Fast photochemical oxidation of proteins (FPOP): A powerful mass spectrometry-based structural proteomics tool

In-Cell Fast Photochemical Oxidation Interrogates the Native Structure of Integral Membrane Proteins

Integral membrane proteins (IMPs) are pivotal for cellular functions but challenging to investigate. Here, IC-FPOMP (in-cell fast photochemical oxidation of MPs) is introduced, a method enabling in situ footprinting of IMPs within live cells. IC-FPOMP generates reactive oxygen radicals from various precursors (TiO2 nanoparticles or H2O2) near the membrane. Leveraging a laser and a 96-well plate platform, high-throughput and rapid footprinting of IMPs are achieved. IC-FPOMP of two human IMPs (human glucose transporter-hGLUT1 and human gamma-glutamyl carboxylase-hGGCX) are successful, providing footprinting of both the transmembrane and extramembrane regions. Comparative analysis of hGLUT1 in liposomes versus cells shows that the membrane may impact the transporter's conformation differently. In-cell drug screening targeting hGLUT1 reveals drug-binding behavior in vivo. In summary, IC-FPOMP offers insights into IMP structure-function relationships in cells and facilitates drug discovery.

PERCEPTRON-XFMS: An Open-Source Web Server for Analysis of X-ray Footprinting with Mass Spectrometry Data

PERCEPTRON-XFMS is a freely available web-based platform for automated X-ray Footprinting with Mass Spectrometry (XFMS) analysis. XFMS provides residue-specific information on protein solvent accessibility by determining hydroxyl radical modification towards investigating protein interactions and conformational changes. The approach can enable global identification of structural waters associated with surface and internal residues in a protein. Towards an integrative analysis of XFMS data, PERCEPTRON-XFMS (i) extracts and quantifies oxidation rates, (ii) computes dose-response curves, and (iii) calculates protection factors for modified residues. The webserver takes five input files: (i) LC-MS data (mzXML), (ii) Mascot search results, (iii) protein sequence (fasta), (iv) structure (PDB), and (v) solvent accessible surface area (SASA) values. The platform outputs (i) dose-response plots, (ii) protection factors, and (iii) centrality values of modified residues. For a convenient visualization of these results, the webserver also provides PDB files with protection factors, and centrality scores as an output. This is the first integrative platform that seamlessly brings together experimental and computational measures of water dynamics; thus, providing a much-needed bioinformatics tool for both fundamental and applied protein science. PERCEPTRON-XFMS webserver is freely available at https://perceptronxfms.lums.edu.pk along with its source code, at https://data.mendeley.com/datasets/ssjxhyrtwc.

Allostery

Allostery describes the ability of biological macromolecules to transmit signals spatially through the molecule from an allosteric site – a site that is distinct from orthosteric binding sites of primary, endogenous ligands – to the functional or active site. This review starts with a historical overview and a description of the classical example of allostery – hemoglobin – and other well-known examples (aspartate transcarbamoylase, Lac repressor, kinases, G-protein-coupled receptors, adenosine triphosphate synthase, and chaperonin). We then discuss fringe examples of allostery, including intrinsically disordered proteins and inter-enzyme allostery, and the influence of dynamics, entropy, and conformational ensembles and landscapes on allosteric mechanisms, to capture the essence of the field. Thereafter, we give an overview over central methods for investigating molecular mechanisms, covering experimental techniques as well as simulations and artificial intelligence (AI)-based methods. We conclude with a review of allostery-based drug discovery, with its challenges and opportunities: with the recent advent of AI-based methods, allosteric compounds are set to revolutionize drug discovery and medical treatments.

Enrichable Protein Footprinting for Structural Proteomics

Protein footprinting is a useful method for studying protein higher order structure and conformational changes induced by interactions with various ligands via addition of covalent modifications onto the protein. Compared to other methods that provide single amino acid-level structural resolution, such as cryo-EM, X-ray diffraction, and NMR, mass spectrometry (MS)-based methods can be advantageous as they require lower protein amounts and purity. As with other MS-based proteomic methods, such as post-translational modification analysis, enrichment techniques have proven necessary for both optimal sensitivity and sequence coverage when analyzing highly complex proteomes. Currently used reagents for footprinting via covalent labeling, such as hydroxyl radicals and carbodiimide-based methods, do not yet have a suitable enrichment method, limiting their applicability to whole proteome analysis. Here, we report a method for enrichable covalent labeling built upon the GEE/EDC system commonly used to covalently label aspartic acid and glutamic acid residues. Novel labeling reagents containing alkynyl functionality can be "clicked" to any azido-containing molecule with copper-catalyzed azide-alkyne cycloaddition (CuAAC), allowing for enrichment or further labeling. Multiple azide- and alkyne-containing GEE-like molecules were tested, and the most efficient method was determined to be the EDC-facilitated coupling of glycine propargyl amide (GPA) to proteins. The pipeline we report includes clicking via CuAAC to a commercially available biotin-azide containing a photocleavable linker, followed by enrichment using a streptavidin resin and subsequent cleavage under ultraviolet light. The enrichment process was optimized through the screening of clickable amines, coupling reagents, and enrichment scaffolds and methods with pure model proteins and has also been applied to complex mixtures of proteins isolated from the model plant, Arabidopsis thaliana, suggesting that our method may ultimately be used to measure protein conformation on a proteomic scale.

Using long columns to quantify over 9200 unique protein groups from brain tissue in a single injection on an Orbitrap Exploris 480 mass spectrometer

The most exciting advancement in LC-MS/MS-based bottom-up proteomics has centered around enhancing mass spectrometers. Among these, the latest and most advanced mass spectrometer for bottom-up proteomics is the Orbitrap Astral that has the highest scan rate to accelerate throughput and the highest sensitivity to handle a very small amount of peptide samples and to achieve deeper proteomics. However, its affordability remains a challenge for most laboratories. While significant strides have been made in improving mass spectrometry, advancing liquid chromatography (LC) to achieve deeper proteomics has not achieved significant successes since the innovation of Multidimensional Protein Identification Technology (MudPIT) in 2001. To achieve deeper proteomics in a less labor-intensive and more reproducible approach while using a more cost-effective mass spectrometer, such as the Orbitrap Exploris 480, we evaluated trap columns as long as 40 cm and analytical column as long as 600 cm besides sample loading amount, gradient time, and analytical column particle size to enable a fractionation-free method for a single injection to obtain deeper proteomics. The length of trap and analytic columns is the key factor. Using a 30 cm trap column and 250 cm analytical column with other optimized LC conditions, we quantified over 9200 unique protein groups from brain tissue in a single injection using a 24-h gradient on an Orbitrap Exploris 480 mass spectrometer.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

Mapping conformational changes on bispecific antigen-binding biotherapeutic by covalent labeling and mass spectrometry

Biotherapeutic's higher order structure (HOS) is a critical determinant of its functional properties and conformational relevance. Here, we evaluated two covalent labeling methods: diethylpyrocarbonate (DEPC)-labeling and fast photooxidation of proteins (FPOP), in conjunction with mass spectrometry (MS), to investigate structural modifications for the new class of immuno-oncological therapy known as bispecific antigen-binding biotherapeutics (BABB). The evaluated techniques unveiled subtle structural changes occurring at the amino acid residue level within the antigen-binding domain under both native and thermal stress conditions, which cannot be detected by conventional biophysical techniques, e.g., near-ultraviolet circular dichroism (NUV-CD). The determined variations in labeling uptake under native and stress conditions, corroborated by binding assays, shed light on the binding effect, and highlighted the potential of covalent-labeling methods to effectively monitor conformational changes that ultimately influence the product quality. Our study provides a foundation for implementing the developed techniques in elucidating the inherent structural characteristics of novel therapeutics and their conformational stability.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

Using mass spectrometry-based methods to understand amyloid formation and inhibition of alpha-synuclein and amyloid beta

Amyloid fibrils, insoluble β-sheets structures that arise from protein misfolding, are associated with several neurodegenerative disorders. Many small molecules have been investigated to prevent amyloid fibrils from forming; however, there are currently no therapeutics to combat these diseases. Mass spectrometry (MS) is proving to be effective for studying the high order structure (HOS) of aggregating proteins and for determining structural changes accompanying protein-inhibitor interactions. When combined with native MS (nMS), gas-phase ion mobility, protein footprinting, and chemical cross-linking, MS can afford regional and sometimes amino acid spatial resolution of the aggregating protein. The spatial resolution is greater than typical low-resolution spectroscopic, calorimetric, and the traditional ThT fluorescence methods used in amyloid research today. High-resolution approaches can struggle when investigating protein aggregation, as the proteins exist as complex oligomeric mixtures of many sizes and several conformations or polymorphs. Thus, MS is positioned to complement both high- and low-resolution approaches to studying amyloid fibril formation and protein-inhibitor interactions. This review covers basics in MS paired with ion mobility, continuous hydrogen-deuterium exchange (continuous HDX), pulsed hydrogen-deuterium exchange (pulsed HDX), fast photochemical oxidation of proteins (FPOP) and other irreversible labeling methods, and chemical cross-linking. We then review the applications of these approaches to studying amyloid-prone proteins with a focus on amyloid beta and alpha-synuclein. Another focus is the determination of protein-inhibitor interactions. The expectation is that MS will bring new insights to amyloid formation and thereby play an important role to prevent their formation.

Evaluating Chemical Footprinting-Induced Perturbation of Protein Higher Order Structure

Specific amino acid footprinting mass spectrometry (MS) is an increasingly utilized method for elucidating protein higher order structure (HOS). It does this by adding to certain amino acid residues a mass tag, whose reaction extent depends on solvent accessibility and microenvironment of the protein. Unlike reactive free radicals and carbenes, these specific footprinters react slower than protein unfolding. Thus, their footprinting, under certain conditions, provokes structural changes to the protein, leading to labeling on non-native structures. It is critical to establish conditions (i.e., reagent concentrations, time of reaction) to ensure that the structure of the protein following footprinting remains native. Here, we compare the efficacy of five methods in assessing protein HOS following footprinting at the intact protein level and then further localize the perturbation at the peptide level. Three are MS-based methods that provide dose-response plot analysis, evaluation of Poisson distributions of precursor and products, and determination of the average number of modifications. These MS-based methods reliably and effectively indicate HOS perturbation at the intact protein level, whereas spectroscopic methods (circular dichroism (CD) and dynamic light scattering (DLS)) are less sensitive in monitoring subtle HOS perturbation caused by footprinting. Evaluation of HOS at the peptide level indicates regions that are sensitive to localized perturbations. Peptide-level analysis also provides higher resolution of the HOS perturbation, and we recommend using it for future footprinting studies. Overall, this work shows conclusive evidence for HOS perturbation caused by footprinting. Implementation of quality control workflows can identify conditions to avoid the perturbation, for footprinting, allowing accurate and reliable identification of protein structural changes that accompany, for example, ligand interactions, mutations, and changes in solution environment.

Transition Metal Ion FRET-Based Probe to Study Cu(II)-Mediated Amyloid- Ligand Binding

Recent therapeutic strategies suggest that small peptides can act as aggregation inhibitors of monomeric amyloid-β (Αβ) by inducing structural rearrangements upon complexation. However, characterizing the binding events in such dynamic and transient noncovalent complexes, especially in the presence of natively occurring metal ions, remains a challenge. Here, we deploy a combined transition metal ion Förster resonance energy transfer (tmFRET) and native ion mobility-mass spectrometry (IM-MS) approach to characterize the structure of mass- and charge-selected Aβ complexes with Cu(II) ions (a quencher) and a potential aggregation inhibitor, a small neuropeptide named leucine enkephalin (LE). We show conformational changes of monomeric Αβ species upon Cu(II)-binding, indicating an uncoiled N-terminus and a close interaction between the C-terminus and the central hydrophobic region. Furthermore, we introduce LE labeled at the N-terminus with a metal-chelating agent, nitrilotriacetic acid (NTA). This allows us to employ tmFRET to probe the binding even in low-abundance and transient Aβ-inhibitor-metal ion complexes. Complementary intramolecular distance and global shape information from tmFRET and native IM-MS, respectively, confirmed Cu(II) displacement toward the N-terminus of Αβ, which discloses the binding region and the inhibitor's orientation.

Exploring Residue-Level Interactions between the Biofilm-Driving R2ab Protein and Polystyrene Nanoparticles

In biological systems, proteins can bind to nanoparticles to form a "corona" of adsorbed molecules. The nanoparticle corona is of significant interest because it impacts an organism's response to a nanomaterial. Understanding the corona requires knowledge of protein structure, orientation, and dynamics at the surface. A residue-level mapping of protein behavior on nanoparticle surfaces is needed, but this mapping is difficult to obtain with traditional approaches. Here, we have investigated the interaction between R2ab and polystyrene nanoparticles (PSNPs) at the level of individual residues. R2ab is a bacterial surface protein from Staphylococcus epidermidis and is known to interact strongly with polystyrene, leading to biofilm formation. We have used mass spectrometry after lysine methylation and hydrogen-deuterium exchange (HDX) NMR spectroscopy to understand how the R2ab protein interacts with PSNPs of different sizes. Lysine methylation experiments reveal subtle but statistically significant changes in methylation patterns in the presence of PSNPs, indicating altered protein surface accessibility. HDX rates become slower overall in the presence of PSNPs. However, some regions of the R2ab protein exhibit faster than average exchange rates in the presence of PSNPs, while others are slower than the average behavior, suggesting conformational changes upon binding. HDX rates and methylation ratios support a recently proposed "adsorbotope" model for PSNPs, wherein adsorbed proteins consist of unfolded anchor points interspersed with partially structured regions. Our data also highlight the challenges of characterizing complex protein-nanoparticle interactions using these techniques, such as fast exchange rates. While providing insights into how R2ab adsorbs onto PSNP surfaces, this research emphasizes the need for advanced methods to comprehend residue-level interactions in the nanoparticle corona.

Comprehensive characterization of higher order structure changes in methionine oxidized monoclonal antibodies via NMR chemometric analysis and biophysical approaches

The higher order structure (HOS) of monoclonal antibodies (mAbs) is an important quality attribute with strong contribution to clinically relevant biological functions and drug safety. Due to the multi-faceted nature of HOS, the synergy of multiple complementary analytical approaches can substantially improve the understanding, accuracy, and resolution of HOS characterization. In this study, we applied one- and two-dimensional (1D and 2D) nuclear magnetic resonance (NMR) spectroscopy coupled with chemometric analysis, as well as circular dichroism (CD), differential scanning calorimetry (DSC), and fluorescence spectroscopy as orthogonal methods, to characterize the impact of methionine (Met) oxidation on the HOS of an IgG1 mAb. We used a forced degradation method involving concentration-dependent oxidation by peracetic acid, in which Met oxidation is site-specifically quantified by liquid chromatography-mass spectrometry. Conventional biophysical techniques report nuanced results, in which CD detects no change to the secondary structure and little change in the tertiary structure. Yet, DSC measurements show the destabilization of Fab and Fc domains due to Met oxidation. More importantly, our study demonstrates that 1D and 2D NMR and chemometric analysis can provide semi-quantitative analysis of chemical modifications and resolve localized conformational changes with high sensitivity. Furthermore, we leveraged a novel 15N-Met labeling technique of the antibody to directly observe structural perturbations at the oxidation sites. The NMR methods described here to probe HOS changes are highly reliable and practical in biopharmaceutical characterization.

Dimethylthiourea as a Quencher in Hydroxyl Radical Protein Footprinting Experiments

Hydroxyl radical protein footprinting (HRPF) is a mass-spectrometry-based method for studying protein structures, interactions, conformations, and folding. This method is based on the irreversible labeling of solvent-exposed amino acid side chains by hydroxyl radicals. While catalase is commonly used as a quencher after the labeling of a protein by the hydroxyl radicals to efficiently remove the remaining hydrogen peroxide, it has some disadvantages. Catalase quenching adds a relatively high amount of protein to the sample, limiting the sensitivity of the method due to dynamic range issues and causing significant issues when dealing with more complex samples. We evaluated dimethylthiourea (DMTU) as a replacement for catalase in the quenching HRPF reactions. We observed that DMTU is highly effective at quenching HRPF oxidation. DMTU does not cause the background protein issues that catalase does, resulting in an increased number of protein identifications from complex mixtures. We recommend the replacement of catalase quenching with DMTU for all HRPF experiments.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

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.

Characterization of Higher Order Structural Changes of a Thermally Stressed Monoclonal Antibody via Mass Spectrometry Footprinting and Other Biophysical Approaches

Characterizing changes in the higher order structure (HOS) of monoclonal antibodies upon stressed conditions is critical to gaining a better understanding of the product and process. One single biophysical approach may not be best suited to assess HOS comprehensively; thus, the synergy from multiple, complementary approaches improves characterization accuracy and resolution. In this study, we employed two mass spectrometry (MS )-based footprinting techniques, namely, fast photochemical oxidation of proteins (FPOP)-MS and hydrogen-deuterium exchange (HDX)-MS, supported by dynamic light scattering (DLS), differential scanning calorimetry (DSC), circular dichroism (CD), and nuclear magnetic resonance (NMR) to study changes to the HOS of a mAb upon thermal stress. The biophysical techniques report a nuanced characterization of the HOS in which CD detects no changes to the secondary or tertiary structure, yet DLS measurements show an increase in the hydrodynamic radius. DSC indicates that the stability decreases, and chemical or conformational changes accumulate with incubation time according to NMR. Furthermore, whereas HDX-MS does not indicate HOS changes, FPOP-MS footprinting reveals conformational changes at residue resolution for some amino acids. The local phenomena observed with FPOP-MS indicate that several residues show various patterns of degradation during thermal stress: no change, an increase in solvent exposure, and a biphasic response to solvent exposure. All evidences show that FPOP-MS efficiently resolves subtle structural changes and novel degradation pathways upon thermal stress treatment at residue-level resolution.

Comprehensive Overview of Bottom-Up Proteomics using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods to aid the novice and experienced researcher. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this work to serve as a basic resource for new practitioners in the field of shotgun or bottom-up proteomics.

Efficient Analysis of Proteome-Wide FPOP Data by FragPipe

Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent-accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and a lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP data sets. Our workflow, implemented as part of the FragPipe computational platform, combines the speed of the MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 150% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.

What's the defect? Using mass defects to study oligomerization of membrane proteins and peptides in nanodiscs with native mass spectrometry

Many membrane proteins form functional complexes that are either homo- or hetero-oligomeric. However, it is challenging to characterize membrane protein oligomerization in intact lipid bilayers, especially for polydisperse mixtures. Native mass spectrometry of membrane proteins and peptides inserted in lipid nanodiscs provides a unique method to study the oligomeric state distribution and lipid preferences of oligomeric assemblies. To interpret these complex spectra, we developed novel data analysis methods using macromolecular mass defect analysis. Here, we provide an overview of how mass defect analysis can be used to study oligomerization in nanodiscs, discuss potential limitations in interpretation, and explore strategies to resolve these ambiguities. Finally, we review recent work applying this technique to studying formation of antimicrobial peptide, amyloid protein, and viroporin complexes with lipid membranes.

Exploring the Residue-Level Interactions between the R2ab Protein and Polystyrene Nanoparticles

In biological systems, proteins can bind to nanoparticles to form a "corona" of adsorbed molecules. The nanoparticle corona is of high interest because it impacts the organism's response to the nanomaterial. Understanding the corona requires knowledge of protein structure, orientation, and dynamics at the surface. Ultimately, a residue-level mapping of protein behavior on nanoparticle surfaces is needed, but this mapping is difficult to obtain with traditional approaches. Here, we have investigated the interaction between R2ab and polystyrene nanoparticles (PSNPs) at the level of individual residues. R2ab is a bacterial surface protein from Staphylococcus epidermidis and is known to interact strongly with polystyrene, leading to biofilm formation. We have used mass spectrometry after lysine methylation and hydrogen-deuterium exchange (HDX) NMR spectroscopy to understand how the R2ab protein interacts with PSNPs of different sizes. Through lysine methylation, we observe subtle but statistically significant changes in methylation patterns in the presence of PSNPs, indicating altered protein surface accessibility. HDX measurements reveal that certain regions of the R2ab protein undergo faster exchange rates in the presence of PSNPs, suggesting conformational changes upon binding. Both results support a recently proposed "adsorbotope" model, wherein adsorbed proteins consist of unfolded anchor points interspersed with regions of partial structure. Our data also highlight the challenges of characterizing complex protein-nanoparticle interactions using these techniques, such as fast exchange rates. While providing insights into how proteins respond to nanoparticle surfaces, this research emphasizes the need for advanced methods to comprehend these intricate interactions fully at the residue level.

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

Efficient Analysis of Proteome-wide FPOP Data by FragPipe

Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP datasets. Our workflow combines the speed of MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 50% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.

Development of Spheroid-FPOP: An In-Cell Protein Footprinting Method for 3D Tumor Spheroids

Many cancer drugs fail at treating solid epithelial tumors with hypoxia and insufficient drug penetration thought to be contributing factors to the observed chemoresistance. Owing to this, it is imperative to evaluate potential cancer drugs in conditions as close to in vivo as possible, which is not always done. To address this, we developed a mass spectrometry-based protein footprinting method for exploring the impact of hypoxia on protein in 3D colorectal cancer cells. Our group has previously extended the protein footprinting method fast photochemical oxidation of proteins (FPOP) for live cell analysis (IC-FPOP); however, this is the first application of IC-FPOP in a 3D cancer model. In this study, we perform IC-FPOP on intact spheroids (Spheroid-FPOP) using a modified version of the static platform incubator with an XY movable stage (PIXY) FPOP platform. We detected modification in each of three spheroid layers, even the hypoxic core. Pathway analysis revealed protein modifications in over 10 distinct protein pathways, including some involved in protein ubiquitination; a process modulated in cancer pathologies. These results demonstrate the feasibility of Spheroid-FPOP to be utilized as a tool to interrogate protein interactions within a native tumor microenvironment.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Quantitative structural proteomics in living cells by covalent protein painting

The fold and conformation of proteins are key to successful cellular function, but all techniques for protein structure determination are performed in an artificial environment with highly purified proteins. While protein conformations have been solved to atomic resolution and modern protein structure prediction tools rapidly generate near accurate models of proteins, there is an unmet need to uncover the conformations of proteins in living cells. Here, we describe Covalent Protein Painting (CPP), a simple and fast method to infer structural information on protein conformation in cells with a quantitative protein footprinting technology. CPP monitors the conformational landscape of the 3D proteome in cells with high sensitivity and throughput. A key advantage of CPP is its' ability to quantitatively compare the 3D proteomes between different experimental conditions and to discover significant changes in the protein conformations. We detail how to perform a successful CPP experiment, the factors to consider before performing the experiment, and how to interpret the results.

Quantifying In Situ Structural Stabilities of Human Blood Plasma Proteins Using a Novel Iodination Protein Stability Assay

Many of the diseases that plague society today are driven by a loss of protein quality. One method to quantify protein quality is to measure the protein folding stability (PFS). Here, we present a novel mass spectrometry (MS)-based approach for PFS measurement, iodination protein stability assay (IPSA). IPSA quantifies the PFS by tracking the surface-accessibility differences of tyrosine, histidine, methionine, and cysteine under denaturing conditions. Relative to current methods, IPSA increases protein coverage and granularity to track the PFS changes of a protein along its sequence. To our knowledge, this study is the first time the PFS of human serum proteins has been measured in the context of the blood serum (in situ). We show that IPSA can quantify the PFS differences between different transferrin iron-binding states in near in vivo conditions. We also show that the direction of the denaturation curve reflects the in vivo surface accessibility of the amino acid residue and reproducibly reports a residue-specific PFS. Along with IPSA, we introduce an analysis tool Chalf that provides a simple workflow to calculate the residue-specific PFS. The introduction of IPSA increases the potential to use protein structural stability as a structural quality metric in understanding the etiology and progression of human disease. Data is openly available at Chorusproject.org (project ID 1771).

Conditional Fragment Ion Probabilities Improve Database Searching for Nonmonoisotopic Precursors

Stochastic, intensity-based precursor isolation can result in isotopically enriched fragment ions. This problem is exacerbated for large peptides and stable isotope labeling experiments using deuterium or ¹⁵N. For stable isotope labeling experiments, incomplete and ubiquitous labeling strategies result in the isolation of peptide ions composed of many distinct structural isomers. Unfortunately, existing proteomics search algorithms do not account for this variability in isotopic incorporation, and thus often yield poor peptide and protein identification rates. We sought to resolve this shortcoming by deriving the expected isotopic distributions of each fragment ion and incorporating them into the theoretical mass spectra used for peptide-spectrum-matching. We adapted the Comet search platform to integrate a modified spectral prediction algorithm we term Conditional fragment Ion Distribution Search (CIDS). Comet-CIDS uses a traditional database searching strategy, but for each candidate peptide we compute the isotopic distribution of each fragment to better match the observed m/z distributions. Evaluating previously generated D₂O and ¹⁵N labeled data sets, we found that Comet-CIDS identified more confident peptide spectral matches and higher protein sequence coverage compared to traditional theoretical spectra generation, with the magnitude of improvement largely determined by the amount of labeling in the sample.

Native mass spectrometry for the investigation of protein structural (dis)order

A central challenge in structural biology is represented by dynamic and heterogeneous systems, as typically represented by proteins in solution, with the extreme case of intrinsically disordered proteins (IDPs) [1-3]. These proteins lack a specific three-dimensional structure and have poorly organized secondary structure. For these reasons, they escape structural characterization by conventional biophysical methods. The investigation of these systems requires description of conformational ensembles, rather than of unique, defined structures or bundles of largely superimposable structures. Mass spectrometry (MS) has become a central tool in this field, offering a variety of complementary approaches to generate structural information on either folded or disordered proteins [4-6]. Two main categories of methods can be recognized. On one side, conformation-dependent reactions (such as cross-linking, covalent labeling, H/D exchange) are exploited to label molecules in solution, followed by the characterization of the labeling products by denaturing MS [7-11]. On the other side, non-denaturing ("native") MS can be used to directly explore the different conformational components in terms of geometry and structural compactness [12-16]. All these approaches have in common the capability to conjugate protein structure investigation with the peculiar analytical power of MS measurements, offering the possibility of assessing species distributions for folding and binding equilibria and the combination of both. These methods can be combined with characterization of noncovalent complexes [17, 18] and post-translational modifications [19-23]. This review focuses on the application of native MS to protein structure and dynamics investigation, with a general methodological section, followed by examples on specific proteins from our laboratory.

Structural mass spectrometry of membrane proteins

The analysis of proteins and protein complexes by mass spectrometry (MS) has come a long way since the invention of electrospray ionization (ESI) in the mid 80s. Originally used to characterize small soluble polypeptide chains, MS has progressively evolved over the past 3 decades towards the analysis of samples of ever increasing heterogeneity and complexity, while the instruments have become more and more sensitive and resolutive. The proofs of concepts and first examples of most structural MS methods appeared in the early 90s. However, their application to membrane proteins, key targets in the biopharma industry, is more recent. Nowadays, a wealth of information can be gathered from such MS-based methods, on all aspects of membrane protein structure: sequencing (and more precisely proteoform characterization), but also stoichiometry, non-covalent ligand binding (metals, drug, lipids, carbohydrates), conformations, dynamics and distance restraints for modelling. In this review, we present the concept and some historical and more recent applications on membrane proteins, for the major structural MS methods.

Simulation of Energy-Resolved Mass Spectrometry Distributions from Surface-Induced Dissociation

Understanding the relationship between protein structure and experimental data is crucial for utilizing experiments to solve biochemical problems and optimizing the use of sparse experimental data for structural interpretation. Tandem mass spectrometry (MS/MS) can be used with a variety of methods to collect structural data for proteins. One example is surface-induced dissociation (SID), which is used to break apart protein complexes (via a surface collision) into intact subcomplexes and can be performed at multiple laboratory frame SID collision energies. These energy-resolved MS/MS experiments have shown that the profile of the breakages depends on the acceleration energy of the collision. It is possible to extract an appearance energy (AE) from energy-resolved mass spectrometry (ERMS) data, which shows the relative intensity of each type of subcomplex as a function of SID acceleration energy. We previously determined that these AE values for specific interfaces correlated with structural features related to interface strength. In this study, we further examined the structural relationships by developing a method to predict the full ERMS plot from the structure, rather than extracting a single value. First, we noted that for proteins with multiple interface types, we could reproduce the correct shapes of breakdown curves, further confirming previous structural hypotheses. Next, we demonstrated that interface size and energy density (measured using Rosetta) correlated with data derived from the ERMS plot (R2 = 0.71). Furthermore, based on this trend, we used native crystal structures to predict ERMS. The majority of predictions resulted in good agreement, and the average root-mean-square error was 0.20 for the 20 complexes in our data set. We also show that if additional information on cleavage as a function of collision energy could be obtained, the accuracy of predictions improved further. Finally, we demonstrated that ERMS prediction results were better for the native than for inaccurate models in 17/20 cases. An application to run this simulation has been developed in Rosetta, which is freely available for use.

Mass Spectrometry Methods for Measuring Protein Stability

Mass spectrometry is a central technology in the life sciences, providing our most comprehensive account of the molecular inventory of the cell. In parallel with developments in mass spectrometry technologies targeting such assessments of cellular composition, mass spectrometry tools have emerged as versatile probes of biomolecular stability. In this review, we cover recent advancements in this branch of mass spectrometry that target proteins, a centrally important class of macromolecules that accounts for most biochemical functions and drug targets. Our efforts cover tools such as hydrogen-deuterium exchange, chemical cross-linking, ion mobility, collision induced unfolding, and other techniques capable of stability assessments on a proteomic scale. In addition, we focus on a range of application areas where mass spectrometry-driven protein stability measurements have made notable impacts, including studies of membrane proteins, heat shock proteins, amyloidogenic proteins, and biotherapeutics. We conclude by briefly discussing the future of this vibrant and fast-moving area of research.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

Challenges and Opportunities for Bayesian Statistics in Proteomics

Proteomics is a data-rich science with complex experimental designs and an intricate measurement process. To obtain insights from the large data sets produced, statistical methods, including machine learning, are routinely applied. For a quantity of interest, many of these approaches only produce a point estimate, such as a mean, leaving little room for more nuanced interpretations. By contrast, Bayesian statistics allows quantification of uncertainty through the use of probability distributions. These probability distributions enable scientists to ask complex questions of their proteomics data. Bayesian statistics also offers a modular framework for data analysis by making dependencies between data and parameters explicit. Hence, specifying complex hierarchies of parameter dependencies is straightforward in the Bayesian framework. This allows us to use a statistical methodology which equals, rather than neglects, the sophistication of experimental design and instrumentation present in proteomics. Here, we review Bayesian methods applied to proteomics, demonstrating their potential power, alongside the challenges posed by adopting this new statistical framework. To illustrate our review, we give a walk-through of the development of a Bayesian model for dynamic organic orthogonal phase-separation (OOPS) data.

Human γS-Crystallin Resists Unfolding Despite Extensive Chemical Modification from Exposure to Ionizing Radiation

Ionizing radiation has dramatic effects on living organisms, causing damage to proteins, DNA, and other cellular components. γ radiation produces reactive oxygen species (ROS) that damage biological macromolecules. Protein modification due to interactions with hydroxyl radical is one of the most common deleterious effects of radiation. The human eye lens is particularly vulnerable to the effects of ionizing radiation, as it is metabolically inactive and its proteins are not recycled after early development. Therefore, radiation damage accumulates and eventually can lead to cataract formation. Here we explore the impact of γ radiation on a long-lived structural protein. We exposed the human eye lens protein γS-crystallin (HγS) to high doses of γ radiation and investigated the chemical and structural effects. HγS accumulated many post-translational modifications (PTMs), appearing to gain significant oxidative damage. Biochemical assays suggested that cysteines were affected, with the concentration of free thiol reduced with increasing γ radiation exposure. SDS-PAGE analysis showed that irradiated samples form protein-protein cross-links, including nondisulfide covalent bonds. Tandem mass spectrometry on proteolytic digests of irradiated samples revealed that lysine, methionine, tryptophan, leucine, and cysteine were oxidized. Despite these chemical modifications, HγS remained folded past 10.8 kGy of γ irradiation as evidenced by circular dichroism and intrinsic tryptophan fluorescence spectroscopy.

Epitope mapping of anti-drug antibodies to a clinical candidate bispecific antibody

Anti-drug antibodies (ADA) can limit the efficacy and safety of therapeutic antibodies. However, determining the exact nature of ADA interactions with the target drug via epitope mapping is challenging due to the polyclonal nature of the IgG response. Here, we demonstrate successful proof-of-concept for the application of hydroxyl radical footprinting (HRF)-mass spectrometry for epitope mapping of ADAs obtained from goats that were administered a knob-into-hole bispecific antibody (BsAb1). Subsequently, we performed epitope mapping of ADAs obtained from cynomolgus (cyno) monkeys that were administered BsAb1 as we described in a recently published paper. Herein, we provide the first data to demonstrate the feasibility of using HRF for ADA epitope mapping, and show that both goat and cyno-derived ADAs specifically target the complementary-determining regions in both arms of BsAb1, suggesting that the ADA epitopes on BsAb1 may be species-independent.

Nanoparticles and photochemistry for native-like transmembrane protein footprinting

Mass spectrometry-based footprinting can probe higher order structure of soluble proteins in their native states and serve as a complement to high-resolution approaches. Traditional footprinting approaches, however, are hampered for integral membrane proteins because their transmembrane regions are not accessible to solvent, and they contain hydrophobic residues that are generally unreactive with most chemical reagents. To address this limitation, we bond photocatalytic titanium dioxide (TiO₂) nanoparticles to a lipid bilayer. Upon laser irradiation, the nanoparticles produce local concentrations of radicals that penetrate the lipid layer, which is made permeable by a simultaneous laser-initiated Paternò-Büchi reaction. This approach achieves footprinting for integral membrane proteins in liposomes, helps locate both ligand-binding residues in a transporter and ligand-induced conformational changes, and reveals structural aspects of proteins at the flexible unbound state. Overall, this approach proves effective in intramembrane footprinting and forges a connection between material science and biology.

Hydroxyl Radical Protein Footprinting: A Mass Spectrometry-Based Structural Method for Studying the Higher Order Structure of Proteins

Hydroxyl radical protein footprinting (HRPF) coupled to mass spectrometry has been successfully used to investigate a plethora of protein-related questions. The method, which utilizes hydroxyl radicals to oxidatively modify solvent-accessible amino acids, can inform on protein interaction sites and regions of conformational change. Hydroxyl radical-based footprinting was originally developed to study nucleic acids, but coupling the method with mass spectrometry has enabled the study of proteins. The method has undergone several advancements since its inception that have increased its utility for more varied applications such as protein folding and the study of biotherapeutics. In addition, recent innovations have led to the study of increasingly complex systems including cell lysates and intact cells. Technological advances have also increased throughput and allowed for better control of experimental conditions. In this review, we provide a brief history of the field of HRPF and detail recent innovations and applications in the field.

Recent advancements in mass spectrometry for higher order structure characterization of protein therapeutics

Molecular characterization of higher order structure (HOS) in protein therapeutics is crucial to the selection of candidate molecules, understanding of structure-function relationships, formulation development, stability assessment, and comparability studies. Recent advances in mass spectrometry (MS), including native MS, hydrogen/deuterium exchange (HDX)-MS, and fast photochemical oxidation of proteins (FPOP) coupled with MS, have provided orthogonal ways to characterize HOS of protein therapeutics. In this review, we present the utility of native MS, HDX-MS and FPOP-MS in protein therapeutics discovery and development, with a focus on epitope mapping, aggregation assessment, and comparability studies. We also discuss future trends in the application of these MS methods to HOS characterization.

Fenton-Chemistry-Based Oxidative Modification of Proteins Reflects Their Conformation

In order to understand protein structure to a sufficient extent for, e.g., drug discovery, no single technique can provide satisfactory information on both the lowest-energy conformation and on dynamic changes over time (the ‘four-dimensional’ protein structure). Instead, a combination of complementary techniques is required. Mass spectrometry methods have shown promise in addressing protein dynamics, but often rely on the use of high-end commercial or custom instruments. Here, we apply well-established chemistry to conformation-sensitive oxidative protein labelling on a timescale of a few seconds, followed by analysis through a routine protein analysis workflow. For a set of model proteins, we show that site selectivity of labelling can indeed be rationalised in terms of known structural information, and that conformational changes induced by ligand binding are reflected in the modification pattern. In addition to conventional bottom-up analysis, further insights are obtained from intact mass measurement and native mass spectrometry. We believe that this method will provide a valuable and robust addition to the ‘toolbox’ of mass spectrometry researchers studying higher-order protein structure.

Integration of Mass Spectrometry Data for Structural Biology

Mass spectrometry (MS) is increasingly being used to probe the structure and dynamics of proteins and the complexes they form with other macromolecules. There are now several specialized MS methods, each with unique sample preparation, data acquisition, and data processing protocols. Collectively, these methods are referred to as structural MS and include cross-linking, hydrogen-deuterium exchange, hydroxyl radical footprinting, native, ion mobility, and top-down MS. Each of these provides a unique type of structural information, ranging from composition and stoichiometry through to residue level proximity and solvent accessibility. Structural MS has proved particularly beneficial in studying protein classes for which analysis by classic structural biology techniques proves challenging such as glycosylated or intrinsically disordered proteins. To capture the structural details for a particular system, especially larger multiprotein complexes, more than one structural MS method with other structural and biophysical techniques is often required. Key to integrating these diverse data are computational strategies and software solutions to facilitate this process. We provide a background to the structural MS methods and briefly summarize other structural methods and how these are combined with MS. We then describe current state of the art approaches for the integration of structural MS data for structural biology. We quantify how often these methods are used together and provide examples where such combinations have been fruitful. To illustrate the power of integrative approaches, we discuss progress in solving the structures of the proteasome and the nuclear pore complex. We also discuss how information from structural MS, particularly pertaining to protein dynamics, is not currently utilized in integrative workflows and how such information can provide a more accurate picture of the systems studied. We conclude by discussing new developments in the MS and computational fields that will further enable in-cell structural studies.

In-Cell Labeling and Mass Spectrometry for Systems-Level Structural Biology

Biological systems have evolved to utilize proteins to accomplish nearly all functional roles needed to sustain life. A majority of biological functions occur within the crowded environment inside cells and subcellular compartments where proteins exist in a densely packed complex network of protein-protein interactions. The structural biology field has experienced a renaissance with recent advances in crystallography, NMR, and CryoEM that now produce stunning models of large and complex structures previously unimaginable. Nevertheless, measurements of such structural detail within cellular environments remain elusive. This review will highlight how advances in mass spectrometry, chemical labeling, and informatics capabilities are merging to provide structural insights on proteins, complexes, and networks that exist inside cells. Because of the molecular detection specificity provided by mass spectrometry and proteomics, these approaches provide systems-level information that not only benefits from conventional structural analysis, but also is highly complementary. Although far from comprehensive in their current form, these approaches are currently providing systems structural biology information that can uniquely reveal how conformations and interactions involving many proteins change inside cells with perturbations such as disease, drug treatment, or phenotypic differences. With continued advancements and more widespread adaptation, systems structural biology based on in-cell labeling and mass spectrometry will provide an even greater wealth of structural knowledge.

Higher-Order Structure Characterization of NKG2A/CD94 Protein Complex and Anti-NKG2A Antibody Binding Epitopes by Mass Spectrometry-Based Protein Footprinting Strategies

NK group 2 member A (NKG2A), an immune checkpoint inhibitor, is an emerging therapeutic target in immuno-oncology. NKG2A forms a heterodimer with CD94 on the cell surface of NK and a subset of T cells and recognizes the nonclassical human leukocyte antigen (HLA-E) in humans. Therapeutic blocking antibodies that block the ligation between HLA-E and NKG2A/CD94 have been shown to enhance antitumor immunity in mice and humans. In this study, we illustrate the practical utilities of mass spectrometry (MS)-based protein footprinting in areas from reagent characterization to antibody epitope mapping. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) in the higher-order structure characterization of NKG2A in complex with CD94 provides novel insights into the conformational dynamics of NKG2A/CD94 heterodimer. To fully understand antibody/target interactions, we employed complementary protein footprinting methods, including HDX-MS and fast photochemical oxidation of proteins (FPOP)-MS, to determine the binding epitopes of therapeutic monoclonal antibodies targeting NKG2A. Such a combination approach provides molecular insights into the binding mechanisms of antibodies to NKG2A with high specificity, demonstrating the blockade of NKG2A/HLA-E interaction.

Investigation of D76N β2-Microglobulin Using Protein Footprinting and Structural Mass Spectrometry

NMR studies and X-ray crystallography have shown that the structures of the 99-residue amyloidogenic protein β2-microglobulin (β2m) and its more aggregation-prone variant, D76N, are indistinguishable, and hence, the reason for the striking difference in their aggregation propensities remains elusive. Here, we have employed two protein footprinting methods, hydrogen-deuterium exchange (HDX) and fast photochemical oxidation of proteins (FPOP), in conjunction with ion mobility-mass spectrometry, to probe the differences in conformational dynamics of the two proteins. Using HDX-MS, a clear difference in HDX protection is observed between these two proteins in the E-F loop (residues 70-77) which contains the D76N substitution, with a significantly higher deuterium uptake being observed in the variant protein. Conversely, following FPOP-MS only minimal differences in the level of oxidation between the two proteins are observed in the E-F loop region, suggesting only modest side-chain movements in that area. Together the HDX-MS and FPOP-MS data suggest that a tangible perturbation to the hydrogen-bonding network in the E-F loop has taken place in the D76N variant and furthermore illustrate the benefit of using multiple complementary footprinting methods to address subtle, but possibly biologically important, differences between highly similar proteins.

Evaluating the Sulfate Radical Anion as a New Reagent for In-Cell Fast Photochemical Oxidation of Proteins

Fast photochemical oxidation of proteins (FPOP) has demonstrated the ability to inform on the higher order structure of proteins. Recent technological advances have extended FPOP to live cells (IC-FPOP) using multiple cell lines and in vivo (IV-FPOP) using C. elegans. These innovations allow proteins to be studied in their native cellular environment. Hydroxyl radicals are generated via the photoloysis of hydrogen peroxide. Hydrogen peroxide is a signaling molecule that can induce changes to some proteins in the cell limiting the proteins that can be studied by IC-FPOP. Here, we evaluate the sulfate radical anion as a footprinting label in IC-FPOP with sodium persulfate as the precursor. Our findings show a 1.5-fold increase in the number of modified proteins compared to IC-FPOP using hydroxyl radicals at the same precursor concentration demonstrating the amenability of this radical with IC-FPOP.