Post-translational Modifications Crosstalk Research Articles

Improved prediction of post-translational modification crosstalk within proteins using DeepPCT.

Post-translational modification (PTM) crosstalk events play critical roles in biological processes. Several machine learning methods have been developed to identify PTM crosstalk within proteins, but the accuracy is still far from satisfactory. Recent breakthroughs in deep learning and protein structure prediction could provide a potential solution to this issue. We proposed DeepPCT, a deep learning algorithm to identify PTM crosstalk using AlphaFold2-based structures. In this algorithm, one deep learning classifier was constructed for sequence-based prediction by combining the residue and residue pair embeddings with cross-attention techniques, while the other classifier was established for structure-based prediction by integrating the structural embedding and a graph neural network. Meanwhile, a machine learning classifier was developed using novel structural descriptors and a random forest model to complement the structural deep learning classifier. By integrating the three classifiers, DeepPCT outperformed existing algorithms in different evaluation scenarios and showed better generalizability on new data owing to its less distance dependency. Datasets, codes, and models of DeepPCT are freely accessible at https://github.com/hzau-liulab/DeepPCT/.

Subcellular Proteomic Mapping of Lysine Lactylation.

Protein lactylation is a novel post-translational modification (PTM) involved in many important physiological processes such as macrophage polarization, immune regulation, and tumor cell growth. However, traditional methodologies for studying lactylation have predominantly relied on peptide enrichment from whole-cell lysates, which tend to favor the detection of high-abundance peptides, thus limiting the identification of low-abundance lactylated peptides. To address this limitation, here, we employed subcellular fractionation to separate proteins and map lactylated peptides from each isolated subcellular fraction using a model cell line. In brief, we identified 1,217 lysine lactylation (Kla) sites on 553 proteins across four subcellular fractions. Subsequent pathway enrichment analysis revealed that Kla proteins participate in distinct pathways depending on the subcellular contexts. In addition, this subcellular fractionation method enabled the discovery of 36 previously unreported Kla proteins and 223 novel Kla sites, many of which are present in low abundance. Notably, several proteins contain multiple newly identified Kla sites, exemplified by the transcriptional regulator ATRX. Furthermore, our results indicate the possibility of PTM crosstalk between Kla and other PTMs such as ubiquitination and sumoylation. In conclusion, subcellular fractionation facilitates the identification of Kla proteins that have been previously uncovered and could be overlooked by affinity enrichment of whole-cell lysates.

Normalized and Directional Interplay Scoring for the Interrogation of Proteoform Data.

Histone proteoforms, often presenting multiple co-occurring post-translational modifications (PTMs), are central to chromatin regulation and gene expression. A proteoform is a specific form of a protein that includes variations arising from genetic changes, alternative RNA splicing, proteolytic processing, and PTMs. Genomic context-dependent histone proteoforms define the histone code, influencing cellular phenotype by dictating interactions with DNA and chromatin-associated proteins. Understanding the dynamics of histone proteoforms is essential for elucidating chromatin-based regulatory mechanisms. Advances in middle-down and top-down proteomics methods enable accurate identification and quantitation of hundreds to thousands of proteoforms in a single run. However, the resulting data complexity presents significant challenges for analysis and visualization. Here, we introduce new computational methods to analyze the dynamics of histone PTMs and demonstrate their use in mouse organs during aging. We have developed and benchmarked two novel PTM crosstalk scores. The score that we term 'Normalized Interplay' addresses limitations of the original crosstalk score 'Interplay' providing a more complete and accurate measure of PTM crosstalk. The second score, 'delta I' or Directional Interplay is an asymmetric measure quantifying the magnitude and directionality of crosstalk between PTMs. Applying our two-stage scoring approach to data from CrosstalkDB, a community resource that curates proteoform-level data, reveals the dynamics of histone H3 modifications during aging. The source code is available under an Apache license at https://github.com/k-p4/ptm_interplay_scoring .

Promotion of RNF168-Mediated Nucleosomal H2A Ubiquitylation by Structurally Defined K63-Polyubiquitylated Linker Histone H1.

The chemical synthesis of histones with homogeneous modifications is a powerful approach for quantitatively deciphering the functional crosstalk between different post-translational modifications (PTMs). In this study, we developed an expedient site-specific (poly)ubiquitylation strategy (CAEPL, Cysteine Aminoethylation coupled with Enzymatic Protein Ligation), which integrates the Cys-aminoethylation reaction with the process of ubiquitin-activating enzyme UBA1-assisted native chemical ligation. Using this strategy, we successfully prepared monoubiquitylated and K63-linked di- and tri-ubiquitylated linker histone H1.0 proteins, which were incorporated into individual chromatosomes. Quantitative biochemical analysis of different RNF168 constructs on H1 ubiquitylated chromatosomes with different ubiquitin chain lengths demonstrated that K63-linked polyubiquitylated H1.0 could directly stimulate RNF168 ubiquitylation activity by enhancing the affinity between RNF168 and the chromatosome. Subsequent cryo-EM structural analysis of the RNF168/UbcH5c-Ub/H1.0-K63-Ub3 chromatosome complex revealed the potential recruitment orientation between RNF168 UDM1 domain and K63-linked ubiquitin chain on H1.0. Finally, we explored the impact of H1.0 ubiquitylation on RNF168 activity in the context of asymmetric H1.0-K63-Ub3 di-nucleosome substrate, revealing a comparable stimulation effect of both the inter- and intra-nucleosomal crosstalk. Overall, our study highlights the significance of access to structurally defined polyubiquitylated H1.0 by the CAEPL strategy, enabling in-depth mechanistic investigations of in-trans PTM crosstalk between linker histone H1.0 and core histone H2A ubiquitylation.

Posttranslational Modifications of α-Synuclein, Their Therapeutic Potential, and Crosstalk in Health and Neurodegenerative Diseases.

α-Synuclein (α-Syn) aggregation in Lewy bodies and Lewy neurites has emerged as a key pathogenetic feature in Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. Various factors, including posttranslational modifications (PTMs), can influence the propensity of α-Syn to misfold and aggregate. PTMs are biochemical modifications of a protein that occur during or after translation and are typically mediated by enzymes. PTMs modulate several characteristics of proteins including their structure, activity, localization, and stability. α-Syn undergoes various posttranslational modifications, including phosphorylation, ubiquitination, SUMOylation, acetylation, glycation, O-GlcNAcylation, nitration, oxidation, polyamination, arginylation, and truncation. Different PTMs of a protein can physically interact with one another or work together to influence a particular physiological or pathological feature in a process known as PTMs crosstalk. The development of detection techniques for the cooccurrence of PTMs in recent years has uncovered previously unappreciated mechanisms of their crosstalk. This has led to the emergence of evidence supporting an association between α-Syn PTMs crosstalk and synucleinopathies. In this review, we provide a comprehensive evaluation of α-Syn PTMs, their impact on misfolding and pathogenicity, the pharmacological means of targeting them, and their potential as biomarkers of disease. We also highlight the importance of the crosstalk between these PTMs in α-Syn function and aggregation. Insight into these PTMS and the complexities of their crosstalk can improve our understanding of the pathogenesis of synucleinopathies and identify novel targets of therapeutic potential. SIGNIFICANCE STATEMENT: α-Synuclein is a key pathogenic protein in Parkinson's disease and other synucleinopathies, making it a leading therapeutic target for disease modification. Multiple posttranslational modifications occur at various sites in α-Synuclein and alter its biophysical and pathological properties, some interacting with one another to add to the complexity of the pathogenicity of this protein. This review details these modifications, their implications in disease, and potential therapeutic opportunities.

A model for predicting post-translational modification cross-talk based on the Multilayer Network

Post-translational modifications (PTMs) are pivotal in controlling protein function, signaling pathways, and cellular processes, underscoring their importance in biological systems. PTMs not only regulate various signaling pathways by modifying individual residues but also regulate signaling pathways through the interaction of different modified residues within proteins or between proteins, which is known as PTM cross-talk. An in-depth study of the interactions between PTMs can lead to a clearer understanding of the regulatory mechanisms mediated by PTMs. Therefore, accurately identifying potential PTM cross-talk within proteins (Intra PTM cross-talk) or between proteins (Inter PTM cross-talk) is of utmost importance in biological research. In this work, we introduce an innovative approach called WPTCMN/PTCMN for simultaneous prediction of Intra/Inter PTM cross-talk using an integrated deep neural network, which is based on a Multilayer Network. Comprehensive experimental analysis demonstrates that using the Multilayer Network to capture the complex associations between Intra/Inter PTM cross-talk exhibits remarkable superiority in predicting PTM cross-talk. Specifically, the AUC value achieved on Intra PTM cross-talk is 0.924, while on Inter PTM cross-talk it reaches 0.872, surpassing existing methods. Therefore, WPTCMN/PTCMN represents an effective tool for simultaneous prediction of Intra/Inter PTM cross-talk.

Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches.

Over 400 different types of post-translational modifications (PTMs) have been reported and over 200 various types of PTMs have been discovered using mass spectrometry (MS)-based proteomics. MS-based proteomics has proven to be a powerful method capable of global PTM mapping with the identification of modified proteins/peptides, the localization of PTM sites and PTM quantitation. PTMs play regulatory roles in protein functions, activities and interactions in various heart related diseases, such as ischemia/reperfusion injury, cardiomyopathy and heart failure. The recognition of PTMs that are specific to cardiovascular pathology and the clarification of the mechanisms underlying these PTMs at molecular levels are crucial for discovery of novel biomarkers and application in a clinical setting. With sensitive MS instrumentation and novel biostatistical methods for precise processing of the data, low-abundance PTMs can be successfully detected and the beneficial or unfavorable effects of specific PTMs on cardiac function can be determined. Moreover, computational proteomic strategies that can predict PTM sites based on MS data have gained an increasing interest and can contribute to characterization of PTM profiles in cardiovascular disorders. More recently, machine learning- and deep learning-based methods have been employed to predict the locations of PTMs and explore PTM crosstalk. In this review article, the types of PTMs are briefly overviewed, approaches for PTM identification/quantitation in MS-based proteomics are discussed and recently published proteomic studies on PTMs associated with cardiovascular diseases are included.

Proteomics Applications in Toxoplasma gondii: Unveiling the Host-Parasite Interactions and Therapeutic Target Discovery.

Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID (BirA*-mediated proximity-dependent biotin identification), APEX (ascorbate peroxidase-mediated proximity labeling), and Y2H (yeast two hybrid), as well as various proteomics approaches, including single-cell analysis, DIA (data-independent acquisition), targeted, top-down, and plasma proteomics. Furthermore, we discuss bioinformatics and the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.

Analysis of a macrophage carbamylated proteome reveals a function in post-translational modification crosstalk

BackgroundLysine carbamylation is a biomarker of rheumatoid arthritis and kidney diseases. However, its cellular function is understudied due to the lack of tools for systematic analysis of this post-translational modification (PTM).MethodsWe adapted a method to analyze carbamylated peptides by co-affinity purification with acetylated peptides based on the cross-reactivity of anti-acetyllysine antibodies. We also performed immobilized-metal affinity chromatography to enrich for phosphopeptides, which allowed us to obtain multi-PTM information from the same samples.ResultsBy testing the pipeline with RAW 264.7 macrophages treated with bacterial lipopolysaccharide, 7,299, 8,923 and 47,637 acetylated, carbamylated, and phosphorylated peptides were identified, respectively. Our analysis showed that carbamylation occurs on proteins from a variety of functions on sites with similar as well as distinct motifs compared to acetylation. To investigate possible PTM crosstalk, we integrated the carbamylation data with acetylation and phosphorylation data, leading to the identification 1,183 proteins that were modified by all 3 PTMs. Among these proteins, 54 had all 3 PTMs regulated by lipopolysaccharide and were enriched in immune signaling pathways, and in particular, the ubiquitin-proteasome pathway. We found that carbamylation of linear diubiquitin blocks the activity of the anti-inflammatory deubiquitinase OTULIN.ConclusionsOverall, our data show that anti-acetyllysine antibodies can be used for effective enrichment of carbamylated peptides. Moreover, carbamylation may play a role in PTM crosstalk with acetylation and phosphorylation, and that it is involved in regulating ubiquitination in vitro.Graphical 9DSWmM7hoJm8b3LaxSLrsCVideo

Serial and multi-level proteome analysis for microscale protein samples

Post-translational modifications (PTMs), such as phosphorylation and ubiquitination, play key roles in signal transduction and protein homeostasis. The crosstalk of PTMs greatly expands the components of proteome and protein functions. Multi-level proteome analysis, which involves proteome investigations of total lysate and PTMs in this context, provides a comprehensive approach to explore the PTM crosstalk of a biological system under diverse disturbances. However, multi-level proteome practice remains technically challenging. Here we intended to build a strategy for multi-level proteome analysis, in which we focus on the serial profiling the total proteome, ubiquitinome and phosphoproteome from the microscale of starting material. We started by evaluating five common lysis buffers and found that the sodium deoxycholate buffer provided the best overall performance. We then developed an approach for serial enrichment and profiling of the multi-level proteome. To expand the depth of identification, we customized the variable windows to perform data-independent acquisition (DIA) sequencing for each proteome. In total, we identified 6465 proteins, ∼20,000 GlyGly sites (class 1), and ∼ 19,000 phosphosites (class 1) sequentially using 1 mg of HeLa digest by three DIA measurements. We applied this strategy to analyze MG132-treated HeLa cells and observed the crosstalk between ubiquitination and phosphorylation. Our method can be referenced for other multi-level proteome studies with microscale samples. SignificanceLysis buffer containing sodium deoxycholate provided the best overall performance in multi-level proteome analysis. One step of ubiquitination enrichment before phosphorylation enrichment does not reduce the reproducibility of phosphoproteome. Customized isolation windows were established for DIA analysis on each level of proteome. Combined the serial enrichment approach and the customized single-shot DIA method enabled the multi-level proteome of microscale protein samples.

Insights into the Lysine Acetylome of the Haloarchaeon Haloferax volcanii during Oxidative Stress by Quantitative SILAC-Based Proteomics.

Oxidative stress adaptation strategies are important to cell function and are linked to cardiac, neurodegenerative disease, and cancer. Representatives of the Archaea domain are used as model organisms based on their extreme tolerance to oxidants and close evolutionary relationship with eukaryotes. A study of the halophilic archaeon Haloferax volcanii reveals lysine acetylation to be associated with oxidative stress responses. The strong oxidant hypochlorite: (i) stimulates an increase in lysine acetyltransferase HvPat2 to HvPat1 abundance ratios and (ii) selects for lysine deacetylase sir2 mutants. Here we report the dynamic occupancy of the lysine acetylome of glycerol-grown H. volcanii as it shifts in profile in response to hypochlorite. These findings are revealed by the: (1) quantitative multiplex proteomics of the SILAC-compatible parent and Δsir2 mutant strains and (2) label-free proteomics of H26 'wild type' cells. The results show that lysine acetylation is associated with key biological processes including DNA topology, central metabolism, cobalamin biosynthesis, and translation. Lysine acetylation targets are found conserved across species. Moreover, lysine residues modified by acetylation and ubiquitin-like sampylation are identified suggesting post-translational modification (PTM) crosstalk. Overall, the results of this study expand the current knowledge of lysine acetylation in Archaea, with the long-term goal to provide a balanced evolutionary perspective of PTM systems in living organisms.

Targeting epigenetic crosstalk that restrains the responses of exhausted T cells to immune checkpoint blockade therapy

Abstract Epigenetic scarring of exhausted CD8 T (TEX) cells during chronic virus infections or cancer remains a major cell-intrinsic barrier to T cell immunotherapies, including immune checkpoint blockade (ICB). For successful epigenetic reprogramming of TEX cells, it is crucial to identify and target the molecular mechanisms underlying terminal exhaustion. Previous work revealed that de novo DNA methylation enforces silencing of T cell function and restrains their responses to ICB therapy. Yet, it remains largely unknown whether post-translational histone modifications crosstalk with de novo DNA methylation during the progression to terminal exhaustion. To better understand the interplay between these epigenetic mechanisms in chronically stimulated CD8 T cells, we employed our novel in vitro model of human T cell dysfunction, as well as preclinical models of T cell exhaustion including chronic LCMV infection. We found a significant relationship between dynamic histone changes and de novo DNA methylation in TEX cells. Importantly, targeting a key histone-modifying enzyme in dysfunctional human T cells improved their effector function and cytotoxicity in vitro. In addition, during chronic LCMV infection, combined treatment by a selective inhibitor and anti-PD-L1 significantly enhanced the ICB responses of stem-like and cytolytic subsets of TEX cells. We further explored the impact of targeting histone modifications on DNA methylation programming in CD8 T cells. These findings provide important mechanistic insights for developing novel therapeutic approaches to epigenetically reprogram TEX cells and enhance T cell immunotherapies. Supported by the Ohio State University College of Medicine and the OSU Comprehensive Cancer Center.

EdeepSADPr: an extensive deep-learning architecture for prediction of the in situ crosstalks of serine phosphorylation and ADP-ribosylation.

The in situ post-translational modification (PTM) crosstalk refers to the interactions between different types of PTMs that occur on the same residue site of a protein. The crosstalk sites generally have different characteristics from those with the single PTM type. Studies targeting the latter's features have been widely conducted, while studies on the former's characteristics are rare. For example, the characteristics of serine phosphorylation (pS) and serine ADP-ribosylation (SADPr) have been investigated, whereas those of their in situ crosstalks (pSADPr) are unknown. In this study, we collected 3,250 human pSADPr, 7,520 SADPr, 151,227pS and 80,096 unmodified serine sites and explored the features of the pSADPr sites. We found that the characteristics of pSADPr sites are more similar to those of SADPr compared to pS or unmodified serine sites. Moreover, the crosstalk sites are likely to be phosphorylated by some kinase families (e.g., AGC, CAMK, STE and TKL) rather than others (e.g., CK1 and CMGC). Additionally, we constructed three classifiers to predict pSADPr sites from the pS dataset, the SADPr dataset and the protein sequences separately. We built and evaluated five deep-learning classifiers in ten-fold cross-validation and independent test datasets. We also used the classifiers as base classifiers to develop a few stacking-based ensemble classifiers to improve performance. The best classifiers had the AUC values of 0.700, 0.914 and 0.954 for recognizing pSADPr sites from the SADPr, pS and unmodified serine sites, respectively. The lowest prediction accuracy was achieved by separating pSADPr and SADPr sites, which is consistent with the observation that pSADPr's characteristics are more similar to those of SADPr than the rest. Finally, we developed an online tool for extensively predicting human pSADPr sites based on the CNNOH classifier, dubbed EdeepSADPr. It is freely available through http://edeepsadpr.bioinfogo.org/. We expect our investigation will promote a comprehensive understanding of crosstalks.

In-depth analysis of the Sirtuin 5-regulated mouse brain malonylome and succinylome using library-free data-independent acquisitions.

Post-translational modifications (PTMs) dynamically regulate proteins and biological pathways, typically through the combined effects of multiple PTMs. Lysine residues are targeted for various PTMs, including malonylation and succinylation. However, PTMs offer specific challenges to mass spectrometry-based proteomics during data acquisition and processing. Thus, novel and innovative workflows using data-independent acquisition (DIA) ensure confident PTM identification, precise site localization, and accurate and robust label-free quantification. In this study, we present a powerful approach that combines antibody-based enrichment with comprehensive DIA acquisitions and spectral library-free data processing using directDIA (Spectronaut). Identical DIA data can be used to generate spectral libraries and comprehensively identify and quantify PTMs, reducing the amount of enriched sample and acquisition time needed, while offering a fully automated workflow. We analyzed brains from wild-type and Sirtuin 5 (SIRT5)-knock-out mice, and discovered and quantified 466 malonylated and 2211 succinylated peptides. SIRT5 regulation remodeled the acylomes by targeting 164 malonylated and 578 succinylated sites. Affected pathways included carbohydrate and lipid metabolisms, synaptic vesicle cycle, and neurodegenerative diseases. We found 48 common SIRT5-regulated malonylation and succinylation sites, suggesting potential PTM crosstalk. This innovative and efficient workflow offers deeper insights into the mouse brain lysine malonylome and succinylome.

Comparative Ubiquitination Proteomics Revealed the Salt Tolerance Mechanism in Sugar Beet Monomeric Additional Line M14.

Post-translational modifications (PTMs) are important molecular processes that regulate organismal responses to different stresses. Ubiquitination modification is not only involved in human health but also plays crucial roles in plant growth, development, and responses to environmental stresses. In this study, we investigated the ubiquitination proteome changes in the salt-tolerant sugar beet monomeric additional line M14 under salt stress treatments. Based on the expression of the key genes of the ubiquitination system and the ubiquitination-modified proteins before and after salt stress, 30 min of 200 mM NaCl treatment and 6 h of 400 mM NaCl treatment were selected as time points. Through label-free proteomics, 4711 and 3607 proteins were identified in plants treated with 200 mM NaCl and 400 mM NaCl, respectively. Among them, 611 and 380 proteins were ubiquitinated, with 1085 and 625 ubiquitination sites, in the two salt stress conditions, respectively. A quantitative analysis revealed that 70 ubiquitinated proteins increased and 47 ubiquitinated proteins decreased. At the total protein level, 42 were induced and 20 were repressed with 200 mM NaCl, while 28 were induced and 27 were repressed with 400 mM NaCl. Gene ontology, KEGG pathway, protein interaction, and PTM crosstalk analyses were performed using the differentially ubiquitinated proteins. The differentially ubiquitinated proteins were mainly involved in cellular transcription and translation processes, signal transduction, metabolic pathways, and the ubiquitin/26S proteasome pathway. The uncovered ubiquitinated proteins constitute an important resource of the plant stress ubiquitinome, and they provide a theoretical basis for the marker-based molecular breeding of crops for enhanced stress tolerance.

Simultaneous enrichment and sequential separation of O-linked glycopeptides and phosphopeptides with immobilized titanium (IV) ion affinity chromatography materials

Protein phosphorylation and O-linked glycosylation are two critical posttranslational modifications (PTMs) and they both target identical amino acid residues, generating “crosstalk”. Analysis of the crosstalk between these PTMs is crucial for deciphering their biological functions. Although several strategies have been established to enrich N-linked glycopeptides and phosphopeptides simultaneously, they are not appropriate for O-linked glycopeptides and phosphopeptides. In this study, we established a method for the simultaneous enrichment and sequential elution of O-linked glycopeptides and phosphopeptides into two fractions using commercially available immobilized titanium (IV) ion affinity chromatography (Ti4+-IMAC) materials. The established method exhibited high selectivity, repeatability, and recovery of the targeted peptides. Particularly, the overlap between the O-linked glycopeptide and phosphopeptide fractions was very low (∼3%). The application of this method to cell lysates of the colon cancer HT29 cell line resulted in a comparable number of enriched phosphopeptides as the coeluted method. However, the number of identified O-linked glycopeptides with our established method was 9.7-fold higher than that with the coelution method. Our study demonstrated that the established strategy was beneficial for the simultaneous analysis of O-linked glycopeptides and phosphopeptides, which might facilitate the study of the biological function of PTM crosstalk.

Prediction of post-translational modification cross-talk and mutation within proteins via imbalanced learning

Post-translational modification (PTM) is crucial for various cell signaling pathways and biological processes. However, the interactions between PTMs (PTM cross-talk) or PTMs and other sites (PTM mutation) are still in there infancy, with many challenges remaining unexplored. Since PTMs play a fundamental role in cell biology, many mutations cause abnormalities in many PTM sites and affect many human diseases. In this research, we propose an algorithm to improve PTM sites and PTM sites (PTM cross-talk) prediction and to study the interaction between PTM sites and mutation sites (PTM mutation). In addition to the primary network features of three-dimensional protein structure and sequence features, the dynamic features based on ENMs (elastic network models) are also used to improve model performance. Through feature selection, we reserved 48 features and developed a predictor for predicting PTM cross-talk and mutation. According to the evaluation based on PTM cross-talk, the area under the curve of our best prediction model reaches 0.911, which exceeds the state-of-art-model PCTpred. Based on the evaluation of PTM mutation, our prediction model is highly reliable, with an AUC score of 0.935. Even with the removal of the distance, the performance of our model (which is the most excellent model of the nine models, Random Forest model) is relatively stable.

The structural context of posttranslational modifications at a proteome-wide scale.

The recent revolution in computational protein structure prediction provides folding models for entire proteomes, which can now be integrated with large-scale experimental data. Mass spectrometry (MS)-based proteomics has identified and quantified tens of thousands of posttranslational modifications (PTMs), most of them of uncertain functional relevance. In this study, we determine the structural context of these PTMs and investigate how this information can be leveraged to pinpoint potential regulatory sites. Our analysis uncovers global patterns of PTM occurrence across folded and intrinsically disordered regions. We found that this information can help to distinguish regulatory PTMs from those marking improperly folded proteins. Interestingly, the human proteome contains thousands of proteins that have large folded domains linked by short, disordered regions that are strongly enriched in regulatory phosphosites. These include well-known kinase activation loops that induce protein conformational changes upon phosphorylation. This regulatory mechanism appears to be widespread in kinases but also occurs in other protein families such as solute carriers. It is not limited to phosphorylation but includes ubiquitination and acetylation sites as well. Furthermore, we performed three-dimensional proximity analysis, which revealed examples of spatial coregulation of different PTM types and potential PTM crosstalk. To enable the community to build upon these first analyses, we provide tools for 3D visualization of proteomics data and PTMs as well as python libraries for data accession and processing.

A Spin-Tip Enrichment Strategy for Simultaneous Analysis of N-Glycopeptides and Phosphopeptides from Human Pancreatic Tissues.

Mass spectrometry can provide deep coverage of post-translational modifications (PTMs), although enrichment of these modifications from complex biological matrices is often necessary due to their low stoichiometry in comparison to non-modified analytes. Most enrichment workflows of PTMs on peptides in bottom-up proteomics workflows, where proteins are enzymatically digested before the resulting peptides are analyzed, only enrich one type of modification. It is the entire complement of PTMs, however, that leads to biological functions, and enrichment of a single type of PTM may miss such crosstalk of PTMs. PTM crosstalk has been observed between protein glycosylation and phosphorylation, the two most common PTMs in human proteins and also the two most studied PTMs using mass spectrometry workflows. Using the simultaneous enrichment strategy described herein, both PTMs are enriched from post-mortem human pancreatic tissue, a complex biological matrix. Dual-functional Ti(IV)-immobilized metal affinity chromatography is used to separate various forms of glycosylation and phosphorylation simultaneously in multiple fractions in a convenient spin tip-based method, allowing downstream analyses of potential PTM crosstalk interactions. This enrichment workflow for glyco- and phosphopeptides can be applied to various sample types to achieve deep profiling of multiple PTMs and identify potential target molecules for future studies.

Post-Translational Modifications of G Protein-Coupled Receptors Revealed by Proteomics and Structural Biology.

G protein–coupled receptors (GPCRs) are a protein superfamily comprising >800 members that regulate numerous cellular and physiologic responses. GPCRs represent the largest class of therapeutic targets with implications in various diseases. Although advances in GPCR structural and pharmacological research have significantly improved our knowledge of GPCR signaling mechanisms, mapping diverse post-translational modifications (PTMs) of GPCR proteins and understanding their regulatory roles have received much less attention. Mass spectrometry-based proteomics has become the most popular technology for profiling protein PTMs in a systematic manner. Herein we provide an overview of PTM types, locations, crosstalk and dynamic regulation for different GPCRs that are characterized using proteomic and/or biochemical approaches. Our main focus is on glycosylation, phosphorylation, ubiquitination and palmitoylation that are known to modulate receptor folding, biosynthesis, trafficking, dimerization and signaling. Furthermore, we discuss the locations of specific PTM sites in the structure of a given GPCR and its signaling complex to highlight the importance of PTM regulation in the molecular basis of GPCRs, which may shed new light on structure-based drug discovery.