Protein-protein Interaction Map Research Articles

Integrating network pharmacology and experimental verification to explore the mechanisms of salidroside against myocardial fibrosis

Myocardial fibrosis (MF) is the manifestation of a variety of cardiovascular diseases. Salidroside (SAL) has been proved to have a certain effect on anti-fibrosis in various organs. However, the mechanism of SAL in the treatment of MF remains unclear. Network pharmacology showed that there were 1228 SAL-related target genes and 2793 MF-related target genes. The intersection of these genes resulted in 271 drug-disease interactions, and 15 core active targets were filtered from protein-protein interaction mapping. The top 20 Gene ontology biological processes analysis showed that the involved processes were close to the pathogenesis of MF. Among the top 20 enriched KEGG pathways, Wnt/β-catenin and TGF-β1/Smad3 signaling pathways were identified. In vivo, MI rats exhibited thinning of the myocardial region and the formation of fibrous scars, the expression of smad3 and β-catenin were increased. After SAL treatment, there was a significant reduction in collagen area and a decrease in the ratio of collagen type I to type III. The expression of smad3 and β-catenin was suppressed and positively correlated with the dosage of SAL. SAL may contribute to the progression of MF through the TGF-β1/Smad3 and Wnt/β-catenin signaling pathways.

Elucidating cellular interactome of chikungunya virus identifies host dependency factors

Chikungunya virus (CHIKV) is a re-emerging mosquito-transmitted RNA virus causing joint and muscle pain. To better understand how CHIKV rewires the host cell and usurps host cell functions, we generated a systematic CHIKV-human protein-protein interaction map and revealed several novel connections that will inform further mechanistic studies. One of these novel interactions, between the viral protein E1 and STIP1 homology and U-box containing protein 1 (STUB1), was found to mediate ubiquitination of E1 and degrade E1 through the proteasome. Capsid associated with G3BP1, G3BP2 and AAA+ ​ATPase valosin-containing protein (VCP). Furthermore, VCP inhibitors blocked CHIKV infection, suggesting VCP could serve as a therapeutic target. Further work is required to fully understand the functional consequences of these interactions. Given that CHIKV proteins are conserved across alphaviruses, many virus-host protein-protein interactions identified in this study might also exist in other alphaviruses. Construction of interactome of CHIKV provides the basis for further studying the function of alphavirus biology.

Seeing the complete picture: proteins in top-down mass spectrometry.

Top-down protein mass spectrometry can provide unique insights into protein sequence and structure, including precise proteoform identification and study of protein-ligand and protein-protein interactions. In contrast with the commonly applied bottom-up approach, top-down approaches do not include digestion of the protein of interest into small peptides, but instead rely on the ionization and subsequent fragmentation of intact proteins. As such, it is fundamentally the only way to fully characterize the composition of a proteoform. Here, we provide an overview of how a top-down protein mass spectrometry experiment is performed and point out recent applications from the literature to the reader. While some parts of the top-down workflow are broadly applicable, different research questions are best addressed with specific experimental designs. The most important divide is between studies that prioritize sequence information (i.e., proteoform identification) versus structural information (e.g., conformational studies, or mapping protein-protein or protein-ligand interactions). Another important consideration is whether to work under native or denaturing solution conditions, and the overall complexity of the sample also needs to be taken into account, as it determines whether (chromatographic) separation is required prior to MS analysis. In this review, we aim to provide enough information to support both newcomers and more experienced readers in the decision process of how to answer a potential research question most efficiently and to provide an overview of the methods that exist to answer these questions.

Exploring an Alternative Cysteine-Reactive Chemistry to Enable Proteome-Wide PPI Analysis by Cross-Linking Mass Spectrometry.

The development of MS-cleavable cross-linking mass spectrometry (XL-MS) has enabled the effective capture and identification of endogenous protein-protein interactions (PPIs) and their residue contacts at the global scale without cell engineering. So far, only lysine-reactive cross-linkers have been successfully applied for proteome-wide PPI profiling. However, lysine cross-linkers alone cannot uncover the complete PPI map in cells. Previously, we have developed a maleimide-based cysteine-reactive MS-cleavable cross-linker (bismaleimide sulfoxide (BMSO)) that is effective for mapping PPIs of protein complexes to yield interaction contacts complementary to lysine-reactive reagents. While successful, the hydrolysis and limited selectivity of maleimides at physiological pH make their applications in proteome-wide XL-MS challenging. To enable global PPI mapping, we have explored an alternative cysteine-labeling chemistry and thus designed and synthesized a sulfoxide-containing MS-cleavable haloacetamide-based cross-linker, Dibromoacetamide sulfoxide (DBrASO). Our results have demonstrated that DBrASO cross-linked peptides display the same fragmentation characteristics as other sulfoxide-containing MS-cleavable cross-linkers, permitting their unambiguous identification by MSn. In combination with a newly developed two-dimensional peptide fractionation method, we have successfully performed DBrASO-based XL-MS analysis of HEK293 cell lysates and demonstrated its capability to complement lysine-reactive reagents and expand PPI coverage at the systems-level.

Cataloguing Protein Complexes In Planta Using TurboID-Catalyzed Proximity Labeling.

Mapping protein-protein interactions is crucial to understand protein function. Recent advances in proximity-dependent biotinylation (BioID) coupled to mass spectrometry (MS) allow the characterization of protein complexes in diverse plant models. Here, we describe the use of BioID in hairy root cultures of tomato and provide detailed information on how to analyze the data obtained by MS.

High-Throughput Protein-Protein Interactions Screening Using Pool-Based Liquid Yeast Two-Hybrid Pipeline.

Because of its adaptability to high-throughput approaches and a low operating cost, the yeast two-hybrid (Y2H) assay remains the most widely used one for high-throughput protein-protein interactions (PPI) mapping experiments. Here we provide a detailed protocol for a liquid culture-based high-throughput binary protein-protein Y2H screen pipeline of a pool of 50 proteins used as baits against a collection of ~12,000 Arabidopsis proteins encoded by sequence-verified open reading frames (ORFs).

Virotrap: Trapping Protein Complexes in Virus-Like Particles.

The discovery of protein-protein interactions can provide crucial information on protein function by linking proteins into known pathways or complexes within the cell. Mass spectrometry (MS)-based methods, such as affinity purification (AP)-MS and proximity-dependent biotin identification (BioID), allowed for a vast increase in the number of reported protein complexes. As a more recent addition to the arsenal of MS-based methods, Virotrap represents a unique technology that benefits from the specific properties of the human immunodeficiency virus-1 (HIV-1) Gag polyprotein. More specifically, Virotrap captures protein complexes in virus-like particles budded from human embryonic kidney (HEK293T) cells, bypassing the need for cell lysis and thus supporting identification of their content using MS. Being intrinsically different to its two main predecessors, affinity purification MS (AP-MS) and biotin-dependent identification (BioID), Virotrap was shown to complement data obtained with the existing MS-based toolkit. The proven complementarity of these MS-based strategies underlines the importance of using different techniques to enable comprehensive mapping of protein-protein interactions (PPIs). In this chapter, we provide a detailed overview of the Virotrap protocol to screen for PPIs using a bait protein of interest.

Abstract 2711: New Advances in Cross-linking Mass Spectrometry for Mapping Protein-Protein Interactions

Abstract 2711: New Advances in Cross-linking Mass Spectrometry for Mapping Protein-Protein Interactions

Proximity-dependent biotin labeling in testicular germ cells identified TESMIN-associated proteins

Characterization of protein–protein interactions (PPI) is a key to understanding the functions of proteins of interest. Recently developed proximity-dependent biotin identification (BioID) has been actively investigated as an alternative PPI mapping method because of its usefulness in uncovering transient PPI. Here, as an example of proximity labeling proteomics application in the testis, we generated two transgenic mouse lines expressing two biotin ligases (BioID2 or TurboID) fused with TESMIN, which translocates from the cytosol to the nucleus during meiotic progression and is required for reproduction. The BioID2 transgene, albeit not the TurboID transgene, rescued fertility defects of the Tesmin KO male mice, indicating that the TESMIN-BioID2 fusion can physiologically replace TESMIN. Furthermore, biotinylated protein pull-down and affinity-purification followed by mass spectrometry using the TESMIN-BioID2 transgenic mice captured components of the MYBL1–MuvB complex that regulate cell-cycle gene expression. Thus, our study shows that proximity labeling proteomics can be applied in male germ cells, although the choice of biotin ligase needs to be carefully tested.

Investigation and Expression Analysis of R2R3-MYBs and Anthocyanin Biosynthesis-Related Genes during Seed Color Development of Common Bean (Phaseolus vulgaris).

Anthocyanins are responsible for the coloration of common bean seeds, and their accumulation is positively correlated with the expression level of anthocyanin biosynthetic genes. The MBW (MYB-bHLH-WD40) complex is thought to regulate the expression of these genes, and MYB proteins, which are a key factor in activating anthocyanin pathway genes, have been identified in several plants. This study demonstrated gene structures, chromosomal placements, gene duplications of R2R3-MYBs, miRNAs associated with R2R3-MYBs, and the interaction of these genes with other flavonoid regulatory genes. qRT-PCR was used to investigate the role of specific R2R3-MYBs and flavonoid genes in common bean seed color development. As a result of a comprehensive analysis with the help of in silico tools, we identified 160 R2R3-MYB genes in the common bean genome. We divided these genes into 16 classes on the basis of their intron-exon and motif structures. Except for three, the rest of the common bean R2R3-MYB members were distributed to all chromosomes with different densities, primarily located on chromosomes 3 and 8. We identified a total of 44 duplicated gene pairs dispersed across 11 chromosomes and evolved under purifying selection (Ka/Ks < 1), 19 of which were derived from a whole-genome duplication. Our research uncovered 25 putative repressor PvMYB proteins that contain the EAR motif. Additionally, fifty different cis-regulatory elements regulated by light, stress, and hormone were identified. Within the genome of the common bean, we discovered a total of 36 microRNAs that target a total of 72 R2R3-MYB transcripts. The effect of 16 R2R3-MYB genes and 16 phenylpropanoid pathway genes, selected on the basis of their interaction in the protein-protein interaction map, playing role in the regulation of seed coat color development was evaluated using qRT-PCR in 5 different tissues at different developmental stages. The results revealed that these specific genes have different expression levels during different developmental periods, with higher levels in the pod filling and early pod stages than in the rest of the developmental periods. Furthermore, it was shown that PvTT8 (bHLH), PvTT2 (PvMYB42), PvMYB113, PvTTG1, and PvWD68 genes have effects on the regulation of seed coat color. The findings of this study, which is the first to use whole-genome analysis to identify and characterize the R2R3-MYB genes in common bean, may serve as a reference for future functional research in the legume.

Potential Biomarkers and Signaling Pathways Associated with the Pathogenesis of Primary Ameloblastoma: A Systems Biology Approach

Objective Ameloblastoma is a benign odontogenic tumor that may lead to ameloblastic carcinoma. This study aimed to determine potential signaling pathways and biological processes, critical genes and their regulating transcription factors (TFs), and miRNAs, as well as protein kinases involved in the etiology of primary ameloblastoma. Methods The dataset GSE132472 was obtained from the GEO database, and multivariate statistical analyses were applied to identify differentially expressed genes (DEGs) in primary ameloblastoma tissues compared to the corresponding normal gingiva samples. A protein-protein interaction (PPI) map was built using the STRING database. The Cytoscape software identified significant modules and the hub genes within the PPI network. Gene Ontology annotation and signaling pathway analyses were executed by employing the DAVID and Reactome databases, respectively. Significant TFs and miRNAs acting on the hub genes were identified using the iRegulon plugin and MiRWalk 2.0 database, respectively. A protein kinase enrichment analysis was conducted using the online Kinase Enrichment Analysis 2 (KEA2) web server. The approved drugs acting on the hub genes were also found. Results A total of 1,629 genes were differentially expressed in primary ameloblastoma (P value <0.01 and |Log2FC| > 1). HRAS, CDK1, MAPK3, ERBB2, COL1A1, CYCS, and BRCA1 demonstrated high degree and betweenness centralities in the PPI network. E2F4 was the most significant TF acting on the hub genes. BTK was the protein kinase significantly enriched by the TFs. Cholesterol biosynthesis was considerably involved in primary ameloblastoma. Conclusions This study provides an intuition into the potential mechanisms involved in the etiology of ameloblastoma.

Protein interactome mapping of Porphyromonas gingivalis provides insights into the formation of the PorQ-Z complex of the type IX secretion system.

Porphyromonas gingivalis is an anaerobic Gram-negative human oral pathogen highly associated with the more severe forms of periodontal disease. Porphyromonas gingivalis utilises the type IX secretion system (T9SS) to transport ∼30 cargo proteins, including multiple virulence factors, to the cell surface. The T9SS is a multiprotein system consisting of at least 20 proteins, and recently, we characterised the protein interactome of these components. Similar to the T9SS, almost all biological processes are mediated through protein-protein interactions (PPIs). Therefore, mapping PPIs is important to understand the biological functions of many proteins in P. gingivalis. Herein, we provide native migration profiles of over 1000 P. gingivalis proteins. Using the T9SS, we demonstrate that our dataset is a useful resource for identifying novel protein interactions. Using this dataset and further analysis of T9SS P. gingivalis mutants, we discover new mechanistic insights into the formation of the PorQ-Z complex of the T9SS. This dataset is a valuable resource for studies of P. gingivalis.

Mapping Protein-Protein Interactions Using Data-Dependent Acquisition without Dynamic Exclusion.

Systematic analysis of affinity-purified samples by liquid chromatography coupled to mass spectrometry (LC-MS) requires high coverage, reproducibility, and sensitivity. While data-independent acquisition (DIA) approaches improve the reproducibility of protein-protein interaction detection as compared to standard data-dependent acquisition approaches, the need for library generation reduces their throughput, and analysis pipelines are still being optimized. In this study, we report the development of a simple and robust approach, termed turboDDA, to improve interactome analysis using spectral counting and data-dependent acquisition (DDA) by eliminating the dynamic exclusion (DE) step and optimizing the acquisition parameters. Using representative interaction and proximity proteomics samples, we detected increases in identified interactors of 18-71% compared to all samples analyzed by standard DDA with dynamic exclusion and for most samples analyzed by DIA with the MSPLIT-DIA spectral counting approach. In summary, turboDDA provides better sensitivity and identifies more high-confident interactors than the optimized DDA with DE and comparable or better sensitivity than DIA spectral counting approaches.

The mechanism of action of the combination of Astragalus membranaceus and Ligusticum chuanxiong in the treatment of ischemic stroke based on network pharmacology and molecular docking.

Since 1990, the incidence of stroke has been rising to become the second leading cause of death in the world, posing a huge burden and challenge to society and families. Astragalus membranaceus and Ligusticum chuanxiong (A&L) have been used as traditional Chinese medicine (TCM) prescriptions to treat and prevent the occurrence of ischemic stroke (IS), but their mechanism of action on the disease has not been fully elucidated. The main objective of this study was to reveal the pharmacological mechanism of A&L in the treatment of IS and to perform preliminary validation. The active ingredients of A&L were obtained from the systematic pharmacology platform of traditional Chinese medicine (TCMSP) database, whereas the genes of IS were obtained from 2 major databases, DrugBank and GeneCards. Cytoscape_v3.8.2 was used to construct the TCM-active ingredient and TCM-active ingredient-cross-target-disease relationship maps, and the MCODE plug-in was used to obtain the core genes, whereas the protein-protein interaction maps were obtained from the STRING database. The results of gene ontology and Kyoto encyclopedia of genes and genomes enrichment were obtained using the Hiplot online tool, and the small molecules in the relevant signalling pathways were verified by molecular docking using AutoDock. A&L contained a total of 26 eligible active ingredients, sharing 161 common targets with IS. A total of 58 core genes with 1326 edges were obtained using the MCODE plug-in. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment results showed association with interleukin-17 signaling pathway, lipid and atherosclerosis, tumor necrosis factor signaling pathway, and Toll-like receptor signaling pathway, which mainly mediates the development of inflammatory responses. Furthermore, molecular docking was conducted and most of the components were found to have good binding to the receptors. This study demonstrates that A&L can be used to treat IS by controlling the inflammatory response through multiple targets and multiple pathways, and provides a reference for subsequent trials.

A protein-protein interaction map reveals that the Coxiella burnetii effector CirB inhibits host proteasome activity.

Coxiella burnetii is the etiological agent of the zoonotic disease Q fever, which is featured by its ability to replicate in acid vacuoles resembling the lysosomal network. One key virulence determinant of C. burnetii is the Dot/Icm system that transfers more than 150 effector proteins into host cells. These effectors function to construct the lysosome-like compartment permissive for bacterial replication, but the functions of most of these effectors remain elusive. In this study, we used an affinity tag purification mass spectrometry (AP-MS) approach to generate a C. burnetii-human protein-protein interaction (PPI) map involving 53 C. burnetii effectors and 3480 host proteins. This PPI map revealed that the C. burnetii effector CBU0425 (designated CirB) interacts with most subunits of the 20S core proteasome. We found that ectopically expressed CirB inhibits hydrolytic activity of the proteasome. In addition, overexpression of CirB in C. burnetii caused dramatic inhibition of proteasome activity in host cells, while knocking down CirB expression alleviated such inhibitory effects. Moreover, we showed that a region of CirB that spans residues 91–120 binds to the proteasome subunit PSMB5 (beta 5). Finally, PSMB5 knockdown promotes C. burnetii virulence, highlighting the importance of proteasome activity modulation during the course of C. burnetii infection.

A network-based pharmacological study on the mechanism of action of muscone in breast cancer.

BackgroundThe purpose of this study was to investigate the mechanism of action of muscone on breast cancer using network pharmacology and molecular docking techniques.MethodsTargets of muscone acid action were collected using the PubChem and SwissTargetPrediction databases. Relevant target sets of breast cancer were collected using the GeneCards database, and the intersection of the drug-disease targets was used as the potential target of muscone action in breast cancer. The STRING database was used to construct a target protein-protein interaction (PPI) network, and the data were imported into Cytoscape 3.7.1 for topological network analysis to obtain the core target genes of muscone in breast cancer. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. The correlation of core gene expression with breast cancer survival was analyzed using the online Kaplan-Meier plotter tool. Molecular docking of core target genes to muscone was performed using AutoDock Vina.ResultsA total of 18 common targets of muscone and breast cancer were obtained through target intersection. The PPI map and topology analysis revealed that androgen receptor (AR), progesterone receptor (PGR), matrix metalloproteinase 9 (MMP9), prostaglandin-endoperoxide synthase 2 (PTGS2), heat shock protein 90 alpha family class A member 1 (HSP90AA1), mitogen-activated protein kinase 14 (MAPK14), and cytochrome P450 family 19 subfamily A member 1 (CYP19A1) might be the key targets of muscone acting on breast cancer. The GO enrichment analysis identified 60 terms, while the KEGG pathway enrichment analysis identified 7 signaling pathways, including steroid hormone biosynthesis, ovarian steroidogenesis, cancer pathways, and the tumor necrosis factor (TNF) signaling pathway. The results of survival stage analysis showed that the binding activity between muskone and key targets was better than other targets. The molecular docking results showed that muscone had the highest docking affinity for the key target CYP19A1 gene at −7.0 kJ/moL.ConclusionsMuscone might exert anti–breast cancer effects through cancer pathways, ovarian steroidogenesis, and TNF signaling pathways and has the potential to be developed as a clinical agent.

Network-based response module comprised of gene expression biomarkers predicts response to infliximab at treatment initiation in ulcerative colitis

This cross-cohort study aimed to (1) determine a network-based molecular signature that predicts the likelihood of inadequate response to the tumor necrosis factor-ɑ inhibitor (TNFi) therapy, infliximab, in ulcerative colitis (UC) patients, and (2) address biomarker irreproducibility across different cohort studies. Whole-transcriptome microarray data were derived from biopsies of affected colon tissue from 2 cohorts of infliximab-treated UC patients (training N=24 and validation N=22). Response was defined as endoscopic and histologic healing at 4-6 weeks and 8 weeks, respectively. From the training cohort, genes with RNA expression that significantly correlated with clinical response outcomes were mapped onto the Human Interactome network map of protein-protein interactions to identify a largest connected component (LCC) of proteins indicative of infliximab response status in UC. Expression levels of transcripts within the LCC were fed into a probabilistic neural network model to generate a classifier that predicts inadequate response to infliximab. A classifier predictive of inadequate response to infliximab was generated and tested in a cross-cohort, blinded fashion; the AUC was 0.83 and inadequate response was predicted with a 100% positive predictive value and 64% sensitivity. Genes separately identified from the 2 cohorts that correlated with response to infliximab appeared distinct but mapped onto the same network region of the Human Interactome, reflecting a common underlying biology of response among UC patients. Cross-cohort validation of a classifier predictive of infliximab response status in UC patients indicates that a molecular signature of non-response to TNFi therapies is present in patients' baseline gene expression data. The goal is to develop a diagnostic test that predicts which patients will have an inadequate response to targeted therapies and define new targets and pathways for therapeutic development.

Two-Dimensional Fractionation Method for Proteome-Wide Cross-Linking Mass Spectrometry Analysis.

Cross-linking mass spectrometry (XL-MS) is an emergent technology for studying protein-protein interactions (PPIs) and elucidating architectures of protein complexes. The development of various MS-cleavable cross-linkers has facilitated the identification of cross-linked peptides, enabling XL-MS studies at the systems level. However, the scope and depth of cellular networks revealed by current XL-MS technologies remain limited. Due to the inherently broad dynamic range and complexity of proteomes, interference from highly abundant proteins impedes the identification of low-abundance cross-linked peptides in complex samples. Thus, peptide enrichment prior to MS analysis is necessary to enhance cross-link identification for proteome-wide studies. Although chromatographic techniques including size exclusion (SEC) and strong cation exchange (SCX) have been successful in isolating cross-linked peptides, new fractionation methods are still needed to further improve the depth of PPI mapping. Here, we present a two-dimensional (2D) separation strategy by integrating peptide SEC with tip-based high pH reverse-phase (HpHt) fractionation to expand the coverage of proteome-wide XL-MS analyses. Combined with the MS-cleavable cross-linker DSSO, we have successfully mapped in vitro PPIs from HEK293 cell lysates with improved identification of cross-linked peptides compared to existing approaches. The method developed here is effective and can be generalized for cross-linking studies of complex samples.

Construction of a Macrophage Infiltration Regulatory Network and Related Prognostic Model of High-Grade Serous Ovarian Cancer

Background High-grade serous ovarian cancer (HGSOC) carries the highest mortality in the gynecological cancers; however, therapeutic outcomes have not significantly improved in recent decades. Macrophages play an essential role in the occurrence and development of ovarian cancer, so the mechanisms of macrophage infiltration should be elucidated. Method We downloaded transcriptome data of ovarian cancers from the Gene Expression Omnibus and The Cancer Genome Atlas. After rigorous screening, 1566 HGSOC were used for data analysis. CIBERSORT was used to estimate the level of macrophage infiltration and WGCNA was used to identify macrophage-related modules. We constructed a macrophage-related prognostic model using machine learning LASSO algorithm and verified it using multiple HGSOC cohorts. Results In the GPL570-OV cohort, high infiltration level of M1 macrophages was associated with a good outcome, while high infiltration level of M2 macrophages was associated with poor outcomes. We used WGCNA to select genes correlated with macrophage infiltration. These genes were used to construct protein-protein interaction maps of macrophage infiltration. IFL44L, RSAD2, IFIT3, MX1, IFIH1, IFI44, and ISG15 were the hub genes in the network. We then constructed a macrophage-related prognostic model composed of CD38, ACE2, BATF2, HLA-DOB, and WARS. The model had the ability to predict the overall survival rate of HGSOC patients in GPL570-OV, GPL6480-OV, TCGA-OV, GSE50088, and GSE26712. In exploring the immune microenvironment, we found that CD4 memory T cells and activated mast cells showed that the degree of infiltration was higher in the high-risk group, while M1 macrophages were the opposite, and HLA molecules were overexpressed in the high-risk group. Conclusion We constructed a macrophage infiltration-related protein interaction network that provides a basis for studying macrophages in HGSOC. Our macrophage-related prognostic model is robust and widely applicable. It predicts overall survival in HGSOC patients and may improve HGSOC treatment.

Proximity-Dependent Labeling of Cysteines.

Mapping protein-protein interactions is crucial for understanding various signaling pathways in living cells, and developing new techniques for this purpose has attracted significant interest. Classic methods (e.g., the yeast two-hybrid) have been supplanted by more sophisticated chemical approaches that label proximal proteins (e.g., BioID, APEX). Herein we describe a proximity-based approach that uniquely labels cysteines. Our approach exploits the nicotinamide N-methyltransferase (NNMT)-catalyzed methylation of an alkyne-substituted 4-chloropyridine (SS6). Upon methylation of the pyridinium nitrogen, this latent electrophile diffuses out of the active site and labels proximal proteins on short time scales (≤5 min). We validated this approach by identifying known (and novel) interacting partners of protein arginine deiminase 2 (PAD2) and pyruvate dehydrogenase kinase 1 (PDK1). To our knowledge, this technology uniquely exploits a suicide substrate to label proximal cysteines in live cells.