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Native mass spectrometry (MS), ion mobility (IM), and collision-induced unfolding (CIU) have all been widely used to study the binding of small molecules to proteins and their complexes. Despite many successes in detecting subtle gas-phase stability differences in smaller systems dominated by single-domain subunits, studies targeting complexes comprised of large, multidomain subunits still face many challenges. For example, polyketide synthases (PKSs) are multiprotein enzymes that use their modular architecture to produce polyketide natural products and form the basis for nearly one-third of pharmaceuticals. Here, we describe the development of CIU methods capable of extracting information from these multiprotein complexes and demonstrate the current limits of quantitative CIU technology by probing the stabilities ∼280 kDa PKS dimer protein complexes. Our approach detects the evidence of the stability shifts associated with substrate binding that accounts for <0.1% of the mass for the intact assembly.

Ion mobility-mass spectrometry (IM-MS) has become a technology deployed across a wide range of structural biology applications despite the challenges in characterizing closely related protein structures. Collision-induced unfolding (CIU) has emerged as a valuable technique for distinguishing closely related, iso-cross-sectional protein and protein complex ions through their distinct unfolding pathways in the gas phase. With the speed and sensitivity of CIU analyses, there has been a rapid growth of CIU-based assays, especially regarding biomolecular targets that remain challenging to assess and characterize with other structural biology tools. With information-rich CIU data, many software tools have been developed to automate laborious data analysis. However, with the recent development of new IM-MS technologies, such as cyclic IM-MS, CIU continues to evolve, necessitating improved data analysis tools to keep pace with new technologies and facilitating the automation of various data processing tasks. Here, we present CIUSuite 3, a software package that contains updated algorithms that support various IM-MS platforms and supports the automation of various data analysis tasks such as peak detection, multidimensional classification, and collision cross section (CCS) calibration. CIUSuite 3 uses local maxima searches along with peak width and prominence filters to detect peaks to automate CIU data extraction. To support both the primary CIU (CIU 1 ) and secondary CIU (CIU 2 ) experiments enabled by cyclic IM-MS, two-dimensional data preprocessing is deployed, which allows multidimensional classification. Our data suggest that additional dimensions in classification improve the overall accuracy of class assignments. CIUSuite 3 also supports CCS calibration for both traveling wave and drift tube IM-MS, and we demonstrate the accuracy of a new single-field CCS calibration method designed for drift tube IM-MS leveraging calibrant CIU data. Overall, CIUSuite 3 is positioned to support current and next-generation IM-MS and CIU assay development deployed in an automated format.

Fc-fusion proteins are an emerging class of protein therapeutics that combine the properties of biological ligands with the unique properties of the fragment crystallizable (Fc) domain of an immunoglobulin G (IgG). Due to their diverse higher-order structures (HOSs), Fc-fusion proteins remain challenging characterization targets within biopharmaceutical pipelines. While high-resolution biophysical tools are available for HOS characterization, they frequently demand extended time frames and substantial quantities of purified samples, rendering them impractical for swiftly screening candidate molecules. Herein, we describe the development of ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) workflows that aim to fill this technology gap, where we focus on probing the HOS of a model Fc-Interleukin-10 (Fc-IL-10) fusion protein engineered using flexible glycine-serine linkers. We evaluate the ability of these techniques to probe the flexibility of Fc-IL-10 in the absence of bulk solvent relative to other proteins of similar size, as well as localize structural changes of low charge state Fc-IL-10 ions to specific Fc and IL-10 unfolding events during CIU. We subsequently apply these tools to probe the local effects of glycine-serine linkers on the HOS and stability of IL-10 homodimer, which is the biologically active form of IL-10. Our data reveals that Fc-IL-10 produces significantly more structural transitions during CIU and broader IM profiles when compared to a wide range of model proteins, indicative of its exceptional structural dynamism. Furthermore, we use a combination of enzymatic approaches to annotate these intricate CIU data and localize specific transitions to the unfolding of domains within Fc-IL-10. Finally, we detect a strong positive, quadratic relationship between average linker mass and fusion protein stability, suggesting a cooperative influence between glycine-serine linkers and overall fusion protein stability. This is the first reported study on the use of IM-MS and CIU to characterize HOS of Fc-fusion proteins, illustrating the practical applicability of this approach.

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.

Quantitative mass spectrometry has been widely used to evaluate the concentrations of molecules within a variety of biological matrices. Typically, such quantitative mass spectrometry analyses are predicated upon the production of mass-resolved precursor or fragment ions, leading to challenges surrounding the quantification of isomeric or conformationally distinct analytes. As such, new approaches are required for the label-free quantification of isomass proteins. Native ion-mobility MS (nIM-MS) in combination with collision induced unfolding (CIU) is a potentially enabling approach for such quantitative mass spectrometry methods as the technique can rapidly separate and detect many biomacromolecule isoforms. CIU uses collisional activation to capture the unfolding trajectory of ions in the gas phase, producing different intermediate structures that can be leveraged to distinguish protein structures that exhibit identical sizes at lower energies. Here we describe the deployment of quantitative CIU methodology to measure the concentrations of isomass pairs of biotherapeutics and sequence homologues in both standard and biological matrices. Our results cover three antibody pairs and include examples of mixed therapies where multiple biologics are commonly provided to patients. In all cases, CIU enables the production of resolved features for each antibody mixture probed, producing calibration curves with correlation coefficients ranging from 0.92 to 0.99, limits of detection ranging from 300 to 5000 nM and sensitivities ranging from 8.7 × 10 -5 nM -1 to 6 × 10 -3 μM -1 . We conclude our report by projecting the future utility of CIU-enabled quantitative MS methods.

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.

Structural analysis by native ion mobility-mass spectrometry provides a direct means to characterize protein interactions, stability, and other biophysical properties of disease-associated biomolecules. Such information is often extracted from collision-induced unfolding (CIU) experiments, performed by ramping a voltage used to accelerate ions entering a trap cell prior to an ion mobility separator. Traditionally, to simplify data analysis and achieve confident ion identification, precursor ion selection with a quadrupole is performed prior to collisional activation. Only one charge state can be selected at one time, leading to an imbalance between the total time required to survey CIU data across all protein charge states and the resulting structural analysis efficiency. Furthermore, the arbitrary selection of a single charge state can inherently bias CIU analyses. We herein aim to compare two conformation sampling methods for protein gas-phase unfolding: (1) traditional quadrupole selection-based CIU and (2) nontargeted, charge selection-free and shotgun workflow, all ion unfolding (AIU). Additionally, we provide a new data interpretation method that integrates across all charge states to project collisional cross section (CCS) data acquired over a range of activation voltages to produce a single unfolding fingerprint, regardless of charge state distributions. We find that AIU in combination with CCS accumulation across all charges offers an opportunity to maximize protein conformational information with minimal time cost, where additional benefits include (1) an improved signal-to-noise ratios for unfolding fingerprints and (2) a higher tolerance to charge state shifts induced by either operating parameters or other factors that affect protein ionization efficiency.

Ion mobility-mass spectrometry (IM-MS) and collision-induced unfolding (CIU) assays of monoclonal antibody (mAb)-based biotherapeutics have proven sensitive to disulfide bridge structures, glycosylation patterns, and small molecule conjugation levels. Despite promising prior reports detailing the capabilities of IM-MS and CIU to differentiate biosimilars, generic mAb therapeutics, there remain questions surrounding the sensitivity of CIU to mAb structure changes that occur upon stress, the reproducibility of such measurements across IM-MS platforms, and the correlation between CIU and differential scanning calorimetry (DSC) datasets. In this report, we describe a comprehensive IM-MS and CIU dataset acquired for three Infliximabs: Remicade, Inflectra, and Renflexis. We subject each infliximab sample to forced degradation through heat stress and observe broadly similar yet subtly different stability patterns for these three biotherapeutics. We find that CIU is capable of tracking differences in mAb higher-order structure (HOS) imparted during forced heat stress degradation and that DSC is less sensitive to these alterations in comparison. Furthermore, we collected our comprehensive IM-MS and CIU data across two instrument platforms (Waters G2 and Agilent 6560), with both producing similar abilities to differentiate mAbs while also revealing minor differences between the results obtained on the two instruments. Finally, we demonstrate that CIU-based heatmaps and classification allow for rapid assessment of the most differentiating charge states for the analysis of infliximab, and using multiplexed classification, we conservatively estimate a 30-fold improvement in the time required to perform mAb stability and HOS measurements over standard DSC tools.

Native ion mobility-mass spectrometry (IM-MS) is capable of revealing much that remains unknown within the structural proteome, promising such information on refractory protein targets. Here, we report the development of a unique drift tube IM-MS (DTIM-MS) platform, which combines high-energy source optics for improved collision induced unfolding (CIU) experiments and an electromagnetostatic cell for electron capture dissociation (ECD). We measured a series of high precision collision cross section (CCS) values for protein and protein complex ions ranging from 6-1600 kDa, exhibiting an average relative standard deviation (RSD) of 0.43 ± 0.20%. Furthermore, we compare our CCS results to previously reported DTIM values, finding strong agreement across similarly configured instrumentation (average RSD of 0.82 ± 0.73%), and systematic differences for DTIM CCS values commonly used to calibrate traveling-wave IM separators (-3% average RSD). Our CIU experiments reveal that the modified DTIM-MS instrument described here achieves enhanced levels of ion activation when compared with any previously reported IM-MS platforms, allowing for comprehensive unfolding of large multiprotein complex ions as well as interplatform CIU comparisons. Using our modified DTIM instrument, we studied two protein complexes. The enhanced CIU capabilities enable us to study the gas phase stability of the GroEL 7-mer and 14-mer complexes. Finally, we report CIU-ECD experiments for the alcohol dehydrogenase tetramer, demonstrating improved sequence coverage by combining ECD fragmentation integrated over multiple CIU intermediates. Further improvements for such native top-down sequencing experiments were possible by leveraging IM separation, which enabled us to separate and analyze CID and ECD fragmentation simultaneously.

Membrane proteins represent most current therapeutic targets, yet remain understudied due to their insolubility in aqueous solvents and generally low yields during purification and expression. Ion mobility-mass spectrometry and collision induced unfolding experiments have recently garnered attention as methods capable of directly detecting and quantifying ligand binding within a wide range of membrane protein systems. Despite prior success, ionized surfactant often creates chemical noise patterns resulting in significant challenges surrounding the study of small membrane protein-ligand complexes. Here, we present a new data analysis workflow that overcomes such chemical noise and then utilize this approach to quantify and classify ligand binding associated with the 36 kDa dimer of translocator protein (TSPO). Following our denoising protocol, we detect separate gas-phase unfolding signatures for lipid and protoporphyrin TSPO binders, molecular classes that likely interact with separate regions of the protein surface. Further, a detailed classification analysis reveals that lipid alkyl chain saturation levels can be detected within our gas-phase protein unfolding data. We combine these data and classification schemes with mass spectra acquired directly from liquid-liquid extracts to propose an identity for a previously unknown endogenous TSPO ligand.

The kinase-inducible domain (KIX) of the transcriptional coactivator CBP binds multiple transcriptional regulators through two allosterically connected sites. Establishing a method for observing activator-specific KIX conformations would facilitate the discovery of drug-like molecules that capture specific conformations and further elucidate how distinct activator-KIX complexes produce differential transcriptional effects. However, the transient and low to moderate affinity interactions between activators and KIX are difficult to capture using traditional biophysical assays. Here, we describe a collision-induced unfolding-based approach that produces unique fingerprints for peptides bound to each of the two available sites within KIX, as well as a third fingerprint for ternary KIX complexes. Furthermore, we evaluate the analytical utility of unfolding fingerprints for KIX complexes using CIUSuite, and conclude by speculating as to the structural origins of the conformational families created from KIX:peptide complexes following collisional activation. Graphical Abstract ᅟ.

Monoclonal antibodies (mAbs) are among the fastest growing class of therapeutics due to their high specificity and low incidence of side effects. Unlike most drugs, mAbs are complex macromolecules (∼150 kDa), leading to a host of quality control and characterization challenges inherent in their development. Recently, we introduced a new approach for the analysis of the intact proteins based on ion mobility-mass spectrometry (IM-MS). Our protocol involves the collision induced unfolding (CIU) of intact antibodies, where collisional heating in the gas-phase is used to generate unfolded antibody forms, which are subsequently separated by IM and then analyzed by MS. Collisional energy is added to the antibody ions in a stepwise fashion, and "fingerprint plots" are created that track the amount of unfolding undergone as a function of the energy imparted to the ions prior to IM separation. In this report, we have used these fingerprints to rapidly distinguish between antibody isoforms, possessing different numbers and/or patterns of disulfide bonding and general levels of glycosylation. In addition, we validate our CIU protocols through control experiments and systematic statistical evaluations of CIU reproducibility. We conclude by projecting the impact of our approach for antibody-related drug discovery and development applications.

Ion mobility-mass spectrometry (IM-MS) is a technology of growing importance for structural biology, providing complementary 3D structure information for biomolecules within samples that are difficult to analyze using conventional analytical tools through the near-simultaneous acquisition of ion collision cross sections (CCSs) and masses. Despite recent advances in IM-MS instrumentation, the resolution of closely related protein conformations remains challenging. Collision induced unfolding (CIU) has been demonstrated as a useful tool for resolving isocrossectional protein ions, as they often follow distinct unfolding pathways when subjected to collisional heating in the gas phase. CIU has been used for a variety of applications, from differentiating binding modes of activation state-selective kinase inhibitors to characterizing the domain structure of multidomain proteins. With the growing utilization of CIU as a tool for structural biology, significant challenges have emerged in data analysis and interpretation, specifically the normalization and comparison of CIU data sets. Here, we present CIUSuite, a suite of software modules designed for the rapid processing, analysis, comparison, and classification of CIU data. We demonstrate these tools as part of a series of workflows for applications in comparative structural biology, biotherapeutic analysis, and high throughput screening of kinase inhibitors. These examples illustrate both the potential for CIU in general protein analysis as well as a demonstration of best practices in the interpretation of CIU data.

Cooperative binding mechanisms are a common feature in biology, enabling a diverse range of protein-based molecular machines to regulate activities ranging from oxygen uptake to cellular membrane transport. Much, however, is not known about such cooperative binding mechanisms, including how such events typically add to the overall stability of such protein systems. Measurements of such cooperative stabilization events are challenging, as they require the separation and resolution of individual protein complex bound states within a mixture of potential stoichiometries to individually assess protein stabilities. Here, we report ion mobility-mass spectrometry results for the concanavalin A tetramer bound to a range of polysaccharide ligands. We use collision induced unfolding, a relatively new methodology that functions as a gas-phase analog of calorimetry experiments in solution, to individually assess the stabilities of concanavalin A bound states. By comparing the differences in activation voltage required to unfold different concanavalin A-ligand stoichiometries, we find evidence suggesting a cooperative stabilization of concanavalin A occurs upon binding most carbohydrate ligands. We critically evaluate this observation by assessing a broad range of ligands, evaluating the unfolding properties of multiple protein charge states, and by comparing our gas-phase results with those obtained from calorimetry experiments carried out in solution., (© 2015 The Protein Society.)

The three-dimensional structures adopted by proteins are predicated by their many biological functions. Mass spectrometry has played a rapidly expanding role in protein structure discovery, enabling the generation of models for both proteins and their higher-order assemblies. While important coursed-grained insights have been generated, relatively few examples exist where mass spectrometry has been successfully applied to the characterization of protein tertiary structure. Here, we demonstrate that gas-phase unfolding can be used to determine the number of autonomously folded domains within monomeric proteins. Our ion mobility-mass spectrometry data highlight a strong, positive correlation between the number of protein unfolding transitions observed in the gas phase and the number of known domains within a group of sixteen proteins ranging from 8-78 kDa. This correlation and its potential uses for structural biology is discussed., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)