Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications

Impact of Charge State on Characterization of Large Middle-Down Sized Peptides by Tandem Mass Spectrometry

Fragmentation trends of large peptides were characterized by five activation methods, including HCD, ETD, EThcD, 213 nm UVPD, and 193 nm UVPD. Sequence coverages and scores were assessed based on charge site, peptide sequence, and peptide size. The effect of charge state and peptide size on sequence coverage was explored for a Glu-C digest of E. coli ribosomal proteins, and linear regression analysis of the collection of peptides indicated that HCD, ETD, and EThcD have a higher dependence charge state than 193 and 213 nm UV. Four model peptides, neuromedin, glucagon, galanin, and amyloid β, were characterized in greater detail based on charge site analysis and showed a charge state dependence on sequence coverage for collision and electron-based activation methods.

In situ analysis of osmolyte mechanisms of proteome thermal stabilization

Organisms use organic molecules called osmolytes to adapt to environmental conditions. In vitro studies indicate that osmolytes thermally stabilize proteins, but mechanisms are controversial, and systematic studies within the cellular milieu are lacking. We analyzed Escherichia coli and human protein thermal stabilization by osmolytes in situ and across the proteome. Using structural proteomics, we probed osmolyte effects on protein thermal stability, structure and aggregation, revealing common mechanisms but also osmolyte- and protein-specific effects. All tested osmolytes (trimethylamine N-oxide, betaine, glycerol, proline, trehalose and glucose) stabilized many proteins, predominantly via a preferential exclusion mechanism, and caused an upward shift in temperatures at which most proteins aggregated. Thermal profiling of the human proteome provided evidence for intrinsic disorder in situ but also identified potential structure in predicted disordered regions. Our analysis provides mechanistic insight into osmolyte function within a complex biological matrix and sheds light on the in situ prevalence of intrinsically disordered regions.

Structural Mass Spectrometry Captures Residue-Resolved Comprehensive Conformational Rearrangements of a G Protein-Coupled Receptor

G protein-coupled receptor (GPCR) structural studies with in-solution spectroscopic approaches have offered distinctive insights into GPCR activation and signaling that highly complement those yielded from structural snapshots by crystallography or cryo-EM. While most current spectroscopic approaches allow for probing structural changes at selected residues or loop regions, they are not suitable for capturing a holistic view of GPCR conformational rearrangements across multiple domains. Herein, we develop an approach based on limited proteolysis mass spectrometry (LiP-MS) to simultaneously monitor conformational alterations of a large number of residues spanning both flexible loops and structured transmembrane domains for a given GPCR. To benchmark LiP-MS for GPCR conformational profiling, we studied the adenosine 2A receptor (A2AR) in response to different ligand binding (agonist/antagonist/allosteric modulators) and G protein coupling. Systematic and residue-resolved profiling of A2AR conformational rearrangements by LiP-MS precisely captures structural mechanisms in multiple domains underlying ligand engagement, receptor activation, and allostery, and may also reflect local conformational flexibility. Furthermore, these residue-resolution structural fingerprints of the A2AR protein allow us to readily classify ligands of different pharmacology and distinguish the G protein-coupled state. Thus, our study provides a new structural MS approach that would be generalizable to characterizing conformational transition and plasticity for challenging integral membrane proteins.

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.

Decoding the molecular interplay in the central dogma: An overview of mass spectrometry-based methods to investigate protein-metabolite interactions

With the emergence of next-generation nucleotide sequencing and mass spectrometry-based proteomics and metabolomics tools, we have comprehensive and scalable methods to analyze the genes, transcripts, proteins, and metabolites of a multitude of biological systems. Despite the fascinating new molecular insights at the genome, transcriptome, proteome and metabolome scale, we are still far from fully understanding cellular organization, cell cycles and biology at the molecular level. Significant advances in sensitivity and depth for both sequencing as well as mass spectrometry-based methods allow the analysis at the single cell and single molecule level. At the same time, new tools are emerging that enable the investigation of molecular interactions throughout the central dogma of molecular biology. In this review, we provide an overview of established and recently developed mass spectrometry-based tools to probe metabolite-protein interactions-from individual interaction pairs to interactions at the proteome-metabolome scale.

An MSstats workflow for detecting differentially abundant proteins in large-scale data-independent acquisition mass spectrometry experiments with FragPipe processing

Technological advances in mass spectrometry and proteomics have made it possible to perform larger-scale and more-complex experiments. The volume and complexity of the resulting data create major challenges for downstream analysis. In particular, next-generation data-independent acquisition (DIA) experiments enable wider proteome coverage than more traditional targeted approaches but require computational workflows that can manage much larger datasets and identify peptide sequences from complex and overlapping spectral features. Data-processing tools such as FragPipe, DIA-NN and Spectronaut have undergone substantial improvements to process spectral features in a reasonable time. Statistical analysis tools are needed to draw meaningful comparisons between experimental samples, but these tools were also originally designed with smaller datasets in mind. This protocol describes an updated version of MSstats that has been adapted to be compatible with large-scale DIA experiments. A very large DIA experiment, processed with FragPipe, is used as an example to demonstrate different MSstats workflows. The choice of workflow depends on the user's computational resources. For datasets that are too large to fit into a standard computer's memory, we demonstrate the use of MSstatsBig, a companion R package to MSstats. The protocol also highlights key decisions that have a major effect on both the results and the processing time of the analysis. The MSstats processing can be expected to take 1-3 h depending on the usage of MSstatsBig. The protocol can be run in the point-and-click graphical user interface MSstatsShiny or implemented with minimal coding expertise in R.

Proteomic Discovery of RNA-Protein Molecular Clamps Using a Thermal Shift Assay with ATP and RNA (TSAR)

Uncompetitive inhibition is an effective strategy for suppressing dysregulated enzymes and their substrates, but discovery of suitable ligands depends on often-unavailable structural knowledge and serendipity. Hence, despite surging interest in mass spectrometry-based target identification, proteomic studies of substrate-dependent target engagement remain sparse. Herein, we describe the Thermal Shift Assay with ATP and RNA (TSAR) as a template for proteome-wide discovery of substrate-dependent ligand binding. Using proteomic thermal shift assays, we show that simple biochemical additives can facilitate detection of target engagement in native cell lysates. We apply our approach to rocaglates, a family of molecules that specifically clamp RNA to eukaryotic translation initiation factor 4A (eIF4A), DEAD-box helicase 3X (DDX3X), and potentially other members of the DEAD-box (DDX) family of RNA helicases. To identify unexpected interactions, we optimized a target class-specific thermal denaturation window and evaluated ATP analog and RNA probe dependencies for key rocaglate-DDX interactions. We report novel DDX targets of the rocaglate clamping spectrum, confirm that DDX3X is a common target of several widely studied analogs, and provide structural insights into divergent DDX3X affinities between synthetic rocaglates. We independently validate novel targets of high-profile rocaglates, including the clinical candidate Zotatifin (eFT226), using limited proteolysis-mass spectrometry and fluorescence polarization experiments. Taken together, our study provides a model for screening uncompetitive inhibitors using a systematic chemical-proteomics approach to uncover actionable DDX targets, clearing a path towards characterization of novel molecular clamps and associated RNA helicase targets.

Stability-based approaches in chemoproteomics

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in need to be structurally modified by the chaperone. Here, we measured the protein disaggregation and refolding activities of the main yeast cytosolic Hsp70, Ssa1, in the presence of its most abundant JDPs, Sis1 and Ydj1, and two swap mutants, in which the J-domains have been interchanged. The observed differences by which the four constructs differently cooperate with Ssa1 and cooperate with each other, as well as their observed intrinsic ability to bind misfolded substrates and trigger Ssa1's ATPase, indicate the presence of yet uncharacterized intramolecular dynamic interactions between the J-domains and the remaining C-terminal segments of these proteins. Taken together, the data suggest an autoregulatory role to these intramolecular interactions within both type A and B JDPs, which might have evolved to reduce energy-costly ATPase cycles by the Ssa1-4 chaperones that are the most abundant Hsp70s in the yeast cytosol.

Innovative strategies for measuring kinase activity to accelerate the next wave of novel kinase inhibitors

The development of protein kinase inhibitors (PKIs) has gained significance owing to their therapeutic potential for diseases like cancer. In addition, there has been a rise in refining kinase activity assays, each possessing unique biological and analytical characteristics crucial for PKI development. However, the PKI development pipeline experiences high attrition rates and approved PKIs exhibit unexploited potential because of variable patient responses. Enhancing PKI development efficiency involves addressing challenges related to understanding the PKI mechanism of action and employing biomarkers for precision medicine. Selecting appropriate kinase activity assays for these challenges can overcome these attrition rate issues. This review delves into the current obstacles in kinase inhibitor development and elucidates kinase activity assays that can provide solutions.

Monitoring host-pathogen interactions using chemical proteomics

With the rapid emergence and the dissemination of microbial resistance to conventional chemotherapy, the shortage of novel antimicrobial drugs has raised a global health threat. As molecular interactions between microbial pathogens and their mammalian hosts are crucial to establish virulence, pathogenicity, and infectivity, a detailed understanding of these interactions has the potential to reveal novel therapeutic targets and treatment strategies. Bidirectional molecular communication between microbes and eukaryotes is essential for both pathogenic and commensal organisms to colonise their host. In particular, several devastating pathogens exploit host signalling to adjust the expression of energetically costly virulent behaviours. Chemical proteomics has emerged as a powerful tool to interrogate the protein interaction partners of small molecules and has been successfully applied to advance host-pathogen communication studies. Here, we present recent significant progress made by this approach and provide a perspective for future studies.

Special Issue "Deployment of Proteomics Approaches in Biomedical Research"

Many angles of personalized medicine, such as diagnostic improvements, systems biology [...].

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions. Advances in sequencing technologies and computational methods enable the reconstruction of taxonomic and functional profiles of microbial communities using high-throughput multi-omics data. Network-based approaches, including community flux balance analysis, aim to model molecular interactions within and between communities. Despite these advances, challenges remain in computer-assisted biosynthetic capacities elucidation, requiring continued innovation and collaboration among diverse scientists. This review provides insights into the current state and future directions of computer-assisted biosynthetic capacities elucidation in studying microbial communities.

Advanced Techniques for Detecting Protein Misfolding and Aggregation in Cellular Environments

Protein misfolding and aggregation, a key contributor to the progression of numerous neurodegenerative diseases, results in functional deficiencies and the creation of harmful intermediates. Detailed visualization of this misfolding process is of paramount importance for improving our understanding of disease mechanisms and for the development of potential therapeutic strategies. While in vitro studies using purified proteins have been instrumental in delivering significant insights into protein misfolding, the behavior of these proteins in the complex milieu of living cells often diverges significantly from such simplified environments. Biomedical imaging performed in cell provides cellular-level information with high physiological and pathological relevance, often surpassing the depth of information attainable through in vitro methods. This review highlights a variety of methodologies used to scrutinize protein misfolding within biological systems. This includes optical-based methods, strategies leaning on mass spectrometry, in-cell nuclear magnetic resonance, and cryo-electron microscopy. Recent advancements in these techniques have notably deepened our understanding of protein misfolding processes and the features of the resulting misfolded species within living cells. The progression in these fields promises to catalyze further breakthroughs in our comprehension of neurodegenerative disease mechanisms and potential therapeutic interventions.

Proteomic approaches advancing targeted protein degradation

Targeted protein degradation (TPD) is an emerging modality for research and therapeutics. Most TPD approaches harness cellular ubiquitin-dependent proteolytic pathways. Proteolysis-targeting chimeras (PROTACs) and molecular glue (MG) degraders (MGDs) represent the most advanced TPD approaches, with some already used in clinical settings. Despite these advances, TPD still faces many challenges, pertaining to both the development of effective, selective, and tissue-penetrant degraders and understanding their mode of action. In this review, we focus on progress made in addressing these challenges. In particular, we discuss the utility and application of recent proteomic approaches as indispensable tools to enable insights into degrader development, including target engagement, degradation selectivity, efficacy, safety, and mode of action.

An unconventional gatekeeper mutation sensitizes inositol hexakisphosphate kinases to an allosteric inhibitor

Inositol hexakisphosphate kinases (IP6Ks) are emerging as relevant pharmacological targets because a multitude of disease-related phenotypes has been associated with their function. While the development of potent IP6K inhibitors is gaining momentum, a pharmacological tool to distinguish the mammalian isozymes is still lacking. Here, we implemented an analog-sensitive approach for IP6Ks and performed a high-throughput screen to identify suitable lead compounds. The most promising hit, FMP-201300, exhibited high potency and selectivity toward the unique valine gatekeeper mutants of IP6K1 and IP6K2, compared to the respective wild-type (WT) kinases. Biochemical validation experiments revealed an allosteric mechanism of action that was corroborated by hydrogen deuterium exchange mass spectrometry measurements. The latter analysis suggested that displacement of the αC helix, caused by the gatekeeper mutation, facilitates the binding of FMP-201300 to an allosteric pocket adjacent to the ATP-binding site. FMP-201300 therefore serves as a valuable springboard for the further development of compounds that can selectively target the three mammalian IP6Ks; either as analog-sensitive kinase inhibitors or as an allosteric lead compound for the WT kinases.

The potential of cross-linking mass spectrometry in the development of protein-protein interaction modulators

Cross-linking mass spectrometry (XL-MS) can provide a wealth of information on endogenous protein-protein interaction (PPI) networks and protein binding interfaces. These features make XL-MS an attractive tool to support the development of PPI-targeting drugs. Though not yet widely used, applications of XL-MS to drug characterization are beginning to emerge. Here, we compare XL-MS to established structural proteomics methods in drug research, discuss the current state and remaining challenges of XL-MS technology, and provide a perspective on the future role XL-MS can play in drug development, with a particular emphasis on PPI modulators.

Artificial intelligence-coupled plasmonic infrared sensor for detection of structural protein biomarkers in neurodegenerative diseases

Diagnosis of neurodegenerative disorders (NDDs) including Parkinson's disease and Alzheimer's disease is challenging owing to the lack of tools to detect preclinical biomarkers. The misfolding of proteins into oligomeric and fibrillar aggregates plays an important role in the development and progression of NDDs, thus underscoring the need for structural biomarker-based diagnostics. We developed an immunoassay-coupled nanoplasmonic infrared metasurface sensor that detects proteins linked to NDDs, such as alpha-synuclein, with specificity and differentiates the distinct structural species using their unique absorption signatures. We augmented the sensor with an artificial neural network enabling unprecedented quantitative prediction of oligomeric and fibrillar protein aggregates in their mixture. The microfluidic integrated sensor can retrieve time-resolved absorbance fingerprints in the presence of a complex biomatrix and is capable of multiplexing for the simultaneous monitoring of multiple pathology-associated biomarkers. Thus, our sensor is a promising candidate for the clinical diagnosis of NDDs, disease monitoring, and evaluation of novel therapies.

DiLeu Isobaric Labeling Coupled with Limited Proteolysis Mass Spectrometry for High-Throughput Profiling of Protein Structural Changes in Alzheimer's Disease

High-throughput quantitative analysis of protein conformational changes has a profound impact on our understanding of the pathological mechanisms of Alzheimer's disease (AD). To establish an effective workflow enabling quantitative analysis of changes in protein conformation within multiple samples simultaneously, here we report the combination of N,N-dimethyl leucine (DiLeu) isobaric tag labeling with limited proteolysis mass spectrometry (DiLeu-LiP-MS) for high-throughput structural protein quantitation in serum samples collected from AD patients and control donors. Twenty-three proteins were discovered to undergo structural changes, mapping to 35 unique conformotypic peptides with significant changes between the AD group and the control group. Seven out of 23 proteins, including CO3, CO9, C4BPA, APOA1, APOA4, C1R, and APOA, exhibited a potential correlation with AD. Moreover, we found that complement proteins (e.g., CO3, CO9, and C4BPA) related to AD exhibited elevated levels in the AD group compared to those in the control group. These results provide evidence that the established DiLeu-LiP-MS method can be used for high-throughput structural protein quantitation, which also showed great potential in achieving large-scale and in-depth quantitative analysis of protein conformational changes in other biological systems.

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.