Global analysis of protein structural changes in complex proteomes

Proteomic insights into the extracellular matrix: a focus on proteoforms and their implications in health and disease

INTRODUCTION

The extracellular matrix (ECM) is a highly organized and dynamic network of proteins and glycosaminoglycans that provides critical structural, mechanical, and biochemical support to cells. The functions of the ECM are directly influenced by the conformation of the proteins that compose it. ECM proteoforms, which can result from genetic, transcriptional, and/or post-translational modifications, adopt different conformations and, consequently, confer different structural properties and functionalities to the ECM in both physiological and pathological contexts.

AREAS COVERED

In this review, we discuss how bottom-up proteomics has been applied to identify, map, and quantify post-translational modifications (e.g. additions of chemical groups, proteolytic cleavage, or cross-links) and ECM proteoforms arising from alternative splicing or genetic variants. We further illustrate how proteoform-level information can be leveraged to gain novel insights into ECM protein structure and ECM functions in health and disease.

EXPERT OPINION

In the Expert opinion section, we discuss remaining challenges and opportunities with an emphasis on the importance of devising experimental and computational methods tailored to account for the unique biochemical properties of ECM proteins with the goal of increasing sequence coverage and, hence, accurate ECM proteoform identification.

AI-empowered perturbation proteomics for complex biological systems

The insufficient availability of comprehensive protein-level perturbation data is impeding the widespread adoption of systems biology. In this perspective, we introduce the rationale, essentiality, and practicality of perturbation proteomics. Biological systems are perturbed with diverse biological, chemical, and/or physical factors, followed by proteomic measurements at various levels, including changes in protein expression and turnover, post-translational modifications, protein interactions, transport, and localization, along with phenotypic data. Computational models, employing traditional machine learning or deep learning, identify or predict perturbation responses, mechanisms of action, and protein functions, aiding in therapy selection, compound design, and efficient experiment design. We propose to outline a generic PMMP (perturbation, measurement, modeling to prediction) pipeline and build foundation models or other suitable mathematical models based on large-scale perturbation proteomic data. Finally, we contrast modeling between artificially and naturally perturbed systems and highlight the importance of perturbation proteomics for advancing our understanding and predictive modeling of biological systems.

Chemical proteomics accelerates the target discovery of natural products

More than half of the global novel drugs are directly or indirectly derived from natural products (NPs) because of their better selectivity towards proteins. Traditional medicines perform multiple bioactivities through various NPs binding to drug targets, which highlights the opportunities of target discovery for drug development. However, detecting the binding relationship between NPs and targets remains challenging. Chemical proteomics, an interdisciplinary field of chemistry, proteomics, biology, and bioinformatics, has emerged as a potential approach for uncovering drug-target interactions. This review summarizes the principles and characteristics of the current widely applied chemical proteomic technologies, while delving into their latest applications in the target discovery of natural medicine. These endeavours demonstrate the potential of chemical proteomics for target discovery to supply dependable methodologies for the target elucidation of NPs.

Real-Time Visualization of Protein Microenvironment Changes with High Spatial Resolution in Live Cells via Site-Specific Incorporation of Rotor-Based Fluorescent Noncanonical Amino Acids

Traditional methods, such as the use of fluorescent protein fusions and environment-sensitive fluorophores, have limitations when studying protein microenvironment changes at the finest spatial resolution. These techniques often rely on bulky proteins or tags restricted to the N- or C-terminus, which can disrupt the natural behavior of the target protein and dramatically limit the ability of their method to investigate noninvasively microenvironment effects. To overcome these challenges, we have developed an innovative strategy to visualize microenvironment changes of protein substructures in real-time by genetically incorporating environment-sensitive noncanonical amino acids (ncAAs) containing rotor-based fluorophores (RBFs) at specific positions within a protein of interest. Through computational redesign of aminoacyl-tRNA synthetase, we successfully incorporated these rotor-based ncAAs into various proteins in mammalian cells. By site-specifically placing these ncAAs in distinct regions of proteins, we detected microenvironmental changes of several different protein domains during events such as aggregation, clustering, aggregation disassembly, and cluster dissociation.

Global profiling of protein complex dynamics with an experimental library of protein interaction markers

Methods to systematically monitor protein complex dynamics are needed. We introduce serial ultrafiltration combined with limited proteolysis-coupled mass spectrometry (FLiP-MS), a structural proteomics workflow that generates a library of peptide markers specific to changes in PPIs by probing differences in protease susceptibility between complex-bound and monomeric forms of proteins. The library includes markers mapping to protein-binding interfaces and markers reporting on structural changes that accompany PPI changes. Integrating the marker library with LiP-MS data allows for global profiling of protein-protein interactions (PPIs) from unfractionated lysates. We apply FLiP-MS to Saccharomyces cerevisiae and probe changes in protein complex dynamics after DNA replication stress, identifying links between Spt-Ada-Gcn5 acetyltransferase activity and the assembly state of several complexes. FLiP-MS enables protein complex dynamics to be probed on any perturbation, proteome-wide, at high throughput, with peptide-level structural resolution and informing on occupancy of binding interfaces, thus providing both global and molecular views of a system under study.

Protein surface chemistry encodes an adaptive tolerance to desiccation

Cellular desiccation - the loss of nearly all water from the cell - is a recurring stress in an increasing number of ecosystems that can drive protein unfolding and aggregation. For cells to survive, at least some of the proteome must resume function upon rehydration. Which proteins tolerate desiccation, and the molecular determinants that underlie this tolerance, are largely unknown. Here, we apply quantitative and structural proteomic mass spectrometry to show that certain proteins possess an innate capacity to tolerate rehydration following extreme water loss. Structural analysis points to protein surface chemistry as a key determinant for desiccation tolerance, which we test by showing that rational surface mutants can convert a desiccation sensitive protein into a tolerant one. Desiccation tolerance also has strong overlap with cellular function, with highly tolerant proteins responsible for production of small molecule building blocks, and intolerant proteins involved in energy-consuming processes such as ribosome biogenesis. As a result, the rehydrated proteome is preferentially enriched with metabolite and small molecule producers and depleted of some of the cell's heaviest consumers. We propose this functional bias enables cells to kickstart their metabolism and promote cell survival following desiccation and rehydration.

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.

Cognition-Associated Protein Structural Changes in a Rat Model of Aging are Related to Reduced Refolding Capacity

Cognitive decline during aging represents a major societal burden, causing both personal and economic hardship in an increasingly aging population. There are a few well-known proteins that can misfold and aggregate in an age-dependent manner, such as amyloid β and α-synuclein. However, many studies have found that the proteostasis network, which functions to keep proteins properly folded, is impaired with age, suggesting that there may be many more proteins that incur structural alterations with age. Here, we used limited-proteolysis mass spectrometry (LiP-MS), a structural proteomic method, to globally interrogate protein conformational changes in a rat model of cognitive aging. Specifically, we compared soluble hippocampal proteins from aged rats with preserved cognition to those from aged rats with impaired cognition. We identified several hundred proteins as having undergone cognition-associated structural changes (CASCs). We report that CASC proteins are substantially more likely to be nonrefoldable than non-CASC proteins, meaning they typically cannot spontaneously refold to their native conformations after being chemically denatured. The potentially cofounding variable of post-translational modifications is systematically addressed, and we find that oxidation and phosphorylation cannot significantly explain the limited proteolysis signal. These findings suggest that noncovalent, conformational alterations may be general features in cognitive decline, and more broadly, that proteins need not form amyloids for their misfolded states to be relevant to age-related deterioration in cognitive abilities.

Mass Spectrometry Structural Proteomics Enabled by Limited Proteolysis and Cross-Linking

The exploration of protein structure and function stands at the forefront of life science and represents an ever-expanding focus in the development of proteomics. As mass spectrometry (MS) offers readout of protein conformational changes at both the protein and peptide levels, MS-based structural proteomics is making significant strides in the realms of structural and molecular biology, complementing traditional structural biology techniques. This review focuses on two powerful MS-based techniques for peptide-level readout, namely limited proteolysis-mass spectrometry (LiP-MS) and cross-linking mass spectrometry (XL-MS). First, we discuss the principles, features, and different workflows of these two methods. Subsequently, we delve into the bioinformatics strategies and software tools used for interpreting data associated with these protein conformation readouts and how the data can be integrated with other computational tools. Furthermore, we provide a comprehensive summary of the noteworthy applications of LiP-MS and XL-MS in diverse areas including neurodegenerative diseases, interactome studies, membrane proteins, and artificial intelligence-based structural analysis. Finally, we discuss the factors that modulate protein conformational changes. We also highlight the remaining challenges in understanding the intricacies of protein conformational changes by LiP-MS and XL-MS technologies.

The ASC inflammasome adapter governs SAA-derived protein aggregation in inflammatory amyloidosis

Extracellularly released molecular inflammasome assemblies -ASC specks- cross-seed Aβ amyloid in Alzheimer's disease. Here we show that ASC governs the extent of inflammation-induced amyloid A (AA) amyloidosis, a systemic disease caused by the aggregation and peripheral deposition of the acute-phase reactant serum amyloid A (SAA) in chronic inflammatory conditions. Using super-resolution microscopy, we found that ASC colocalized tightly with SAA in human AA amyloidosis. Recombinant ASC specks accelerated SAA fibril formation and mass spectrometry after limited proteolysis showed that ASC interacts with SAA via its pyrin domain (PYD). In a murine model of inflammatory AA amyloidosis, splenic amyloid load was conspicuously decreased in Pycard-/- mice which lack ASC. Treatment with anti-ASCPYD antibodies decreased amyloid loads in wild-type mice suffering from AA amyloidosis. The prevalence of natural anti-ASC IgG (-logEC50 ≥ 2) in 19,334 hospital patients was <0.01%, suggesting that anti-ASC antibody treatment modalities would not be confounded by natural autoimmunity. These findings expand the role played by ASC and IL-1 independent inflammasome employments to extraneural proteinopathies and suggest that anti-ASC immunotherapy may contribute to resolving such diseases.

PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications

Protein language models (PLMs) play a dominant role in protein representation learning. Most existing PLMs regard proteins as sequences of 20 natural amino acids. The problem with this representation method is that it simply divides the protein sequence into sequences of individual amino acids, ignoring the fact that certain residues often occur together. Therefore, it is inappropriate to view amino acids as isolated tokens. Instead, the PLMs should recognize the frequently occurring combinations of amino acids as a single token. In this study, we use the byte-pair-encoding algorithm and unigram to construct advanced residue vocabularies for protein sequence tokenization, and we have shown that PLMs pre-trained using these advanced vocabularies exhibit superior performance on downstream tasks when compared to those trained with simple vocabularies. Furthermore, we introduce PETA, a comprehensive benchmark for systematically evaluating PLMs. We find that vocabularies comprising 50 and 200 elements achieve optimal performance. Our code, model weights, and datasets are available at https://github.com/ginnm/ProteinPretraining . SCIENTIFIC CONTRIBUTION: This study introduces advanced protein sequence tokenization analysis, leveraging the byte-pair-encoding algorithm and unigram. By recognizing frequently occurring combinations of amino acids as single tokens, our proposed method enhances the performance of PLMs on downstream tasks. Additionally, we present PETA, a new comprehensive benchmark for the systematic evaluation of PLMs, demonstrating that vocabularies of 50 and 200 elements offer optimal performance.

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.

Improved drug target deconvolution with PISA-DIA using an extended, overlapping temperature gradient

Thermal proteome profiling (TPP) is a powerful tool for drug target deconvolution. Recently, data-independent acquisition mass spectrometry (DIA-MS) approaches have demonstrated significant improvements to depth and missingness in proteome data, but traditional TPP (a.k.a. CEllular Thermal Shift Assay "CETSA") workflows typically employ multiplexing reagents reliant on data-dependent acquisition (DDA). Herein, we introduce a new experimental design for the Proteome Integral Solubility Alteration via label-free DIA approach (PISA-DIA). We highlight the proteome coverage and sensitivity achieved by using multiple overlapping thermal gradients alongside DIA-MS, which maximizes efficiencies in PISA sample concatenation and safeguards against missing protein targets that exist at high melting temperatures. We demonstrate our extended PISA-DIA design has superior proteome coverage as compared to using tandem-mass tags (TMT) necessitating DDA-MS analysis. Importantly, we demonstrate our PISA-DIA approach has the quantitative and statistical rigor using A-1331852, a specific inhibitor of BCL-xL. Due to the high melt temperature of this protein target, we utilized our extended multiple gradient PISA-DIA workflow to identify BCL-xL. We assert our novel overlapping gradient PISA-DIA-MS approach is ideal for unbiased drug target deconvolution, spanning a large temperature range whilst minimizing target dropout between gradients, increasing the likelihood of resolving the protein targets of novel compounds.

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.

The role of Nα-terminal acetylation in protein conformation

Especially in higher eukaryotes, the N termini of proteins are subject to enzymatic modifications, with the acetylation of the alpha-amino group of nascent polypeptides being a prominent one. In recent years, the specificities and substrates of the enzymes responsible for this modification, the Nα-terminal acetyltransferases, have been mapped in several proteomic studies. Aberrant expression of, and mutations in these enzymes were found to be associated with several human diseases, explaining the growing interest in protein Nα-terminal acetylation. With some enzymes, such as the Nα-terminal acetyltransferase A complex having thousands of possible substrates, researchers are now trying to decipher the functional outcome of Nα-terminal protein acetylation. In this review, we zoom in on one possible functional consequence of Nα-terminal protein acetylation; its effect on protein folding. Using selected examples of proteins associated with human diseases such as alpha-synuclein and huntingtin, here, we discuss the sometimes contradictory findings of the effects of Nα-terminal protein acetylation on protein (mis)folding and aggregation.

Systematic identification of structure-specific protein-protein interactions

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

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.

Fatty Acid Synthase as Interacting Anticancer Target of the Terpenoid Myrianthic Acid Disclosed by MS-Based Proteomics Approaches

This research focuses on the target deconvolution of the natural compound myrianthic acid, a triterpenoid characterized by an ursane skeleton isolated from the roots of Myrianthus arboreus and from Oenothera maritima Nutt. (Onagraceae), using MS-based chemical proteomic techniques. Application of drug affinity responsive target stability (DARTS) and targeted-limited proteolysis coupled to mass spectrometry (t-LiP-MS) led to the identification of the enzyme fatty acid synthase (FAS) as an interesting macromolecular counterpart of myrianthic acid. This result, confirmed by comparison with the natural ursolic acid, was thoroughly investigated and validated in silico by molecular docking, which gave a precise picture of the interactions in the MA/FAS complex. Moreover, biological assays showcased the inhibitory activity of myrianthic acid against the FAS enzyme, most likely related to its antiproliferative activity towards tumor cells. Given the significance of FAS in specific pathologies, especially cancer, the myrianthic acid structural moieties could serve as a promising reference point to start the potential development of innovative approaches in therapy.

Cobalamins Function as Allosteric Activators of an Angelman Syndrome-Associated UBE3A/E6AP Variant

Genetic aberrations of the maternal UBE3A allele, which encodes the E3 ubiquitin ligase E6AP, are the cause of Angelman syndrome (AS), an imprinting disorder. In most cases, the maternal UBE3A allele is not expressed. Yet, approximately 10 percent of AS individuals harbor distinct point mutations in the maternal allele resulting in the expression of full-length E6AP variants that frequently display compromised ligase activity. In a high-throughput screen, we identified cyanocobalamin, a vitamin B12-derivative, and several alloxazine derivatives as activators of the AS-linked E6AP-F583S variant. Furthermore, we show by cross-linking coupled to mass spectrometry that cobalamins affect the structural dynamics of E6AP-F583S and apply limited proteolysis coupled to mass spectrometry to obtain information about the regions of E6AP that are involved in, or are affected by binding cobalamins and alloxazine derivatives. Our data suggest that dietary supplementation with vitamin B12 can be beneficial for AS individuals.

Poly-pharmacology of existing drugs: How to crack the code?

Drug development in oncology is highly challenging, with less than 5% success rate in clinical trials. This alarming figure points out the need to study in more details the multiple biological effects of drugs in specific contexts. Indeed, the comprehensive assessment of drug poly-pharmacology can provide insights into their therapeutic and adverse effects, to optimize their utilization and maximize the success rate of clinical trials. Recent technological advances have made possible in-depth investigation of drug poly-pharmacology. This review first highlights high-throughput methodologies that have been used to unveil new mechanisms of action of existing drugs. Then, we discuss how emerging chemo-proteomics strategies allow effectively dissecting the poly-pharmacology of drugs in an unsupervised manner.

Integrated Proteomics Characterization of NLRP3 Inflammasome Inhibitor MCC950 in Monocytic Cell Line Confirms Direct MCC950 Engagement with Endogenous NLRP3

Inhibition of the NLRP3 inflammasome is a promising strategy for the development of new treatments for inflammatory diseases. MCC950 is a potent and selective small-molecule inhibitor of the NLRP3 pathway and has been validated in numerous species and disease models. Although the capacity of MCC950 to block NLRP3 signaling is well-established, it is still critical to identify the mechanism of action and molecular targets of MCC950 to inform and derisk drug development. Quantitative proteomics performed in disease-relevant systems provides a powerful method to study both direct and indirect pharmacological responses to small molecules to elucidate the mechanism of action and confirm target engagement. A comprehensive target deconvolution campaign requires the use of complementary chemical biology techniques. Here we applied two orthogonal chemical biology techniques: compressed Cellular Thermal Shift Assay (CETSA) and photoaffinity labeling chemoproteomics, performed under biologically relevant conditions with LPS-primed THP-1 cells, thereby deconvoluting, for the first time, the molecular targets of MCC950 using chemical biology techniques. In-cell chemoproteomics with inlysate CETSA confirmed the suspected mechanism as the disruption of inflammasome formation via NLRP3. Further cCETSA (c indicates compressed) in live cells mapped the stabilization of NLRP3 inflammasome pathway proteins, highlighting modulation of the targeted pathway. This is the first evidence of direct MCC950 engagement with endogenous NLRP3 in a human macrophage cellular system using discovery proteomics chemical biology techniques, providing critical information for inflammasome studies.

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.

Systematic identification of 20S proteasome substrates

For years, proteasomal degradation was predominantly attributed to the ubiquitin-26S proteasome pathway. However, it is now evident that the core 20S proteasome can independently target proteins for degradation. With approximately half of the cellular proteasomes comprising free 20S complexes, this degradation mechanism is not rare. Identifying 20S-specific substrates is challenging due to the dual-targeting of some proteins to either 20S or 26S proteasomes and the non-specificity of proteasome inhibitors. Consequently, knowledge of 20S proteasome substrates relies on limited hypothesis-driven studies. To comprehensively explore 20S proteasome substrates, we employed advanced mass spectrometry, along with biochemical and cellular analyses. This systematic approach revealed hundreds of 20S proteasome substrates, including proteins undergoing specific N- or C-terminal cleavage, possibly for regulation. Notably, these substrates were enriched in RNA- and DNA-binding proteins with intrinsically disordered regions, often found in the nucleus and stress granules. Under cellular stress, we observed reduced proteolytic activity in oxidized proteasomes, with oxidized protein substrates exhibiting higher structural disorder compared to unmodified proteins. Overall, our study illuminates the nature of 20S substrates, offering crucial insights into 20S proteasome biology.

Widespread alteration of protein autoinhibition in human cancers

Autoinhibition is a prevalent allosteric regulatory mechanism in signaling proteins. Reduced autoinhibition underlies the tumorigenic effect of some known cancer drivers, but whether autoinhibition is altered generally in cancer remains elusive. Here, we demonstrate that cancer-associated missense mutations, in-frame insertions/deletions, and fusion breakpoints are enriched within inhibitory allosteric switches (IASs) across all cancer types. Selection for IASs that are recurrently mutated in cancers identifies established and unknown cancer drivers. Recurrent missense mutations in IASs of these drivers are associated with distinct, cancer-specific changes in molecular signaling. For the specific case of PPP3CA, the catalytic subunit of calcineurin, we provide insights into the molecular mechanisms of altered autoinhibition by cancer mutations using biomolecular simulations, and demonstrate that such mutations are associated with transcriptome changes consistent with increased calcineurin signaling. Our integrative study shows that autoinhibition-modulating genetic alterations are positively selected for by cancer cells.

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.

Chemoproteomics, A Broad Avenue to Target Deconvolution

As a vital project of forward chemical genetic research, target deconvolution aims to identify the molecular targets of an active hit compound. Chemoproteomics, either with chemical probe-facilitated target enrichment or probe-free, provides a straightforward and effective approach to profile the target landscape and unravel the mechanisms of action. Canonical methods rely on chemical probes to enable target engagement, enrichment, and identification, whereas click chemistry and photoaffinity labeling techniques improve the efficiency, sensitivity, and spatial accuracy of target recognition. In comparison, recently developed probe-free methods detect protein-ligand interactions without the need to modify the ligand molecule. This review provides a comprehensive overview of different approaches and recent advancements for target identification and highlights the significance of chemoproteomics in investigating biological processes and advancing drug discovery processes.

Identification of Mortalin as the Main Interactor of Mycalin A, a Poly-Brominated C-15 Acetogenin Sponge Metabolite, by MS-Based Proteomics

Mycalin A (MA) is a polybrominated C-15 acetogenin isolated from the marine sponge Mycale rotalis. Since this substance displays a strong antiproliferative bioactivity towards some tumour cells, we have now directed our studies towards the elucidation of the MA interactome through functional proteomic approaches, (DARTS and t-LIP-MS). DARTS experiments were performed on Hela cell lysates with the purpose of identifying MA main target protein(s); t-LiP-MS was then applied for an in-depth investigation of the MA-target protein interaction. Both these techniques exploit limited proteolysis coupled with MS analysis. To corroborate LiP data, molecular docking studies were performed on the complexes. Finally, biological and SPR analysis were conducted to explore the effect of the binding. Mortalin (GRP75) was identified as the MA's main interactor. This protein belongs to the Hsp70 family and has garnered significant attention due to its involvement in certain forms of cancer. Specifically, its overexpression in cancer cells appears to hinder the pro-apoptotic function of p53, one of its client proteins, because it becomes sequestered in the cytoplasm. Our research, therefore, has been focused on the possibility that MA might prevent this sequestration, promoting the re-localization of p53 to the nucleus and facilitating the apoptosis of tumor cells.

Ligand Modification-Free Methods for the Profiling of Protein-Environmental Chemical Interactions

Adverse health outcomes caused by environmental chemicals are often initiated via their interactions with proteins. Essentially, one environmental chemical may interact with a number of proteins and/or a protein may interact with a multitude of environmental chemicals, forming an intricate interaction network. Omics-wide protein-environmental chemical interaction profiling (PECI) is of prominent importance for comprehensive understanding of these interaction networks, including the toxicity mechanisms of action (MoA), and for providing systematic chemical safety assessment. However, such information remains unknown for most environmental chemicals, partly due to their vast chemical diversity. In recent years, with the continuous efforts afforded, especially in mass spectrometry (MS) based omics technologies, several ligand modification-free methods have been developed, and new attention for systematic PECI profiling was gained. In this Review, we provide a comprehensive overview on these methodologies for the identification of ligand-protein interactions, including affinity interaction-based methods of affinity-driven purification, covalent modification profiling, and activity-based protein profiling (ABPP) in a competitive mode, physicochemical property changes assessment methods of ligand-directed nuclear magnetic resonance (ligand-directed NMR), MS integrated with equilibrium dialysis for the discovery of allostery systematically (MIDAS), thermal proteome profiling (TPP), limited proteolysis-coupled mass spectrometry (LiP-MS), stability of proteins from rates of oxidation (SPROX), and several intracellular downstream response characterization methods. We expect that the applications of these ligand modification-free technologies will drive a considerable increase in the number of PECI identified, facilitate unveiling the toxicological mechanisms, and ultimately contribute to systematic health risk assessment of environmental chemicals.

A label free chemoproteomic-based platform to disclose cannabidiol molecular mechanism of action on chronic myelogenous leukemia cancer cells

The discovery of the interactome of cannabidiol (CBD), a non-psychoactive cannabinoid from Cannabis sativa L., has been here performed on chronic myelogenous leukemia cancer cells, using an optimized chemo-proteomic stage, which links Drug Affinity Responsive Target Stability with Limited Proteolysis Multiple Reaction Monitoring approaches. The obtained results showed the ability of CBD to target simultaneously some potential protein partners, corroborating its well-known poly-pharmacology activity. In human chronic myelogenous leukemia K562 cancer cells, the most fascinating protein partner was identified as the 116 kDa U5 small nuclear ribonucleoprotein element called EFTUD2, which fits with the spliceosome complex. The binding mode of this oncogenic protein with CBD was clarified using mass spectrometry-based and in silico analysis.

Chemoproteomics Reveals USP5 (Ubiquitin Carboxyl-Terminal Hydrolase 5) as Promising Target of the Marine Polyketide Gracilioether A

Mass spectrometry-based chemical proteomic approaches using limited proteolysis have become a powerful tool for the identification and analysis of the interactions between a small molecule (SM) and its protein target(s). Gracilioether A (GeA) is a polyketide isolated from a marine sponge, for which we aimed to trace the interactome using this strategy. DARTS (Drug Affinity Responsive Target Stability) and t-LiP-MS (targeted-Limited Proteolysis-Mass Spectrometry) represented the main techniques used in this study. DARTS was applied on HeLa cell lysate for the identification of the GeA target proteins, and t-LiP-MS was employed to investigate the protein's regions involved in the binding with GeA. The results were complemented through the use of binding studies using Surface Plasmon Resonance (SPR) and in silico molecular docking experiments. Ubiquitin carboxyl-terminal hydrolase 5 (USP5) was identified as a promising target of GeA, and the interaction profile of the USP5-GeA complex was explained. USP5 is an enzyme involved in the pathway of protein metabolism through the disassembly of the polyubiquitin chains on degraded proteins into ubiquitin monomers. This activity is connected to different cellular functions concerning the maintenance of chromatin structure and receptors and the degradation of abnormal proteins and cancerogenic progression. On this basis, this structural information opens the way to following studies focused on the definition of the biological potential of Gracilioether A and the rational development of novel USP5 inhibitors based on a new structural skeleton.

Elovanoid-N34 modulates TXNRD1 key in protection against oxidative stress-related diseases

The thioredoxin (TXN) system is an NADPH + H+/FAD redox-triggered effector that sustains homeostasis, bioenergetics, detoxifying drug networks, and cell survival in oxidative stress-related diseases. Elovanoid (ELV)-N34 is an endogenously formed lipid mediator in neural cells from omega-3 fatty acid precursors that modulate neuroinflammation and senescence gene programming when reduction-oxidation (redox) homeostasis is disrupted, enhancing cell survival. Limited proteolysis (LiP) screening of human retinal pigment epithelial (RPE) cells identified TXNRD1 isoforms 2, 3, or 5, the reductase of the TXN system, as an intracellular target of ELV-N34. TXNRD1 silencing confirmed that the ELV-N34 target was isoform 2 or 3. This lipid mediator induces TXNRD1 structure changes that modify the FAD interface domain, leading to its activity modulation. The addition of ELV-N34 decreased membrane and cytosolic TXNRD1 activity, suggesting localizations for the targeted reductase. These results show for the first time that the lipid mediator ELV-N34 directly modulates TXNRD1 activity, underling its protection in several pathologies when uncompensated oxidative stress (UOS) evolves.

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.

Identification of α-amanitin effector proteins in hepatocytes by limited proteolysis-coupled mass spectrometry

The misuse of poisonous mushrooms containing amatoxins causes acute liver failure (ALF) in patients and is a cause of significant mortality. Although the toxic mechanisms of α-amanitin (α-AMA) and its interactions with RNA polymerase II (RNAP II) have been studied, α-AMA effector proteins that can interact with α-AMA in hepatocytes have not been systematically studied. Limited proteolysis-coupled mass spectrometry (LiP-MS) is an advanced technology that can quickly identify protein-ligand interactions based on global comparative proteomics. This study identified the α-AMA effector proteins found in human hepatocytes, following the detection of conformotypic peptides using LiP-MS coupled with tandem mass tag (TMT) technology. Proteins that are classified into protein processing in the endoplasmic reticulum and the ribosome during the KEGG pathway can be identified through affinity evaluation, according to α-AMA concentration-dependent LiP-MS and LiP-MS in hepatocytes derived from humans and mice, respectively. The possibility of interaction between α-AMA and proteins containing conformotypic peptides was evaluated through molecular docking studies. The results of this study suggest a novel path for α-AMA to induce hepatotoxicity through interactions with various proteins involved in protein synthesis, as well as with RNAP II.

Chemoproteomic mapping of the glycolytic targetome in cancer cells

Hyperactivated glycolysis is a metabolic hallmark of most cancer cells. Although sporadic information has revealed that glycolytic metabolites possess nonmetabolic functions as signaling molecules, how these metabolites interact with and functionally regulate their binding targets remains largely elusive. Here, we introduce a target-responsive accessibility profiling (TRAP) approach that measures changes in ligand binding-induced accessibility for target identification by globally labeling reactive proteinaceous lysines. With TRAP, we mapped 913 responsive target candidates and 2,487 interactions for 10 major glycolytic metabolites in a model cancer cell line. The wide targetome depicted by TRAP unveils diverse regulatory modalities of glycolytic metabolites, and these modalities involve direct perturbation of enzymes in carbohydrate metabolism, intervention of an orphan transcriptional protein's activity and modulation of targetome-level acetylation. These results further our knowledge of how glycolysis orchestrates signaling pathways in cancer cells to support their survival, and inspire exploitation of the glycolytic targetome for cancer therapy.

Target deconvolution with matrix-augmented pooling strategy reveals cell-specific drug-protein interactions

Target deconvolution is a crucial but costly and time-consuming task that hinders large-scale profiling for drug discovery. We present a matrix-augmented pooling strategy (MAPS) which mixes multiple drugs into samples with optimized permutation and delineates targets of each drug simultaneously with mathematical processing. We validated this strategy with thermal proteome profiling (TPP) testing of 15 drugs concurrently, increasing experimental throughput by 60x while maintaining high sensitivity and specificity. Benefiting from the lower cost and higher throughput of MAPS, we performed target deconvolution of the 15 drugs across 5 cell lines. Our profiling revealed that drug-target interactions can differ vastly in targets and binding affinity across cell lines. We further validated BRAF and CSNK2A2 as potential off-targets of bafetinib and abemaciclib, respectively. This work represents the largest thermal profiling of structurally diverse drugs across multiple cell lines to date.

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.

Molecular Evidence of Structural Changes in Silk Using Unlimited Degradation Mass Spectrometry

Proteomics has important uses in archeological science because it can distinguish species, reveal the evolution of paleontology, and provide biological evidence of historical events. However, this technique still has full potential in the study of silk aging mechanisms. In this work, we propose a strategy combining unlimited degradation with mass-spectrometry-based proteomics techniques, which interpret protein fragmentation propensity and secondary structure changes by detecting content changes of specific peptide groups in complex proteomes. This approach was employed to study the conformational changes in silk microscopic crystals after heat treatment. Combining conventional mechanics and crystallographic characterization, a thermal aging degradation mechanism model was proposed. At the same time, it explained the interesting problem that the crystallinity remained unchanged, but the mechanical properties decreased significantly. Focusing on the unlimited degradation process, this method will be widely applicable to the study of silk and wool aging processes and regenerated silk fibroin.

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

Targeting phosphoglycerate kinases by tatridin A, a natural sesquiterpenoid endowed with anti-cancer activity, using a proteomic platform

Tatridin A (TatA) is a germacrane sesquiterpenoid containing one E-double bond and one Z-double bond in its 10-membered ring, which is fused to a 3-methylene-dihydrofuran-2-one moiety. Tatridin A bioactivity has been poorly investigated despite its interesting chemical structure. Here, a functional proteomic platform was adapted to disclose its most reliable targets in leukemia monocytic cells, and phosphoglycerate kinases were recognized as the most affine enzymes. Through a combination of limited proteolysis and molecular docking, it has been discovered that tatridin A interacts with the active domains of phosphoglycerate kinase 1, altering its hinge region, and it can be accountable for tatridin A inhibition potency on enzyme activity. A more detailed tatridin A biological profile showed that it is also fully active against gastric cancer cells, downregulating the mRNA levels of chemokine receptor 4 and β-catenin and inhibiting the invasiveness of living KATO III cells as a direct consequence of phosphoglycerate kinase 1 antagonism.

Small-molecule probes from bench to bedside: advancing molecular analysis of drug-target interactions toward precision medicine

Over the past decade, remarkable advances have been witnessed in the development of small-molecule probes. These molecular tools have been widely applied for interrogating proteins, pathways and drug-target interactions in preclinical research. While novel structures and designs are commonly explored in probe development, the clinical translation of small-molecule probes remains limited, primarily due to safety and regulatory considerations. Recent synergistic developments - interfacing novel chemical probes with complementary analytical technologies - have introduced and expedited diverse biomedical opportunities to molecularly characterize targeted drug interactions directly in the human body or through accessible clinical specimens (e.g., blood and ascites fluid). These integrated developments thus offer unprecedented opportunities for drug development, disease diagnostics and treatment monitoring. In this review, we discuss recent advances in the structure and design of small-molecule probes with novel functionalities and the integrated development with imaging, proteomics and other emerging technologies. We further highlight recent applications of integrated small-molecule technologies for the molecular analysis of drug-target interactions, including translational applications and emerging opportunities for whole-body imaging, tissue-based measurement and blood-based analysis.

Molecular mechanisms of snoRNA-IL-15 crosstalk in adipocyte lipolysis and NK cell rejuvenation

Obesity, in which the functional importance of small nucleolar RNAs (snoRNAs) remains elusive, correlates with risk for many cancer types. Here, we identify that the serum copies of adipocyte-expressed SNORD46 correlate with body mass index (BMI), and serum SNORD46 antagonizes interleukin-15 (IL-15) signaling. Mechanically, SNORD46 binds IL-15 via G11, and G11A (a mutation that significantly enhances binding affinity) knockin drives obesity in mice. Functionally, SNORD46 blocks IL-15-induced, FER kinase-dependent phosphorylation of platelet glycoprotein 4 (CD36) and monoglyceride lipase (MGLL) in adipocytes, leading to inhibited lipolysis and browning. In natural killer (NK) cells, SNORD46 suppresses the IL-15-dependent autophagy, leading to reduced viability of obese NK. SNORD46 power inhibitors exhibit anti-obesity effects, concurring with improved viability of obese NK and anti-tumor immunity of CAR-NK cell therapy. Hence, our findings demonstrate the functional importance of snoRNAs in obesity and the utility of snoRNA power inhibitors for antagonizing obesity-associated immune resistance.

Visualizing everything, everywhere, all at once: Cryo-EM and the new field of structureomics

Twenty years ago, the release of the first draft of the human genome sequence instigated a paradigm shift in genomics and molecular biology. Arguably, structural biology is entering an analogous era, with availability of an experimentally determined or predicted molecular model for almost every protein-coding gene from many genomes-producing a reference "structureome". Structural predictions require experimental validation and not all proteins conform to a single structure, making any reference structureome necessarily incomplete. Despite these limitations, a reference structureome can be used to characterize cell state in more detail than by quantifying sequence or expression levels alone. Cryogenic electron microscopy (cryo-EM) is a method that can generate atomic resolution views of molecules and cells frozen in place. In this perspective I consider how emerging cryo-EM methods are contributing to the new field of structureomics.

Cellular Exposure to Chloroacetanilide Herbicides Induces Distinct Protein Destabilization Profiles

Herbicides in the widely used chloroacetanilide class harbor a potent electrophilic moiety, which can damage proteins through nucleophilic substitution. In general, damaged proteins are subject to misfolding. Accumulation of misfolded proteins compromises cellular integrity by disrupting cellular proteostasis networks, which can further destabilize the cellular proteome. While direct conjugation targets can be discovered through affinity-based protein profiling, there are few approaches to probe how cellular exposure to toxicants impacts the stability of the proteome. We apply a quantitative proteomics methodology to identify chloroacetanilide-destabilized proteins in HEK293T cells based on their binding to the H31Q mutant of the human Hsp40 chaperone DNAJB8. We find that a brief cellular exposure to the chloroacetanilides acetochlor, alachlor, and propachlor induces misfolding of dozens of cellular proteins. These herbicides feature distinct but overlapping profiles of protein destabilization, highly concentrated in proteins with reactive cysteine residues. Consistent with the recent literature from the pharmacology field, reactivity is driven by neither inherent nucleophilic nor electrophilic reactivity but is idiosyncratic. We discover that propachlor induces a general increase in protein aggregation and selectively targets GAPDH and PARK7, leading to a decrease in their cellular activities. Hsp40 affinity profiling identifies a majority of propachlor targets identified by competitive activity-based protein profiling (ABPP), but ABPP can only identify about 10% of protein targets identified by Hsp40 affinity profiling. GAPDH is primarily modified by the direct conjugation of propachlor at a catalytic cysteine residue, leading to global destabilization of the protein. The Hsp40 affinity strategy is an effective technique to profile cellular proteins that are destabilized by cellular toxin exposure. Raw proteomics data is available through the PRIDE Archive at PXD030635.

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.

Protein Folding Stability Profiling of Colorectal Cancer Chemoresistance Identifies Functionally Relevant Biomarkers

Reported here is the application of three protein folding stability profiling techniques (including the stability of proteins from rates of oxidation, thermal protein profiling, and limited proteolysis approaches) to identify differentially stabilized proteins in six patient-derived colorectal cancer (CRC) cell lines with different oxaliplatin sensitivities and eight CRC patient-derived xenografts (PDXs) derived from two of the patient derived cell lines with different oxaliplatin sensitivities. Compared to conventional protein expression level analyses, which were also performed here, the stability profiling techniques identified both unique and novel proteins and cellular components that differentiated the sensitive and resistant samples including 36 proteins that were differentially stabilized in at least two techniques in both the cell line and PDX studies of oxaliplatin resistance. These 36 differentially stabilized proteins included 10 proteins previously connected to cancer chemoresistance. Two differentially stabilized proteins, fatty acid synthase and elongation factor 2, were functionally validated in vitro and found to be druggable protein targets with biological functions that can be modulated to improve the efficacy of CRC chemotherapy. These results add to our understanding of CRC oxaliplatin resistance, suggest biomarker candidates for predicting oxaliplatin sensitivity in CRC, and inform new strategies for overcoming chemoresistance in CRC.

Emerging maps of allosteric regulation in cellular networks

Allosteric regulation is classically defined as action at a distance, where a perturbation outside of a protein active site affects function. While this definition has motivated many studies of allosteric mechanisms at the level of protein structure, translating these insights to the allosteric regulation of entire cellular processes - and their crosstalk - has received less attention, despite the broad importance of allostery for cellular regulation foreseen by Jacob and Monod. Here, we revisit an evolutionary model for the widespread emergence of allosteric regulation in colocalized proteins, describe supporting evidence, and discuss emerging advances in mapping allostery in cellular networks that link precise and often allosteric perturbations at the molecular level to functional changes at the pathway and systems levels.

Targeting USP-7 by a Novel Fluorinated 5-Pyrazolyl-Urea Derivative

The impact of innovative technologies on the target discovery has been employed here to characterize the interactome of STIRUR 41, a promising 3-fluoro-phenyl-5-pyrazolyl-urea derivative endowed with anti-cancer activity, on neuroblastoma-related cells. A drug affinity responsive target stability-based proteomic platform has been optimized to elucidate the molecular mechanism at the basis of STIRUR 41 action, together with immunoblotting analysis and in silico molecular docking. Ubiquitin Specific Protease 7 (USP-7), one of the deubiquitinating enzymes which protect substrate proteins from proteasomal degradation, has been identified as the most affine STIRUR 41 target. As further demonstrated by in vitro and in-cell assays, STIRUR 41 was able to inhibit both the enzymatic activity of USP-7 and its expression levels in neuroblastoma-related cells, thus laying an encouraging base for the blockade of USP-7 downstream signaling.