding how protein complexes dissociate in the gas phase, indicating that current models need to be refined to explain protein complex dissociation.

Mechanistic Insights into IscU Conformation Regulation for Fe-S Cluster Biogenesis Revealed by Variable Temperature Electrospray Ionization Native Ion Mobility Mass Spectrometry

Iron-sulfur (Fe-S) cluster (ISC) cofactors are required for the function of many critical cellular processes. In the ISC Fe-S cluster biosynthetic pathway, IscU assembles Fe-S cluster intermediates from iron, electrons, and inorganic sulfur, which is provided by the cysteine desulfurase enzyme IscS. IscU also binds to Zn, which mimics and competes for binding with the Fe-S cluster. Crystallographic and nuclear magnetic resonance spectroscopic studies reveal that IscU is a metamorphic protein that exists in multiple conformational states, which include at least a structured form and a disordered form. The structured form of IscU is favored by metal binding and is stable in a narrow temperature range, undergoing both cold and hot denaturation. Interestingly, the form of IscU that binds IscS and functions in Fe-S cluster assembly remains controversial. Here, results from variable temperature electrospray ionization (vT-ESI) native ion mobility mass spectrometry (nIM-MS) establish that IscU exists in structured, intermediate, and disordered forms that rearrange to more extended conformations at higher temperatures. A comparison of Zn-IscU and apo-IscU reveals that Zn(II) binding attenuates the cold/heat denaturation of IscU, promotes refolding of IscU, favors the structured and intermediate conformations, and inhibits the disordered high charge states. Overall, these findings provide a structural rationalization for the role of Zn(II) in stabilizing IscU conformations and IscS in altering the IscU active site to prepare for Zn(II) release and cluster synthesis. This work highlights how vT-ESI-nIM-MS can be applied as a powerful tool in mechanistic enzymology by providing details of relationships among temperature, protein conformations, and ligand/protein binding.

Linking Gas-Phase and Solution-Phase Protein Unfolding via Mobile Proton Simulations

Native mass spectrometry coupled to ion mobility (IM-MS) combined with collisional activation (CA) of ions in the gas phase (in vacuo) is an important method for the study of protein unfolding. It has advantages over classical biophysical and structural techniques as it can be used to analyze small volumes of low-concentration heterogeneous mixtures while maintaining solution-like behavior and does not require labeling with fluorescent or other probes. It is unclear, however, whether the unfolding observed during collision activation experiments mirrors solution-phase unfolding. To bridge the gap between in vacuo and in-solution behavior, we use unbiased molecular dynamics (MD) to create in silico models of in vacuo unfolding of a well-studied protein, the N-terminal domain of ribosomal L9 (NTL9) protein. We utilize a mobile proton algorithm (MPA) to create 100 thermally unfolded and coulombically unfolded in silico models for observed charge states of NTL9. The unfolding behavior in silico replicates the behavior in-solution and is in line with the in vacuo observations; however, the theoretical collision cross section (CCS) of the in silico models was lower compared to that of the in vacuo data, which may reflect reduced sampling.

Stability and conformational memory of electrosprayed and rehydrated bacteriophage MS2 virus coat proteins

Proteins are innately dynamic, which is important for their functions, but which also poses significant challenges when studying their structures. Gas-phase techniques can utilise separation and a range of sample manipulations to transcend some of the limitations of conventional techniques for structural biology in crystalline or solution phase, and isolate different states for separate interrogation. However, the transfer from solution to the gas phase risks affecting the structures, and it is unclear to what extent different conformations remain distinct in the gas phase, and if resolution in silico can recover the native conformations and their differences. Here, we use extensive molecular dynamics simulations to study the two distinct conformations of dimeric capsid protein of the MS2 bacteriophage. The protein undergoes notable restructuring of its peripheral parts in the gas phase, but subsequent simulation in solvent largely recovers the native structure. Our results suggest that despite some structural loss due to the experimental conditions, gas-phase structural biology techniques provide meaningful data that inform not only about the structures but also conformational dynamics of proteins.

Mass Spectrometry and Machine Learning Reveal Determinants of Client Recognition by Antiamyloid Chaperones

The assembly of proteins and peptides into amyloid fibrils is causally linked to serious disorders such as Alzheimer's disease. Multiple proteins have been shown to prevent amyloid formation in vitro and in vivo, ranging from highly specific chaperone-client pairs to completely nonspecific binding of aggregation-prone peptides. The underlying interactions remain elusive. Here, we turn to the machine learning-based structure prediction algorithm AlphaFold2 to obtain models for the nonspecific interactions of β-lactoglobulin, transthyretin, or thioredoxin 80 with the model amyloid peptide amyloid β and the highly specific complex between the BRICHOS chaperone domain of C-terminal region of lung surfactant protein C and its polyvaline target. Using a combination of native mass spectrometry (MS) and ion mobility MS, we show that nonspecific chaperoning is driven predominantly by hydrophobic interactions of amyloid β with hydrophobic surfaces in β-lactoglobulin, transthyretin, and thioredoxin 80, and in part regulated by oligomer stability. For C-terminal region of lung surfactant protein C, native MS and hydrogen-deuterium exchange MS reveal that a disordered region recognizes the polyvaline target by forming a complementary β-strand. Hence, we show that AlphaFold2 and MS can yield atomistic models of hard-to-capture protein interactions that reveal different chaperoning mechanisms based on separate ligand properties and may provide possible clues for specific therapeutic intervention.

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.

Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction

Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCSIM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCSIM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.

Exploring Gas-Phase MS Methodologies for Structural Elucidation of Branched N-Glycan Isomers

Structural isomers of N-glycans that are identical in mass and atomic composition provide a great challenge to conventional mass spectrometry (MS). This study employs additional dimensions of structural elucidation including ion mobility (IM) spectroscopy coupled to hydrogen/deuterium exchange (HDX) and electron capture dissociation (ECD) to characterize three main A2 N-glycans and their conformers. A series of IM-MS experiments were able to separate the low abundance N-glycans and their linkage-based isomers (α1-3 and α1-6 for A2G1). HDX-IM-MS data indicated the presence of multiple gas-phase structures for each N-glycan including the isomers of A2G1. Identification of A2G1 isomers by their collision cross section was complicated due to the preferential collapse of sugars in the gas phase, but it was possible by further ECD fragmentation. The cyclic IM-ECD approach was capable of assigning and identifying each isomer to its IM peak. Two unique cross-ring fragments were identified for each isomer: m/z = 624.21 for α1-6 and m/z = 462.16 for α1-3. Based on these key fragments, the first IM peak, indicating a more compact conformation, was assigned to α1-3 and the second IM peak, a more extended conformer, was assigned to α1-6.

Separation and Collision Cross Section Measurements of Protein Complexes Afforded by a Modular Drift Tube Coupled to an Orbitrap Mass Spectrometer

New developments in analytical technologies and biophysical methods have advanced the characterization of increasingly complex biomolecular assemblies using native mass spectrometry (MS). Ion mobility methods, in particular, have enabled a new dimension of structural information and analysis of proteins, allowing separation of conformations and providing size and shape insights based on collision cross sections (CCSs). Based on the concepts of absorption-mode Fourier transform (aFT) multiplexing ion mobility spectrometry (IMS), here, a modular drift tube design proves capable of separating native-like proteins up to 148 kDa with resolution up to 45. Coupled with high-resolution Orbitrap MS, binding of small ligands and cofactors can be resolved in the mass domain and correlated to changes in structural heterogeneity observed in the ion-neutral CCS distributions. We also demonstrate the ability to rapidly determine accurate CCSs for proteins with 1-min aFT-IMS-MS sweeps without the need for calibrants or correction factors.

Sizing up DNA nanostructure assembly with native mass spectrometry and ion mobility

Recent interest in biological and synthetic DNA nanostructures has highlighted the need for methods to comprehensively characterize intermediates and end products of multimeric DNA assembly. Here we use native mass spectrometry in combination with ion mobility to determine the mass, charge state and collision cross section of noncovalent DNA assemblies, and thereby elucidate their structural composition, oligomeric state, overall size and shape. We showcase the approach with a prototypical six-subunit DNA nanostructure to reveal how its assembly is governed by the ionic strength of the buffer, as well as how the mass and mobility of heterogeneous species can be well resolved by careful tuning of instrumental parameters. We find that the assembly of the hexameric, barrel-shaped complex is guided by positive cooperativity, while previously undetected higher-order 12- and 18-mer assemblies are assigned to defined larger-diameter geometric structures. Guided by our insight, ion mobility-mass spectrometry is poised to make significant contributions to understanding the formation and structural diversity of natural and synthetic oligonucleotide assemblies relevant in science and technology.

Recent developments in data acquisition, treatment and analysis with ion mobility-mass spectrometry for lipidomics

Lipids are involved in many biological processes and their study is constantly increasing. To identify a lipid among thousand requires of reliable methods and techniques. Ion Mobility (IM) can be coupled with Mass Spectrometry (MS) to increase analytical selectivity in lipid analysis of lipids. IM-MS has experienced an enormous development in several aspects, including instrumentation, sensitivity, amount of information collected and lipid identification capabilities. This review summarizes the latest developments in IM-MS analyses for lipidomics and focusses on the current acquisition modes in IM-MS, the approaches for the pre-treatment of the acquired data and the subsequent data analysis. Methods and tools for the calculation of Collision Cross Section (CCS) values of analytes are also reviewed. CCS values are commonly studied to support the identification of lipids, providing a quasi-orthogonal property that increases the confidence level in the annotation of compounds and can be matched in CCS databases. The information contained in this review might be of help to new users of IM-MS to decide the adequate instrumentation and software to perform IM-MS experiments for lipid analyses, but also for other experienced researchers that can reconsider their routines and protocols. This article is protected by copyright. All rights reserved.

Combination of IM-Based Approaches to Unravel the Coexistence of Two Conformers on a Therapeutic Multispecific mAb

Multispecific antibodies, which target multiple antigens at once, are emerging as promising therapeutic entities to offer more effective treatment than conventional monoclonal antibodies (mAbs). However, these highly complex mAb formats pose significant analytical challenges. We report here on the characterization of a trispecific antibody (tsAb), which presents two isomeric forms clearly separated and identified with size exclusion chromatography coupled to native mass spectrometry (SEC-nMS). Previous studies showed that these isomers might originate from a proline cis/trans isomerization in one Fab subunit of the tsAb. We combined several innovative ion mobility (IM)-based approaches to confirm the isomeric nature of the two species and to gain new insights into the conformational landscape of both isomers. Preliminary SEC-nIM-MS measurements performed on a low IM resolution instrument provided the first hints of the coexistence of different conformers, while complementary collision-induced unfolding (CIU) experiments evidenced distinct gas-phase unfolding behaviors upon activation for the two isomers. As subtle conformational differences remained poorly resolved on our early generation IM platform, we performed high-resolution cyclic IM (cIM-MS) to unambiguously conclude on the coexistence of two conformers. The cis/trans equilibrium was further tackled by exploiting the IMⁿ slicing capabilities of the cIM-MS instrument. Altogether, our results clearly illustrate the benefits of combining state-of-the-art nMS and IM-MS approaches to address challenging issues encountered in biopharma. As engineered antibody constructs become increasingly sophisticated, CIU and cIM-MS methodologies undoubtedly have the potential to integrate the drug development analytical toolbox to achieve in-depth conformational characterization of these products.