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At least 19 recordsLinked to original sources

PubMed2024

Chemical proteomics to study metabolism, a reductionist approach applied at the systems level.

Cellular metabolism encompasses a complex array of interconnected biochemical pathways that are required for cellular homeostasis. When dysregulated, metabolism underlies multiple human pathologies. At the heart of metabolic networks are enzymes that have been historically studied through a reductionist lens, and more recently, using high throughput approaches including genomics and proteomics. Merging these two divergent viewpoints are chemical proteomic technologies, including activity-based protein profiling, which combines chemical probes specific to distinct enzyme families or amino acid residues with proteomic analysis. This enables the study of metabolism at the network level with the precision of powerful biochemical approaches. Herein, we provide a primer on how chemical proteomic technologies custom-built for studying metabolism have unearthed fundamental principles in metabolic control. In parallel, these technologies have leap-frogged drug discovery through identification of novel targets and drug specificity. Collectively, chemical proteomics technologies appear to do the impossible: uniting systematic analysis with a reductionist approach.

Humans↗

PubMed2026

3D Proteomics: Structural, Functional, Chemical and Biomarker Discovery Proteomics With LiP-MS.

Protein structural dynamics drive changes in protein function, making the capture of such dynamics essential for interrogating biological systems. Here we review limited proteolysis coupled to mass spectrometry (LiP-MS), a structural and chemical proteomics method that uses changes in susceptibility to protease cleavage to profile proteome-wide protein structural changes within complex biological samples. In the decade since its development, LiP-MS has become a broadly used structural proteomics method, with peptide-level resolution. It has identified drug targets, delineated altered cellular pathways in response to complex perturbations, revealed structural information on otherwise challenging protein targets, and demonstrated the new concept of structural biomarkers of disease. Because LiP-MS simultaneously probes numerous types of molecular events, such as molecular binding, changes in enzyme activity, chemical modifications, allosteric conformational changes, aggregation, and unfolding, it supports a new proteomics workflow which we term 3D proteomics. This workflow enables the detection of specific functional sites within proteins that are altered upon perturbation, thereby guiding the generation of molecular hypotheses. Further, by globally profiling structural in addition to protein abundance changes, LiP-MS has proven able to greatly increase the information content of functional proteomics screens. In sum, LiP-MS has supported the development of a novel conceptual framework for generating, visualizing, and interpreting structural proteomics data with peptide level resolution, thereby comprehensively probing biological systems. Here we survey the applications of LiP-MS, discuss methodological variants developed by us and others, and describe the use of this new type of omics readout for structural, functional, chemical, and biomarker discovery proteomics.

Proteomics↗

PubMed2025

Exploring the associations between preen oil bacterial, chemical and proteomic profiles of passerines.

Preen gland bacteria are thought to be the key producers of preen oil components such as chemosignalling molecules including volatile organic compounds (VOCs) and antimicrobial compounds including peptides and antimicrobial VOCs. However, data on the preen oil bacteriome and chemical composition are limited to a small subset of bird species, and the presence of antimicrobial peptides is largely unexplored. Here, we performed an exploratory study to characterize, for the first time, the preen oil chemical and proteomic profiles and to explore the possible contribution of the bacteriome to the production of preen oil VOCs and antimicrobial peptides (bacteriocins) in eight passerine species, each represented by a single individual. Preen oil bacteriome, chemical and proteomic profiles varied among birds. The bacterial profiles were dominated by the genera Streptococcus, Lactococcus, Corynebacterium and Cutibacterium. The chemical profiles mainly consisted of alcohols, ketones and carboxylic acids. The biological functions primarily associated with the proteomic profiles were proteolysis and response to oxidative stress. Although we were unable to explore a direct association between the bacteriome and chemical profiles, the preen oil contained bacteriocin- and VOC-producing bacterial genera capable of producing detected microbially-derived VOCs (mVOCs), the relative abundance of which varied between birds. Riparian species showed the highest chemical diversity and high abundances of putative preen oil mVOC-producing bacteria, which could suggest habitat-specific adaptations. This exploratory study may significantly contribute to the formulation of hypotheses on the potential role of host ecological factors in the variation of preen oil bacterial, chemical and proteomic profiles in passerines.

Animals↗

PubMed2026

Integrative proteomics reveals MSH6 to modulate PARP inhibitor sensitivity in BRCA1/2-proficient ovarian cancer.

Ovarian cancer remains a leading cause of gynecologic cancer-related deaths worldwide. Deficiencies in BRCA1/2 are well-established biomarkers that predict sensitivity to poly(ADP-ribose) polymerase inhibitors (PARPis). However, emerging evidence indicates that a subset of BRCA-proficient tumors also responds to PARPi therapy, suggesting the presence of additional molecular mechanisms. We hypothesized that the composition of the PARP1 protein complex and PARylation-mediated signaling contribute to PARPi response in BRCA-proficient HGSOC. We assessed PARPi response across a panel of BRCA-proficient ovarian cancer cell lines and identified distinct sensitive and resistant groups. Chemical proteomics with rucaparib revealed different PARP1 complexes including higher enrichment of MSH6 in sensitive cells. Co-immunoprecipitation analyses further confirmed differential assembly of PARP1-MSH6-PARP2 complexes between sensitive and resistant models. To explore PARylation signaling, we performed ADP-ribosylation proteomics using clickable NAD⁺ analogs, revealing distinct PARylation profiles between sensitive and resistant cell lines. CHAF1A, a known MSH6 interactor and PARP1 substrate, showed more pronounced reduction in ADP-ribosylation in PARPi-sensitive cells. Targeting MSH6 using CRISPR or siRNA decreased PARPi sensitivity. In addition, mTOR signaling was reduced in sensitive, but increased in resistant cells, following rucaparib treatment. Notably, MSH6 knockdown led to increased CHAF1A expression regardless of rucaparib treatment. Importantly, knockdown of CHAF1A significantly impaired cell viability, especially in A2780 cells, and suppressed mTOR signaling, suggesting that CHAF1A acts downstream of MSH6 to regulate the mTOR axis. Furthermore, co-treatment with mTORC1 inhibitors enhanced the cellular effects of rucaparib in resistant cells, suggesting a therapeutic potential of targeting downstream mTOR effectors to overcome intrinsic resistance. In conclusion, this study identifies the PARP1-MSH6 interaction to modulate PARPi sensitivity via CHAF1A-mTOR signaling in BRCA-proficient ovarian cancer. By integrating chemical proteomics and ADP-ribosylation proteomics, we delineate the interplay between PARP1 complex composition and signaling dynamics, highlighting MSH6 as a critical modulator of PARPi response and potential biomarker to enhance therapeutic efficacy in BRCA-proficient HGSOC.

Humans↗

PubMed2026

Redox-activated chemistry for probing and perturbing the proteome: Lessons from protein redox switches.

Covalent drug discovery and chemical proteomics have historically relied on a nucleophilic logic, where electrophilic "warheads" react with nucleophilic amino acid side chains. While powerful, this paradigm probes only a single dimension of the protein's chemical surface. In contrast, biology leverages a second axis: redox potential. This is exemplified by the regulated redox proteome, where specific residues undergo reversible oxidation and reduction as functional post-translational modifications. Inspired by this natural machinery, researchers are developing redox-activated probes to label proteins at oxidizable residues and deploying similar chemistry to selectively perturb protein function. This review highlights recent advances in redox-activated covalent chemistry and explores its burgeoning potential for the development of next-generation targeted therapeutics.

Oxidation-Reduction↗

PubMed2026

Mapping the covalent cysteine interactome of Ebselen reveals high-sensitivity target engagement and redox proteome remodeling.

Ebselen is a covalent organoselenium compound with broad pharmacological activity, yet its cellular cysteine targets and downstream proteomic consequences remain incompletely defined. Here, we integrated competitive gel-based activity-based protein profiling, reactivity-dependent tandem orthogonal proteolysis-activity-based protein profiling, and TMT-based quantitative proteomics to map Ebselen-induced cysteine engagement and proteome remodeling in living cancer cells. Ebselen exhibited dose-dependent cytotoxicity and markedly perturbed intracellular thiol-redox balance, as reflected by glutathione depletion and altered reactive oxygen species-associated fluorescence readouts. Competitive gel-based profiling confirmed concentration-dependent engagement of protein cysteine residues in live cells. Quantitative rdTOP-ABPP further identified hundreds of dose-responsive cysteine sites in HeLa and HepG2 cells and revealed a preference for cysteine microenvironments enriched with basic residues. Cross-cell-line comparison highlighted CDK5 Cys53, SMU1 Cys298, and RPSA2 Cys163 as conserved covalent nodes, among which CDK5 Cys53 showed high sensitivity to Ebselen treatment, a finding validated by competitive labeling and MS-based site assignment. Global TMT proteomics revealed extensive remodeling of redox-related and cell-survival-associated pathways, including compensatory upregulation of selenoproteins such as TXNRD1 and GPX family members. Together, these results define a chemical proteomic atlas of Ebselen-cysteine interactions and provide a framework for understanding and optimizing covalent organoselenium therapeutics.

Humans↗

PubMed2025

Decoding Arginine Dimethylation Isomers via pH-Tuned Reactivity with Methylglyoxal: A Chemical Approach for Functional Proteomics.

Arginine dimethylation, encompassing asymmetric and symmetric configurations, represents a fundamental post-translational modification. Despite sharing identical chemical formulas, the two arginine dimethylation isomers exhibit different or even opposite biological effects. Therefore, it is necessary to determine their specific structure before conducting a further biological investigation. However, current methods for arginine dimethylation analysis face great challenges in efficient isomer differentiation, preventing the functional investigation of arginine dimethylation. To overcome this obstacle, herein, we introduce a novel chemical strategy leveraging pH-tuned reactivity with methylglyoxal (MGO) to decode these dimethylation isomers. By utilizing molecular dynamics simulation analysis, we revealed the different chemical reactivities of asymmetrically and symmetrically dimethylated arginine when reacted with MGO at different pH conditions. This property enabled the development of a pH-tuned chemical strategy by combining the MGO reaction with boronate affinity enrichment to simultaneously enrich and differentiate the dimethylation isomers. This strategy can effectively distinguish dimethylated arginine isomers in complex cell samples, and the good feasibility of this strategy was verified by orthogonal validation with the neutral loss. Of the obtained data set, this strategy identified sDMA at R112 of SNRPN, which is confirmed to be modified by PRMT5. Further functional analysis reveals its crucial role in maintaining protein stability and in regulating spliceosome assembly. Overall, by transforming the inherent pH sensitivity of MGO reactions into a powerful analytical tool, our work establishes the first chemical platform for functional proteomic dissection of arginine dimethylation isomers, which paves the way for further regulating mechanism investigations of protein methylation.

Pyruvaldehyde↗

PubMed2026

Chemoproteomics Prioritizes Mitochondrial ADP/ATP Translocase as a Candidate Target Associated with 6PPDQ-Induced Respiratory Toxicity in Rainbow Trout Gill.

6PPD quinone (6PPDQ) is an emerging contaminant that induces acute respiratory toxicity in rainbow trout (Oncorhynchus mykiss), yet its underlying molecular mechanisms remain poorly understood. In the present study, short-term in vivo exposure of rainbow trout to 6PPDQ resulted in substantial accumulation and limited biotransformation of 6PPDQ in the gill, accompanied by pronounced gill structural damage and increased whole-fish oxygen consumption. Taking advantage of the electrophilic reactivity of the quinone moiety of 6PPDQ toward cysteine residues, we applied activity-based protein profiling (ABPP) to gill tissue. ABPP revealed marked alterations in mitochondrial cysteine reactivity and highlighted ADP/ATP translocase (ANT) as a candidate 6PPDQ-interacting mitochondrial protein. A Cys-160-containing ANT peptide within the nucleotide-binding domain of ANT was pinpointed as the covalent binding site through ABPP, Peptide-centric Local Stability Assay (PELSA), and molecular docking. Functional assays using isolated gill mitochondria showed that 6PPDQ elicited an uncoupling-like mitochondrial respiratory response that was partially attenuated by the ANT inhibitor carboxyatractyloside (CATR), supporting the functional involvement of ANT in this gill-based model. Together, these findings nominate ANT as a candidate gill mitochondrial target associated with 6PPDQ-induced acute respiratory toxicity and demonstrate the utility of chemoproteomics for prioritizing mechanistically relevant protein interactions of emerging pollutants.

Animals↗

PubMed2026

DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.

Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.

Humans↗

PubMed2026

Toxicoproteomic analysis reveals arsenic-induced alterations in eye lens proteins of Labeo rohita.

Arsenic occurs extensively in the environment and is classified as a potent carcinogenic substance in humans. Prolonged intake of water contaminated with arsenic results in the development of arsenicosis. In the present study, a toxicoproteomic approach was employed to elucidate arsenic-induced alterations in lens proteins using a fish model. Juveniles of Labeo rohita were exposed to sodium meta-arsenite (NaAsO2) at concentrations of 5, 10, 15, and 20 ppm for a period of 10 days in triplicate experimental groups. Soluble lens proteins were analyzed using one- and two-dimensional gel electrophoresis, immunoblotting of αA-crystallin and MALDI-TOF mass spectrometry. Cataract development was observed at arsenic concentrations ≥ 15 ppm. Proteomic analyses revealed concentration-dependent alterations in lens protein abundance, including significant reductions in βB1, βB2, and βA2b-crystallin, small heat shock protein and skeletal α-actin (p < 0.05). In addition, αA, βA2, and βA2a-crystallin exhibited reduced abundance trends, although these changes were not statistically significant. Two-dimensional immunoblotting revealed 15 distinct αA-crystallin isoforms in control lenses, several of which showed a progressive decrease with increasing arsenic exposure, culminating in complete degradation at 20 ppm. These findings demonstrate that arsenic exposure is associated with substantial alterations in lens crystallins and other proteins involved in structural organization and protein homeostasis, coinciding with cataract development at higher exposure concentrations. The identified proteins may serve as potential toxicoproteomic biomarkers of lens damage in aquatic organisms and provide a foundation for future studies investigating the molecular mechanisms of arsenic-induced lens toxicity.

Animals↗

PubMed2026

From molecular responses to environmental monitoring: advances and translational gaps in omics approaches in fish environmental toxicology.

Fish occupy a central position in aquatic ecosystems and serve as important bioindicators for environmental monitoring, as well as powerful translational models for understanding toxic mechanisms conserved across higher vertebrates. In recent years, omics techniques have proven to be powerful tools to address complex environmental questions that conventional toxicology methods cannot answer. Despite this potential, a critical translational gap remains between molecular findings and their use in ecological risk assessment frameworks. This review critically synthesizes advances across omics techniques including epigenomics, transcriptomics, metabolomics and proteomics and their integration. Special emphasis is placed on methodological considerations and practical aspects of these techniques in fish environmental toxicology and environmental monitoring. Evidence from single-omics studies suggests conserved biomarker signatures across species while characterizing complex phenomena like non-monotonic dose-response relationships, mixture toxicity and transgenerational and stereoselective effects with implications for population level monitoring. Multi-omics studies, especially those involving triple omics, further enhance mechanistic resolution by reconstructing adverse outcome pathways. We further evaluate using case studies when additional molecular layers provide critical insight and when they offer limited advantage, a strategic distinction with direct implications in environmental monitoring programmes. Finally, current limitations and future directions that will ultimately bridge the translational gap and hold promise for advancing mechanistic ecotoxicology and predictive environmental monitoring are discussed.

Animals↗

PubMed2025

Phenomics-Based Discovery of Novel Orthosteric Choline Kinase Inhibitors.

Choline kinase alpha (CHKA) is a central mediator of cell metabolism linked to cancer and immune regulation. Cellular and clinical evaluation of CHKA has been hampered by challenges in the development of drug-like choline kinase inhibitors. Here, we identify CHKA as an unexpected off-target of histone methyltransferase inhibitors using an integrated phenomic approach. We confirm CHKA as a direct protein target of the aminoquinazolines UNC0638 and UNC0737 using a combination of chemoproteomic, biochemical, cellular, and metabolic profiling assays, possibly explaining the previously reported discrepancies observed for different G9a/GLP inhibitor scaffolds in cellular assays. Using primary human cell model systems, we discover that CHKA modulation impairs IgG secretion and B-cell maturation consistent with the notion that choline metabolism plays an important role in immune signalling. Co-crystal structures of UNC0638 and UNC0737 with CHKA unravel an unexpected binding mode and suggest the inhibitors as attractive starting points for the development of selective chemical tools to further explore the biological role of CHKA in cancer and immune metabolism.

Humans↗

PubMed2025

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci.

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with sample multiplexed quantitative proteomics, targeted chemical perturbations, and next-generation sequencing to quantify DNA-protein and DNA-DNA interactions at specific genomic loci. Furthermore, we establish that DNA O-MAP \ is applicable to both repetitive and unique genomic loci of varying sizes (kilobases to megabases), and that DNA O-MAP can measure proximal molecular effectors in a homolog-specific manner.

Journal Article↗

PubMed2026

Machine Learning in Hyperlipidaemia Research: Screening and Experimental Insights into Lipid Metabolism Modulators.

Hyperlipidemia, characterized by elevated blood lipid levels, represents a major global health concern due to its strong association with cardiovascular disease, diabetes, and metabolic syndrome. While current therapies - such as statins, fibrates, bile acid sequestrants, and PCSK9 inhibitors - are effective in controlling hyperlipidemia, they are often associated with adverse effects, potential drug resistance, and suboptimal efficacy in certain patient populations. All of the above underscore the urgent need for safer and more effective therapeutic alternatives. Among the major molecular targets involved in the regulation of lipid metabolism are HMG-CoA reductase, PCSK9, peroxisome proliferator-activated receptors (PPARs), cholesteryl ester transfer protein (CETP), and nuclear receptors, including the liver X receptor (LXR) and farnesoid X receptor (FXR), which are also targets for future antihyperlipidemic drug development. Recent advancements in artificial intelligence (AI) and machine learning (ML) have significantly transformed and accelerated drug discovery by enabling the processing of vast amounts of genomic, proteomic, and chemical data. Furthermore, ML tools such as quantitative structure-activity relationship (QSAR) modelling, deep learning, random forest, and support vector machines (SVM) have proven predictive and effective in identifying novel lipid metabolism modulators, thereby enhancing the efficacy and accuracy of virtual screening. Meanwhile, molecular docking has become an integral part of structure-based drug design (SBDD), and software such as AutoDock, Glide, and GOLD have proven effective in generating accurate ligand-target docking models. Molecular docking, together with ML-based approaches, enables the identification of potent and selective drug candidates. Overall, the combination of ML and molecular docking offers an efficient and accurate platform for antihyperlipidemic drug discovery, helping to overcome the limitations of currently available therapeutic strategies.

HMG-CoA reductase↗

PubMed2025

Hepatocyte proteome destabilization and novel targets for PFASs unveiled through combined thermal proteome profiling and deep transfer learning.

Identifying protein targets for per- and polyfluoroalkyl substances (PFASs) is essential to understand their toxicity and health risks. However, knowledge about their interacting proteins is limited since reliable identification methods are lacking. We developed an integrated approach combining thermal proteome profiling (TPP) and deep transfer learning (DTL) modeling to efficiently identify cellular targets of PFAS. TPP measured PFAS binding proteins and the affinities by nanospray liquid chromatography tandem mass spectrometry, while DTL models were constructed to predict PFAS-protein affinities using neural network algorithms. TPP results revealed that PFASs uniquely destabilized the proteome of HepG2 cells, unlike the stabilizing effects by other xenobiotics. Key protein targets for three representative PFASs (PFOA, GenX and Novec 649) were identified, which exhibited weak binding affinities (median EC50 ≈ 30 μM). The number of protein targets increased with molecular weights among the three PFASs. The DTL model achieved a higher Pearson correlation coefficient of 0.89, and reduced mean squared errors by 54 % over previous models for drug-protein interactions. Notably, TPP and DTL jointly pinpointed ribosomal proteins as novel targets of GenX, potentially linking it to cell apoptosis through disrupted protein synthesis. Biolayer interferometry validated GenX binding to RPL4 protein, driven by electrostatic interactions and halogen bonds. This integrated approach effectively uncovers novel PFASs targets, advancing insights into their adverse health effects.

Humans↗

PubMed2026

Streptococcus pneumoniae adaptation to nutrient deprivation and immune modulation drives upper respiratory tract colonization.

Streptococcus pneumoniae is a successful colonizer of the human upper respiratory tract; however, the mechanisms that enable its persistence in this nutrient-limited environment, with numerous immune mechanisms in place, remain enigmatic. Here, we examined how pneumococci adapt to upper respiratory tract conditions and how this affects host interactions. We measured intranasal metal ion and monosaccharide concentrations to create an in vivo-mimicking medium for studying pneumococcal adaptation. Growth in this medium was reduced compared to glucose-rich chemically defined media (CDM). Proteome analysis revealed a shift to galactose as the major carbohydrate source, and decreased levels of fatty acid biosynthesis proteins and pneumolysin, compared to other CDMs. Glycerophosphocholine accumulated extracellularly leading to decreased C-reactive protein and Immunoglobulin M binding to pneumococci. Pneumococci grown in in vivo-mimicking medium, compared to glucose-rich media, were more capable colonizers of primary epithelium and induced less epithelial cytokine release. Together, this shows how pneumococci adapt to the nutrient-limited respiratory environment, modulate epithelial cells, and evade humoral responses to facilitate persistent colonization.

Streptococcus pneumoniae↗

PubMed2025

A covalent chemical probe for Chikungunya nsP2 cysteine protease with antialphaviral activity and proteome-wide selectivity.

Chikungunya is a mosquito-borne viral disease that causes fever and severe joint pain for which there is no direct acting drug treatments. Vinyl sulfone SGC-NSP2PRO-1 (3) was identified as a potent inhibitor of the nsP2 cysteine protease (nsP2pro) that reduced viral titer against infectious isolates of Chikungunya and other alphaviruses. The covalent warhead in 3 captured the active site C478 and inactivated nsP2pro with a kinact/Ki ratio of 5950 M-1 s-1. The vinyl sulfone 3 was inactive across a panel of 23 other cysteine proteases and demonstrated remarkable proteome-wide selectivity by two chemoproteomic methods. A negative control analog SGC-NSP2PRO-1N (4) retained the isoxazole core and covalent warhead but demonstrated > 100-fold decrease in enzyme inhibition. Both 3 and 4 were stable across a wide range of pH in solution and upon prolonged storage as solids. Vinyl sulfone 3 and its negative control 4 will find utility as high-quality chemical probes to study the role of the nsP2pro in cellular studies of alphaviral replication and virulence.

Chikungunya virus↗

PubMed2026

Resolving cellular signaling in space and time: From organelle proteomics to spatial phosphoproteomics.

Cellular signaling is inherently organized in space and time, requiring coordinated control of protein localization, molecular interactions, and enzymatic activity across subcellular compartments. Recent advances in chemical biology, protein engineering, and quantitative proteomics have made it possible to interrogate these dimensions in an integrated manner. Here, we highlight emerging strategies to resolve signaling organization across three interconnected dimensions: organelle-resolved proteome mapping to define spatial context, proximity labeling to capture local protein interaction networks, and spatially resolved phosphoproteomics to quantify signaling outputs. Developments in proximity labeling, including split, conditionally activated and light-gated enzymes, enable temporally controlled, context-dependent profiling of transient protein assemblies in living cells. Advances in high-throughput and low-input phosphoproteomics, together with improved computational frameworks for kinase activity inference and subcellular enrichment strategies, are enabling spatially resolved measurement of signaling activity. Together, these approaches are shifting the field from static localization maps toward dynamic models of signaling networks.

Proteomics↗