Search

Many factors, such as the farming systems and preslaughter rearing practices, can influence the physiological and metabolic functions of poultry with consequent effects on poultry meat quality. In this trial, label-free shotgun proteomics was used to analyze the early post-mortem Pectoralis major muscle proteomes of Ross 308 and Ranger Classic chicken strains raised under two divergent farming systems these being organic and antibiotic-free. The combination of chemometrics using partial-least-square discriminant analysis (PLS-DA) and shotgun proteomics allowed clear discrimination between the different groups. Chicken strains were discriminated by differences in the abundance of 73 and 62 proteins within the antibiotic-free and organic farming systems, respectively. The abundances of 71 and 52 proteins were impacted by the farming system within the Ross 308 and Ranger Classic chicken strains, respectively. The analyses allowed for the proposal of several putative biomarkers of meat authenticity, which were found to be related to muscle structure and energy metabolism pathways. This study is a significant step forward in elucidating the potential of proteomics profiling and chemometrics in chicken meat, which may provide opportunities for the efficient assessment of chicken authenticity.

Protein S-sulfhydration involves the regulation of various protein functions, and resolving the S-sulfhydrated proteome (persulfidome) allows for a deeper exploration of various redox regulations. Therefore, we designed a reducible covalent capture method for isolating S-sulfhydrated proteins, which can analyze the persulfidome in biological samples and monitor specific S-sulfhydrated proteins. In this study, we applied this method to reveal the S-sulfhydration levels of proteins, including 3-phosphoglyceraldehyde dehydrogenase, NFκB/p65, and nucleolin. Furthermore, this technique can be used to enrich S-sulfhydrated peptides, aiding in the determination of protein S-sulfhydration modification sites. Finally, we observed that the S-sulfhydration and oxidation of nucleolin on the C543 residue correlate with its nuclear translocation, downstream regulation of p53, Bcl-xL, and Bcl-2 RNA levels and protein expression, as well as the protective function against oxidative stress. Therefore, this method may facilitate the understanding of the regulation of protein function by redox perturbation.

In recent years, advancements in deep learning techniques have significantly expanded the structural coverage of the human proteome. GalaxySagittarius-AF translates these achievements in structure prediction into target prediction for druglike compounds by incorporating predicted structures. This web server searches the database of human protein structures using both similarity- and structure-based approaches, suggesting potential targets for a given druglike compound. In comparison to its predecessor, GalaxySagittarius, GalaxySagittarius-AF utilizes an enlarged structure database, incorporating curated AlphaFold model structures alongside their binding sites and ligands, predicted using an updated version of GalaxySite. GalaxySagittarius-AF covers a large human protein space compared to many other available computational target screening methods. The structure-based prediction method enhances the use of expanded structural information, differentiating it from other target prediction servers that rely on ligand-based methods. Additionally, the web server has undergone enhancements, operating two to three times faster than its predecessor. The updated report page provides comprehensive information on the sequence and structure of the predicted protein targets. GalaxySagittarius-AF is accessible at https://galaxy.seoklab.org/sagittarius_af without the need for registration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Information regarding protein expression and phosphorylation modifications in the bovine milk fat globule membrane is scarce, particularly throughout various lactation periods. This study employed a complete proteome and phosphoproteome between bovine colostrum and mature milk. A total of 11 proteins were seen in both protein expression and phosphorylation levels. There were 400 proteins identified in only protein expression, and 104 phosphoproteins identified in only phosphorylation levels. A total of 232 significant protein characteristics were identified within the proteome and significant phosphorylation sites within 86 phosphoproteins of the phosphoproteome. Biological activities and pathways primarily exhibited associations with the immune system. Simultaneously, a comprehensive analysis of proteins and phosphorylation sites using a multi-omics approach. Hence, the data we have obtained has the potential to expand our understanding of how the bovine milk fat globule membrane might be utilized as a beneficial component in dairy products., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Protein misfolding and aggregation can lead to various diseases. Recent studies have shed light on the aggregated protein in breast cancer pathology, which suggests that it is crucial to design chemical sensors that visualize protein aggregates in breast cancer, especially in clinical patient-derived samples. However, most reported sensors are constrained in cultured cell lines., Results: In this work, we present the development of two isophorone-based crystallization-induced-emission fluorophores for detecting proteome aggregation in breast cancer cell line and tissues biopsied from diseased patients, designated as A1 and A2. These probes exhibited viscosity sensitivity and recovered their fluorescence strongly at crystalline state. Moreover, A1 and A2 exhibit selective binding capacity and strong fluorescence for various aggregated proteins. Utilizing these probes, we detect protein aggregation in stressed breast cancer cells, xenograft mouse model of human breast cancer and clinical patient-derived samples. Notably, the fluorescence intensity of both probes light up in tumor tissues., Significance: The synthesized isophorone-based crystallization-induced-emission fluorophores, A1 and A2, enable sensitive detection of protein aggregation in breast cancer cells and tissues. In the future, aggregated proteins are expected to become indicators for early diagnosis and clinical disease monitoring of breast cancer., Competing Interests: Declaration of competing interest There are no conflicts to declare., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The missense tolerance ratio (MTR) was developed as a novel approach to assess the deleteriousness of variants. Its three-dimensional successor, MTR3D, was demonstrated powerful at discriminating pathogenic from benign variants. However, its reliance on experimental structures and homologs limited its coverage of the proteome. We have now utilized AlphaFold2 models to develop MTR3D-AF2, which covers 89.31% of proteins and 85.39% of residues across the human proteome. This work has improved MTR3D's ability to distinguish clinically established pathogenic from benign variants. MTR3D-AF2 is freely available as an interactive web server at https://biosig.lab.uq.edu.au/mtr3daf2/., (© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Organisms use organic molecules called osmolytes to adapt to environmental conditions. In vitro studies indicate that osmolytes thermally stabilize proteins, but mechanisms are controversial, and systematic studies within the cellular milieu are lacking. We analyzed Escherichia coli and human protein thermal stabilization by osmolytes in situ and across the proteome. Using structural proteomics, we probed osmolyte effects on protein thermal stability, structure and aggregation, revealing common mechanisms but also osmolyte- and protein-specific effects. All tested osmolytes (trimethylamine N-oxide, betaine, glycerol, proline, trehalose and glucose) stabilized many proteins, predominantly via a preferential exclusion mechanism, and caused an upward shift in temperatures at which most proteins aggregated. Thermal profiling of the human proteome provided evidence for intrinsic disorder in situ but also identified potential structure in predicted disordered regions. Our analysis provides mechanistic insight into osmolyte function within a complex biological matrix and sheds light on the in situ prevalence of intrinsically disordered regions., (© 2024. The Author(s).)

Determining the physicochemical properties of a protein can reveal important insights in their structure, biological functions, stability, and interactions with other molecules. Although tools for computing properties of proteins already existed, we could not find a comprehensive tool that enables the calculations of multiple properties for multiple input proteins on the proteome level at once. Facing this limitation, we developed Multiple Protein Profiler (MPP) 1.0 as an integrated tool that allows the profiling of 12 individual properties of multiple proteins in a significant manner. MPP provides a tabular and graphic visualization of properties of multiple proteins. The tool is freely accessible at https://mproteinprofiler.microbiologyandimmunology.dal.ca/ ., (© 2024. The Author(s).)

This Dataset Brief describes the computational prediction of protein structures for the ctenophore Mnemiopsis leidyi. Here, we report the proteome-scale generation of 15,333 protein structure predictions using AlphaFold, as well as an updated implementation of publicly available search, manipulation, and visualization tools for these protein structure predictions through the Mnemiopsis Genome Project Portal (https://research.nhgri.nih.gov/mnemiopsis). The utility of these predictions is demonstrated by highlighting comparisons to experimentally determined structures for the light-sensitive protein mnemiopsin 1 and the ionotropic glutamate receptor (iGluR). The application of these novel protein structure prediction methods will serve to further position non-bilaterian species such as Mnemiopsis as powerful model systems for the study of early animal evolution and human health., (© 2024 The Authors. PROTEOMICS published by Wiley‐VCH GmbH. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Gene expression in Arabidopsis is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA-binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for nearly all Arabidopsis TFs, we lack knowledge about the presence, location and transcriptional strength of their ADs 1 . To address this gap, here we use a yeast library approach to experimentally identify Arabidopsis ADs on a proteome-wide scale, and find that more than half of the Arabidopsis TFs contain an AD. We annotate 1,553 ADs, the vast majority of which are, to our knowledge, previously unknown. Using the dataset generated, we develop a neural network to accurately predict ADs and to identify sequence features that are necessary to recruit coactivator complexes. We uncover six distinct combinations of sequence features that result in activation activity, providing a framework to interrogate the subfunctionalization of ADs. Furthermore, we identify ADs in the ancient AUXIN RESPONSE FACTOR family of TFs, revealing that AD positioning is conserved in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examining function in intrinsically disordered regions and a predictive model of ADs., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

The evolving use of covalent ligands as chemical probes and therapeutic agents could greatly benefit from an expanded array of cysteine-reactive electrophiles for efficient and versatile proteome profiling. Herein, to expand the current repertoire of cysteine-reactive electrophiles, we developed a new class of strain-enabled electrophiles based on cyclopropanes. Proteome profiling has unveiled that C163 of lactate dehydrogenase A (LDHA) and C88 of adhesion regulating molecule 1 (ADRM1) are ligandable residues to modulate the protein functions. Moreover, fragment-based ligand discovery (FBLD) has revealed that one fragment ( Y-35 ) shows strong reactivity toward C66 of thioredoxin domain-containing protein 12 (TXD12), and its covalent binding has been demonstrated to impact its downstream signal pathways. TXD12 plays a pivotal role in enabling Y-35 to exhibit its antisurvival and antiproliferative effects. Finally, dicarbonitrile-cyclopropane has been demonstrated to be an electrophilic warhead in the development of GSTO1-involved dual covalent inhibitors, which is promising to alleviate drug resistance.

AlphaFind is a web-based search engine that provides fast structure-based retrieval in the entire set of AlphaFold DB structures. Unlike other protein processing tools, AlphaFind is focused entirely on tertiary structure, automatically extracting the main 3D features of each protein chain and using a machine learning model to find the most similar structures. This indexing approach and the 3D feature extraction method used by AlphaFind have both demonstrated remarkable scalability to large datasets as well as to large protein structures. The web application itself has been designed with a focus on clarity and ease of use. The searcher accepts any valid UniProt ID, Protein Data Bank ID or gene symbol as input, and returns a set of similar protein chains from AlphaFold DB, including various similarity metrics between the query and each of the retrieved results. In addition to the main search functionality, the application provides 3D visualizations of protein structure superpositions in order to allow researchers to instantly analyze the structural similarity of the retrieved results. The AlphaFind web application is available online for free and without any registration at https://alphafind.fi.muni.cz., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

E3 ubiquitin ligases recognize substrates through their short linear motifs termed degrons. While degron-signaling has been a subject of extensive study, resources for its systematic screening are limited. To bridge this gap, we developed DEGRONOPEDIA, a web server that searches for degrons and maps them to nearby residues that can undergo ubiquitination and disordered regions, which may act as protein unfolding seeds. Along with an evolutionary assessment of degron conservation, the server also reports on post-translational modifications and mutations that may modulate degron availability. Acknowledging the prevalence of degrons at protein termini, DEGRONOPEDIA incorporates machine learning to assess N-/C-terminal stability, supplemented by simulations of proteolysis to identify degrons in newly formed termini. An experimental validation of a predicted C-terminal destabilizing motif, coupled with the confirmation of a post-proteolytic degron in another case, exemplifies its practical application. DEGRONOPEDIA can be freely accessed at degronopedia.com., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Phase separation inside mammalian cells regulates the formation of the biomolecular condensates that are related to gene expression, signalling, development and disease. However, a large population of endogenous condensates and their candidate phase-separating proteins have yet to be discovered in a quantitative and high-throughput manner. Here we demonstrate that endogenously expressed biomolecular condensates can be identified across a cell's proteome by sorting proteins across varying oligomeric states. We employ volumetric compression to modulate the concentrations of intracellular proteins and the degree of crowdedness, which are physical regulators of cellular biomolecular condensates. The changes in degree of the partition of proteins into condensates or phase separation led to varying oligomeric states of the proteins, which can be detected by coupling density gradient ultracentrifugation and quantitative mass spectrometry. In total, we identified 1,518 endogenous condensate proteins, of which 538 have not been reported before. Furthermore, we demonstrate that our strategy can identify condensate proteins that respond to specific biological processes., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

De novo design of complex protein folds using solely computational means remains a substantial challenge 1 . Here we use a robust deep learning pipeline to design complex folds and soluble analogues of integral membrane proteins. Unique membrane topologies, such as those from G-protein-coupled receptors 2 , are not found in the soluble proteome, and we demonstrate that their structural features can be recapitulated in solution. Biophysical analyses demonstrate the high thermal stability of the designs, and experimental structures show remarkable design accuracy. The soluble analogues were functionalized with native structural motifs, as a proof of concept for bringing membrane protein functions to the soluble proteome, potentially enabling new approaches in drug discovery. In summary, we have designed complex protein topologies and enriched them with functionalities from membrane proteins, with high experimental success rates, leading to a de facto expansion of the functional soluble fold space., (© 2024. The Author(s).)

Predicting the binding of ligands to the human proteome via reverse-docking methods enables the understanding of ligand's interactions with potential protein targets in the human body, thereby facilitating drug repositioning and the evaluation of potential off-target effects or toxic side effects of drugs. In this study, we constructed 11 reverse docking pipelines by integrating site prediction tools (PointSite and SiteMap), docking programs (Glide and AutoDock Vina), and scoring functions (Glide, Autodock Vina, RTMScore, DeepRMSD, and OnionNet-SFCT), and then thoroughly benchmarked their predictive capabilities. The results show that the Glide_SFCT (PS) pipeline exhibited the best target prediction performance based on the atomic structure models in AlphaFold2 human proteome. It achieved a success rate of 27.8% when considering the top 100 ranked prediction. This pipeline effectively narrows the range of potential targets within the human proteome, laying a foundation for drug target prediction, off-target assessment, and toxicity prediction, ultimately boosting drug development. By facilitating these critical aspects of drug discovery and development, our work has the potential to ultimately accelerate the identification of new therapeutic agents and improve drug safety., (© 2024 The Protein Society.)

Tandem mass tags (TMT) are widely used in proteomics to simultaneously quantify multiple samples in a single experiment. The tags can be easily added to the primary amines of peptides/proteins through chemical reactions. In addition to amines, TMT reagents also partially react with the hydroxyl groups of serine, threonine, and tyrosine residues under alkaline conditions, which significantly compromises the analytical sensitivity and precision. Under alkaline conditions, reducing the TMT molar excess can partially mitigate overlabeling of histidine-free peptides, but has a limited effect on peptides containing histidine and hydroxyl groups. Here, we present a method under acidic conditions to suppress overlabeling while efficiently labeling amines, using only one-fifth of the TMT amount recommended by the manufacturer. In a deep-scale analysis of a yeast/human two-proteome sample, we systematically evaluated our method against the manufacturer's method and a previously reported TMT-reduced method. Our method reduced overlabeled peptides by 9-fold and 6-fold, respectively, resulting in the substantial enhancement in peptide/protein identification rates. More importantly, the quantitative accuracy and precision were improved as overlabeling was reduced, endowing our method with greater statistical power to detect 42% and 12% more statistically significant yeast proteins compared to the standard and TMT-reduced methods, respectively. Mass spectrometric data have been deposited in the ProteomeXchange Consortium via the iProX partner repository with the data set identifier PXD047052.

Glycoproteome analysis at a site-specific level and proteome scale stands out as a highly promising approach for gaining insights into the intricate roles of glycans in biological systems. Recent years have witnessed an upsurge in the development of innovative methodologies tailored for precisely this purpose. Breakthroughs in mass spectrometry-based glycoproteomic techniques, enabling the identification, quantification, and systematic exploration of site-specific glycans, have significantly enhanced our capacity to comprehensively and thoroughly characterize glycoproteins. In this short review, we delve into novel tools in advancing site-specific glycoproteomic analysis and summarize pertinent studies published in the past two years. Lastly, we discuss the ongoing challenges and outline future prospects in the field, considering both the analytical strategies of mass spectrometry and the tools employed for data interpretation., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Weiqian Cao reports financial support and article publishing charges were provided by National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Depending on the respective research question, LC-MS/MS based bottom-up proteomics poses challenges from the initial biological sample all the way to data evaluation. The focus of this study was to investigate the influence of sample preparation techniques and data analysis parameters on protein identification in Tribolium castaneum by applying free software proteomics platform Max Quant. Multidimensional protein extraction strategies in combination with electrophoretic or chromatographic off-line protein pre-fractionation were applied to enhance the spectrum of isolated proteins from T. castaneum and reduce the effect of co-elution and ion suppression effects during nano-LC-MS/MS measurements of peptides. For comprehensive data analysis, MaxQuant was used for protein identification and R for data evaluation. A wide range of parameters were evaluated to gain reproducible, reliable, and significant protein identifications. A simple phosphate buffer, pH 8, containing protease and phosphatase inhibitor cocktail and application of gentle extraction conditions were used as a first extraction step for T.castaneum proteins. Furthermore, a two-dimensional extraction procedure in combination with electrophoretic pre-fractionation of extracted proteins and subsequent in-gel digest resulted in almost 100% increase of identified proteins when compared to chromatographic fractionation as well as one-pot-analysis. The additionally identified proteins could be assigned to new molecular functions or cell compartments, emphasizing the positive effect of extended sample preparation in bottom-up proteomics. Besides the number of peptides during post-processing, MaxQuant's Match between Runs exhibited a crucial effect on the number of identified proteins. A maximum relative standard deviation of 2% must be considered for the data analysis. Our work with Tribolium castaneum larvae demonstrates that sometimes - depending on matrix and research question - more complex and time-consuming sample preparation can be advantageous for isolation and identification of additional proteins in bottom-up proteomics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Low-complexity domains (LCDs) in proteins are typically enriched in one or two predominant amino acids. As a result, LCDs often exhibit unusual structural/biophysical tendencies and can occupy functional niches. However, for each organism, protein sequences must be compatible with intracellular biomolecules and physicochemical environment, both of which vary from organism to organism. This raises the possibility that LCDs may occupy sequence spaces in select organisms that are otherwise prohibited in most organisms. Here, we report a comprehensive survey and functional analysis of LCDs in all known reference proteomes (>21k organisms), with added focus on rare and unusual types of LCDs. LCDs were classified according to both the primary amino acid and secondary amino acid in each LCD sequence, facilitating detailed comparisons of LCD class frequencies across organisms. Examination of LCD classes at different depths (i.e., domain of life, organism, protein, and per-residue levels) reveals unique facets of LCD frequencies and functions. To our surprise, all 400 LCD classes occur in nature, although some are exceptionally rare. A number of rare classes can be defined for each domain of life, with many LCD classes appearing to be eukaryote-specific. Certain LCD classes were consistently associated with identical functions across many organisms, particularly in eukaryotes. Our analysis methods enable simultaneous, direct comparison of all LCD classes between individual organisms, resulting in a proteome-scale view of differences in LCD frequencies and functions. Together, these results highlight the remarkable diversity and functional specificity of LCDs across all known life forms., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Cascarina, Ross. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Plant-based adhesives, such as those made from wheat, have been prominently used for books and paper-based objects and are also used as conservation adhesives. Starch paste originates from starch granules, whereas flour paste encompasses the entire wheat endosperm proteome, offering strong adhesive properties due to gluten proteins. From a conservation perspective, understanding the precise nature of the adhesive is vital as the longevity, resilience, and reaction to environmental changes can differ substantially between starch- and flour-based pastes. We devised a proteomics method to discern the protein content of these pastes. Protocols involved extracting soluble proteins using 0.5 M NaCl and 30 mM Tris-HCl solutions and then targeting insoluble proteins, such as gliadins and glutenins, with a buffer containing 7 M urea, 2 M thiourea, 4% CHAPS, 40 mM Tris, and 75 mM DTT. Flour paste's proteome is diverse (1942 proteins across 759 groups), contrasting with starch paste's predominant starch-associated protein makeup (218 proteins in 58 groups). Transformation into pastes reduces proteomes' complexity. Testing on historical bookbindings confirmed the use of flour-based glue, which is rich in gluten and serpins. High levels of deamidation were detected, particularly for glutamine residues, which can impact the solubility and stability of the glue over time. The mass spectrometry proteomics data have been deposited to the ProteomeXchange, Consortium (http://proteomecentral.proteomexchange.org) via the MassIVE partner repository with the data set identifier MSV000093372 (ftp://MSV000093372@massive.ucsd.edu).

With the rapid expansion of sequencing of genomes, the functional annotation of proteins becomes a bottleneck in understanding proteomes. The Chromosome-centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome and find functional annotations for them. However, until now there are still 1137 identified human proteins without functional annotation, called uPE1 proteins. Sequence alignment was insufficient to predict their functions, and the crystal structures of most proteins were unavailable. In this study, we demonstrated a new functional annotation strategy, AlphaFun, based on structural alignment using deep-learning-predicted protein structures. Using this strategy, we functionally annotated 99% of the human proteome, including the uPE1 proteins and missing proteins, which have not been identified yet. The accuracy of the functional annotations was validated using the known-function proteins. The uPE1 proteins shared similar functions to the known-function PE1 proteins and tend to express only in very limited tissues. They are evolutionally young genes and thus should conduct functions only in specific tissues and conditions, limiting their occurrence in commonly studied biological models. Such functional annotations provide hints for functional investigations on the uPE1 proteins. This proteome-wide-scale functional annotation strategy is also applicable to any other species.

Detergent-based workflows incorporating sodium dodecyl sulfate (SDS) necessitate additional steps for detergent removal ahead of mass spectrometry (MS). These steps may lead to variable protein recovery, inconsistent enzyme digestion efficiency, and unreliable MS signals. To validate a detergent-based workflow for quantitative proteomics, we herein evaluate the precision of a bottom-up sample preparation strategy incorporating cartridge-based protein precipitation with organic solvent to deplete SDS. The variance of data-independent acquisition (SWATH-MS) data was isolated from sample preparation error by modelling the variance as a function of peptide signal intensity. Our SDS-assisted cartridge workflow yield a coefficient of variance (CV) of 13%-14%. By comparison, conventional (detergent-free) in-solution digestion increased the CV to 50%; in-gel digestion provided lower CVs between 14% and 20%. By filtering peptides predicting to display lower precision, we further enhance the validity of data in global comparative proteomics. These results demonstrate the detergent-based precipitation workflow is a reliable approach for in depth, label-free quantitative proteome analysis., (© 2024 The Authors. Proteomics published by Wiley‐VCH GmbH.)

Phosphorylation of proteins on tyrosine (Tyr) residues evolved in metazoan organisms as a mechanism of coordinating tissue growth 1 . Multicellular eukaryotes typically have more than 50 distinct protein Tyr kinases that catalyse the phosphorylation of thousands of Tyr residues throughout the proteome 1-3 . How a given Tyr kinase can phosphorylate a specific subset of proteins at unique Tyr sites is only partially understood 4-7 . Here we used combinatorial peptide arrays to profile the substrate sequence specificity of all human Tyr kinases. Globally, the Tyr kinases demonstrate considerable diversity in optimal patterns of residues surrounding the site of phosphorylation, revealing the functional organization of the human Tyr kinome by substrate motif preference. Using this information, Tyr kinases that are most compatible with phosphorylating any Tyr site can be identified. Analysis of mass spectrometry phosphoproteomic datasets using this compendium of kinase specificities accurately identifies specific Tyr kinases that are dysregulated in cells after stimulation with growth factors, treatment with anti-cancer drugs or expression of oncogenic variants. Furthermore, the topology of known Tyr signalling networks naturally emerged from a comparison of the sequence specificities of the Tyr kinases and the SH2 phosphotyrosine (pTyr)-binding domains. Finally we show that the intrinsic substrate specificity of Tyr kinases has remained fundamentally unchanged from worms to humans, suggesting that the fidelity between Tyr kinases and their protein substrate sequences has been maintained across hundreds of millions of years of evolution., (© 2024. The Author(s).)

This perspective begins with a speculative consideration of the properties of the earliest proteins to appear during evolution. What did these primitive proteins look like, and how were they of benefit to early forms of life? I proceed to hypothesize that primitive proteins have been preserved through evolution and now serve diverse functions important to the dynamics of cell morphology and biological regulation. The primitive nature of these modern proteins is easy to spot. They are composed of a limited subset of the 20 amino acids used by traditionally evolved proteins and thus are of low sequence complexity. This chemical simplicity limits protein domains of low sequence complexity to forming only a crude and labile type of protein structure currently hidden from the computational powers of machine learning. I conclude by hypothesizing that this structural weakness represents the underlying virtue of proteins that, at least for the moment, constitute the dark matter of the proteome., (© 2024 McKnight; Published by Cold Spring Harbor Laboratory Press.)

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

Plasma membrane proteins (PMPs) play pivotal roles in various cellular events and are crucial in disease pathogenesis, making their comprehensive characterization vital for biomedical research. However, the hydrophobic nature and low expression levels of PMPs pose challenges for conventional enrichment methods, hindering their identification and functional profiling. In this study, we presented a novel TurboID-based enrichment approach for PMPs that helped overcoming some of the existing limitations. We evaluated the efficacy of TurboID and its modified form, TurboID-START, in PMP enrichment, achieving efficient and targeted labelling of PMPs without the need for stable cell line generation. This approach resulted reduction in non-specific biotinylation events, leading to improved PMP enrichment and enabled assessment of the subcellular proteome associated with the plasma membrane. Our findings paved the way for studies targeting the dynamic nature of the plasma membrane proteome and aiming to capture transient associations of proteins with the plasma membrane. The novel TurboID-based enrichment approach presented here offers promising prospects for in-depth investigations into PMPs and their roles in cellular processes., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

One-third of protein domains in the CATH database contain a recently discovered tertiary topological motif: non-covalent lasso entanglements, in which a segment of the protein backbone forms a loop closed by non-covalent interactions between residues and is threaded one or more times by the N- or C-terminal backbone segment. Unknown is how frequently this structural motif appears across the proteomes of organisms. And the correlation of these motifs with various classes of protein function and biological processes have not been quantified. Here, using a combination of protein crystal structures, AlphaFold2 predictions, and Gene Ontology terms we show that in E. coli, S. cerevisiae and H. sapiens that 71%, 52% and 49% of globular proteins contain one-or-more non-covalent lasso entanglements in their native fold, and that some of these are highly complex with multiple threading events. Further, proteins containing these tertiary motifs are consistently enriched in certain functions and biological processes across these organisms and depleted in others, strongly indicating an influence of evolutionary selection pressures acting positively and negatively on the distribution of these motifs. Together, these results demonstrate that non-covalent lasso entanglements are widespread and indicate they may be extensively utilized for protein function and subcellular processes, thus impacting phenotype., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Post-translational oxidation of methionine residues can destabilize proteins or modify their functions. Although levels of methionine oxidation can provide important information regarding the structural integrity and regulation of proteins, their quantitation is often challenging as analytical procedures in and of themselves can artifactually oxidize methionines. Here, we develop a mass-spectrometry-based method called Methionine Oxidation by Blocking with Alkylation (MObBa) that quantifies methionine oxidation by selectively alkylating and blocking unoxidized methionines. Thus, alkylated methionines can be used as a stable proxy for unoxidized methionines. Using proof of concept experiments, we demonstrate that MObBa can be used to measure methionine oxidation levels within individual synthetic peptides and on proteome-wide scales. MObBa may provide a straightforward experimental strategy for mass spectrometric quantitation of methionine oxidation.

Methods for selective covalent modification of amino acids on proteins can enable a diverse array of applications, spanning probes and modulators of protein function to proteomics 1-3 . Owing to their high nucleophilicity, cysteine and lysine residues are the most common points of attachment for protein bioconjugation chemistry through acid-base reactivity 3,4 . Here we report a redox-based strategy for bioconjugation of tryptophan, the rarest amino acid, using oxaziridine reagents that mimic oxidative cyclization reactions in indole-based alkaloid biosynthetic pathways to achieve highly efficient and specific tryptophan labelling. We establish the broad use of this method, termed tryptophan chemical ligation by cyclization (Trp-CLiC), for selectively appending payloads to tryptophan residues on peptides and proteins with reaction rates that rival traditional click reactions and enabling global profiling of hyper-reactive tryptophan sites across whole proteomes. Notably, these reagents reveal a systematic map of tryptophan residues that participate in cation-π interactions, including functional sites that can regulate protein-mediated phase-separation processes., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Glycoproteins in urine have the potential to provide a rich class of informative molecules for studying human health and disease. Despite this promise, the urine glycoproteome has been largely uncharacterized. Here, we present the analysis of glycoproteins in human urine using LC-MS/MS-based intact glycopeptide analysis, providing both the identification of protein glycosites and characterization of the glycan composition at specific glycosites. Gene enrichment analysis reveals differences in biological processes, cellular components, and molecular functions in the urine glycoproteome versus the urine proteome, as well as differences based on the major glycan class observed on proteins. Meta-heterogeneity of glycosylation is examined on proteins to determine the variation in glycosylation across multiple sites of a given protein with specific examples of individual sites differing from the glycosylation trends in the overall protein. Taken together, this dataset represents a potentially valuable resource as a baseline characterization of glycoproteins in human urine for future urine glycoproteomics studies., (© 2024. The Author(s).)

The tendency for proteins to form aggregates is an inherent part of every proteome and arises from the self-assembly of short protein segments called aggregation-prone regions (APRs). While posttranslational modifications (PTMs) have been implicated in modulating protein aggregation, their direct role in APRs remains poorly understood. In this study, we used a combination of proteome-wide computational analyses and biophysical techniques to investigate the potential involvement of PTMs in aggregation regulation. Our findings reveal that while most PTM types are disfavored near APRs, N-glycosylation is enriched and evolutionarily selected, especially in proteins prone to misfolding. Experimentally, we show that N-glycosylation inhibits the aggregation of peptides in vitro through steric hindrance. Moreover, mining existing proteomics data, we find that the loss of N-glycans at the flanks of APRs leads to specific protein aggregation in Neuro2a cells. Our findings indicate that, among its many molecular functions, N-glycosylation directly prevents protein aggregation in higher eukaryotes.

The outer membrane in Gram-negative bacteria consists of an asymmetric phospholipid-lipopolysaccharide bilayer that is densely packed with outer-membrane β-barrel proteins (OMPs) and lipoproteins 1 . The architecture and composition of this bilayer is closely monitored and is essential to cell integrity and survival 2-4 . Here we find that SlyB, a lipoprotein in the PhoPQ stress regulon, forms stable stress-induced complexes with the outer-membrane proteome. SlyB comprises a 10 kDa periplasmic β-sandwich domain and a glycine zipper domain that forms a transmembrane α-helical hairpin with discrete phospholipid- and lipopolysaccharide-binding sites. After loss in lipid asymmetry, SlyB oligomerizes into ring-shaped transmembrane complexes that encapsulate β-barrel proteins into lipid nanodomains of variable size. We find that the formation of SlyB nanodomains is essential during lipopolysaccharide destabilization by antimicrobial peptides or acute cation shortage, conditions that result in a loss of OMPs and compromised outer-membrane barrier function in the absence of a functional SlyB. Our data reveal that SlyB is a compartmentalizing transmembrane guard protein that is involved in cell-envelope proteostasis and integrity, and suggest that SlyB represents a larger family of broadly conserved lipoproteins with 2TM glycine zipper domains with the ability to form lipid nanodomains., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Intrinsically disordered proteins and regions (collectively, IDRs) are pervasive across proteomes in all kingdoms of life, help to shape biological functions and are involved in numerous diseases. IDRs populate a diverse set of transiently formed structures and defy conventional sequence-structure-function relationships 1 . Developments in protein science have made it possible to predict the three-dimensional structures of folded proteins at the proteome scale 2 . By contrast, there is a lack of knowledge about the conformational properties of IDRs, partly because the sequences of disordered proteins are poorly conserved and also because only a few of these proteins have been characterized experimentally. The inability to predict structural properties of IDRs across the proteome has limited our understanding of the functional roles of IDRs and how evolution shapes them. As a supplement to previous structural studies of individual IDRs 3 , we developed an efficient molecular model to generate conformational ensembles of IDRs and thereby to predict their conformational properties from sequences 4,5 . Here we use this model to simulate nearly all of the IDRs in the human proteome. Examining conformational ensembles of 28,058 IDRs, we show how chain compaction is correlated with cellular function and localization. We provide insights into how sequence features relate to chain compaction and, using a machine-learning model trained on our simulation data, show the conservation of conformational properties across orthologues. Our results recapitulate observations from previous studies of individual protein systems and exemplify how to link-at the proteome scale-conformational ensembles with cellular function and localization, amino acid sequence, evolutionary conservation and disease variants. Our freely available database of conformational properties will encourage further experimental investigation and enable the generation of hypotheses about the biological roles and evolution of IDRs., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Natural products perennially serve as prolific sources of drug leads and chemical probes, fueling the development of numerous therapeutics. Despite their scarcity, natural products that modulate protein function through covalent interactions with lysine residues hold immense potential to unlock new therapeutic interventions and advance our understanding of the biological processes governed by these modifications. Phloroglucinol meroterpenoids constitute one of the most expansive classes of natural products, displaying a plethora of biological activities. However, their mechanism of action and cellular targets have, until now, remained elusive. In this study, we detail the concise biomimetic synthesis, computational mechanistic insights, physicochemical attributes, kinetic parameters, molecular mechanism of action, and functional cellular targets of several phloroglucinol meroterpenoids. We harness synthetic clickable analogues of natural products to probe their disparate proteome-wide reactivity and subcellular localization through in-gel fluorescence scanning and cell imaging. By implementing sample multiplexing and a redesigned lysine-targeting probe, we streamline a quantitative activity-based protein profiling, enabling the direct mapping of global reactivity and ligandability of proteinaceous lysines in human cells. Leveraging this framework, we identify numerous lysine-meroterpenoid interactions in breast cancer cells at tractable protein sites across diverse structural and functional classes, including those historically deemed undruggable. We validate that phloroglucinol meroterpenoids perturb biochemical functions through stereoselective and site-specific modification of lysines in proteins vital for breast cancer metabolism, including lipid signaling, mitochondrial respiration, and glycolysis. These findings underscore the broad potential of phloroglucinol meroterpenoids for targeting functional lysines in the human proteome.

The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality of the underlying data, the addition of experimental structural information, the inclusion of new data download options, and an upgraded graphical interface. DescribePROT currently covers 19 structural and functional descriptors for proteins in 273 reference proteomes generated by 11 accurate and complementary predictive tools. Users can search our resource in multiple ways, interact with the data using the graphical interface, and download data at various scales including individual proteins, entire proteomes, and whole database. The annotations in DescribePROT are useful for a broad spectrum of studies that include investigations of protein structure and function, development and validation of predictive tools, and to support efforts in understanding molecular underpinnings of diseases and development of therapeutics. DescribePROT can be freely accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Homorepeats (or polyX), protein segments containing repetitions of the same amino acid, are abundant in proteomes from all kingdoms of life and are involved in crucial biological functions as well as several neurodegenerative and developmental diseases. Mainly inserted in disordered segments of proteins, the structure/function relationships of homorepeats remain largely unexplored. In this review, we summarize present knowledge for the most abundant homorepeats, highlighting the role of the inherent structure and the conformational influence exerted by their flanking regions. Recent experimental and computational methods enable residue-specific investigations of these regions and promise novel structural and dynamic information for this elusive group of proteins. This information should increase our knowledge about the structural bases of phenomena such as liquid-liquid phase separation and trinucleotide repeat disorders., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Cellular functions are mediated by protein-protein interactions, and mapping the interactome provides fundamental insights into biological systems. Affinity purification coupled to mass spectrometry is an ideal tool for such mapping, but it has been difficult to identify low copy number complexes, membrane complexes and complexes that are disrupted by protein tagging. As a result, our current knowledge of the interactome is far from complete, and assessing the reliability of reported interactions is challenging. Here we develop a sensitive high-throughput method using highly reproducible affinity enrichment coupled to mass spectrometry combined with a quantitative two-dimensional analysis strategy to comprehensively map the interactome of Saccharomyces cerevisiae. Thousand-fold reduced volumes in 96-well format enabled replicate analysis of the endogenous GFP-tagged library covering the entire expressed yeast proteome 1 . The 4,159 pull-downs generated a highly structured network of 3,927 proteins connected by 31,004 interactions, doubling the number of proteins and tripling the number of reliable interactions compared with existing interactome maps 2 . This includes very-low-abundance epigenetic complexes, organellar membrane complexes and non-taggable complexes inferred by abundance correlation. This nearly saturated interactome reveals that the vast majority of yeast proteins are highly connected, with an average of 16 interactors. Similar to social networks between humans, the average shortest distance between proteins is 4.2 interactions. AlphaFold-Multimer provided novel insights into the functional roles of previously uncharacterized proteins in complexes. Our web portal ( www.yeast-interactome.org ) enables extensive exploration of the interactome dataset., (© 2023. The Author(s).)

Common workflows in bottom-up proteomics require homogenization of tissue samples to gain access to the biomolecules within the cells. The homogenized tissue samples often contain many different cell types, thereby representing an average of the natural proteome composition, and rare cell types are not sufficiently represented. To overcome this problem, small-volume sampling and spatial resolution are needed to maintain a better representation of the sample composition and their proteome signatures. Using nanosecond infrared laser ablation, the region of interest can be targeted in a three-dimensional (3D) fashion, whereby the spatial information is maintained during the simultaneous process of sampling and homogenization. In this study, we ablated 40 μm thick consecutive layers directly from the scalp through the cortex of embryonic mouse heads and analyzed them by subsequent bottom-up proteomics. Extra- and intracranial ablated layers showed distinct proteome profiles comprising expected cell-specific proteins. Additionally, known cortex markers like SOX2, KI67, NESTIN, and MAP2 showed a layer-specific spatial protein abundance distribution. We propose potential new marker proteins for cortex layers, such as MTA1 and NMRAL1. The obtained data confirm that the new 3D tissue sampling and homogenization method is well suited for investigating the spatial proteome signature of tissue samples in a layerwise manner. Characterization of the proteome composition of embryonic skin and bone structures, meninges, and cortex lamination in situ enables a better understanding of molecular mechanisms of development during embryogenesis and disease pathogenesis.

DNA-encoded chemical library (DEL) has been extensively used for lead compound discovery for decades in academia and industry. Incorporating an electrophile warhead into DNA-encoded compounds recently permitted the discovery of covalent ligands that selectively react with a particular cysteine residue. However, noncysteine residues remain underexplored as modification sites of covalent DELs. Herein, we report the design and utility of tyrosine-targeting DELs of 67 million compounds. Proteome-wide reactivity analysis of tyrosine-reactive sulfonyl fluoride (SF) covalent probes suggested three enzymes (phosphoglycerate mutase 1, glutathione s-transferase 1, and dipeptidyl peptidase 3) as models of tyrosine-targetable proteins. Enrichment with SF-functionalized DELs led to the identification of a series of tyrosine-targeting covalent inhibitors of the model enzymes. In-depth mechanistic investigation revealed their novel modes of action and reactive ligand-accessible hotspots of the enzymes. Our strategy of combining activity-based proteome profiling and covalent DEL enrichment (ABPP-CoDEL), which generated selective covalent binders against a variety of target proteins, illustrates the potential use of this methodology in further covalent drug discovery.

Pathogens have evolved sophisticated strategies to manipulate host signaling pathways, including the phenomenon of molecular mimicry, where pathogen-derived biomolecules imitate host biomolecules. In this study, we resurrected, updated, and optimized a sequence-based bioinformatics pipeline to identify potential molecular mimicry candidates between humans and 32 pathogenic species whose proteomes' 3D structure predictions were available at the start of this study. We observed considerable variation in the number of mimicry candidates across pathogenic species, with pathogenic bacteria exhibiting fewer candidates compared to fungi and protozoans. Further analysis revealed that the candidate mimicry regions were enriched in solvent-accessible regions, highlighting their potential functional relevance. We identified a total of 1,878 mimicked regions in 1,439 human proteins, and clustering analysis indicated diverse target proteins across pathogen species. The human proteins containing mimicked regions revealed significant associations between these proteins and various biological processes, with an emphasis on host extracellular matrix organization and cytoskeletal processes. However, immune-related proteins were underrepresented as targets of mimicry. Our findings provide insights into the broad range of host-pathogen interactions mediated by molecular mimicry and highlight potential targets for further investigation. This comprehensive analysis contributes to our understanding of the complex mechanisms employed by pathogens to subvert host defenses and we provide a resource to assist researchers in the development of novel therapeutic strategies., Competing Interests: The authors declare that they have no competing interests., (© 2023 Rich et al.)

The ubiquity of mass spectrometry-based bottom-up proteomic analyses as a component of biological investigation mandates the validation of methodologies that increase acquisition efficiency, improve sample coverage, and enhance profiling depth. Chromatographic separation is often ignored as an area of potential improvement, with most analyses relying on traditional reversed-phase liquid chromatography (RPLC); this consistent reliance on a single chromatographic paradigm fundamentally limits our view of the observable proteome. Herein, we build upon early reports and validate porous graphitic carbon chromatography (PGC) as a facile means to substantially enhance proteomic coverage without changes to sample preparation, instrument configuration, or acquisition methods. Analysis of offline fractionated cell line digests using both separations revealed an increase in peptide and protein identifications by 43% and 24%, respectively. Increased identifications provided more comprehensive coverage of cellular components and biological processes independent of protein abundance, highlighting the substantial quantity of proteomic information that may go undetected in standard analyses. We further utilize these data to reveal that label-free quantitative analyses using RPLC separations alone may not be reflective of actual protein constituency. Together, these data highlight the value and comprehension offered through PGC-MS proteomic analyses. RAW proteomic data have been uploaded to the MassIVE repository with the primary accession code MSV000091495.

Advances in chemoproteomic technology have revealed covalent interactions between small molecules and protein nucleophiles, primarily cysteine, on a proteome-wide scale. Most chemoproteomic screening approaches are indirect, relying on competition between electrophilic fragments and a minimalist electrophilic probe with inherently limited proteome coverage. Here we develop a chemoproteomic platform for direct electrophile-site identification based on enantiomeric pairs of clickable arylsulfonyl fluoride probes. Using stereoselective site modification as a proxy for ligandability in intact cells, we identify 634 tyrosines and lysines within functionally diverse protein sites, liganded by structurally diverse probes. Among multiple validated sites, we discover a chiral probe that modifies Y228 in the MYC binding site of the epigenetic regulator WDR5, as revealed by a high-resolution crystal structure. A distinct chiral probe stimulates tumour cell phagocytosis by covalently modifying Y387 in the recently discovered immuno-oncology target APMAP. Our work provides a deep resource of ligandable tyrosines and lysines for the development of covalent chemical probes., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Proteus mirabilis is a gram-negative bacterium particularly known for its unique swarming ability. The swarming gives the bacteria ability to enhance adherence to the catheter surface and epithelium cells of the urethra to cause catheter associated urinary tract infections. P. mirabilis has evolved resistant to antibiotics. Additionally, there is an approved vaccine against P. mirabilis , thus demanding for identification of new vaccine targets. This gram-negative bacterium consists of 19,502 core proteins, out of which 19,063 are redundant proteins and remaining 439 are non-redundant proteins. The non-redundant proteins have 21 proteins present on the cell surface out of which 11 proteins are virulent. Antigenicity analysis predicted only 2 proteins as antigenic (fimbrial biogenesis outer membrane usher protein and ligand-gated channel protein). Four and seven B-cells epitopes were predicted from the former and later proteins, respectively. The predicted B-cells epitopes were used for T- cells epitopes prediction. The predicted epitopes were linked to each other through GPGPG linkers and joined with cholera toxin beta subunit adjuvant. A multi-epitopes vaccine construct consisting of 226 residues was docked with MHC-I, MHC-II and TLR-4. The best docked complex in each case has binding energy of -714.6, -744.6 and -829.5 kcal/mol, respectively. Moreover, the docking results were validated through molecular dynamics simulation and binding free energies estimation. The net energy of -137.2 kcal/mol was calculated for vaccine-MHC-I complex, -133.39 kcal/mol for vaccine-MHC-II and -158.68 kcal/mol for vaccine-TLR-4 complex. The designed vaccine construct could provoke immune responses against targeted pathogen and may be used in experimental testing.Communicated by Ramaswamy H. Sarma.

Covalent chemistry represents an attractive strategy for expanding the ligandability of the proteome, and chemical proteomics has revealed numerous electrophile-reactive cysteines on diverse human proteins. Determining which of these covalent binding events affect protein function, however, remains challenging. Here we describe a base-editing strategy to infer the functionality of cysteines by quantifying the impact of their missense mutation on cancer cell proliferation. The resulting atlas, which covers more than 13,800 cysteines on more than 1,750 cancer dependency proteins, confirms the essentiality of cysteines targeted by covalent drugs and, when integrated with chemical proteomic data, identifies essential, ligandable cysteines in more than 160 cancer dependency proteins. We further show that a stereoselective and site-specific ligand targeting an essential cysteine in TOE1 inhibits the nuclease activity of this protein through an apparent allosteric mechanism. Our findings thus describe a versatile method and valuable resource to prioritize the pursuit of small-molecule probes with high function-perturbing potential., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

In proteomics research, with advantages including short digestion times and reusable applications, immobilized enzyme reactors (IMERs) have been paid increasing attention. However, traditional IMERs ignore the reasonable spatial arrangement of trypsin on the supporting matrixes, resulting in the partial overlapping of the active domain on trypsin and reducing digesting efficiency. In this work, a DNA tetrahedron (DNA TET)-based IMER Fe 3 O 4 -GO-AuNPs-DNA TET-Trypsin was designed and prepared. The distance between vertices of DNA TETs effectively controls the distribution of trypsin on the nanomaterials; thus, highly efficient protein digestion and accurate quantitative results can be achieved. Compared to the in-solution digestion (12-16 h), the sequence coverage of bovine serum albumin was up to 91% after a 2-min digestion by the new IMER. In addition, 3328 proteins and 18,488 peptides can be identified from HeLa cell protein extract after a 20-min digestion. For the first time, human growth hormone reference material was rapidly and accurately quantified after a 4-h digestion by IMER. Therefore, this new IMER has great application potential in proteomics research and SI traceable quantification.

Importance: Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth in Escherichia coli . We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions in E. coli and compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, is near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow in E. coli ., Competing Interests: The authors declare no conflict of interest.

Post-translational modifications (PTMs) of biomacromolecules can be useful for understanding the processes by which a relatively small number of individual genes in a particular genome can generate enormous biological complexity in different organisms. The proteomes of barley and the brewing process were investigated by different techniques. However, their diverse and complex PTMs remain understudied. As standard analytical approaches have limitations, innovative analytical approaches need to be developed and applied in PTM studies. To make further progress in this field, it is necessary to specify the sites of modification, as well as to characterize individual isoforms with increased selectivity and sensitivity. This review summarizes advances in the PTM analysis of barley proteins, particularly those involving mass spectrometric detection. Our focus is on monitoring phosphorylation, glycation, and glycosylation, which critically influence functional behavior in metabolism and regulation in organisms.

Background: Aberrant protein kinase regulation leading to abnormal substrate phosphorylation is associated with several human diseases. Despite the promise of therapies targeting kinases, many human kinases remain understudied. Most existing computational tools predicting phosphorylation cover less than 50% of known human kinases. They utilize local feature selection based on protein sequences, motifs, domains, structures, and/or functions, and do not consider the heterogeneous relationships of the proteins. In this work, we present KSFinder, a tool that predicts kinase-substrate links by capturing the inherent association of proteins in a network comprising 85% of the known human kinases. We also postulate the potential role of two understudied kinases based on their substrate predictions from KSFinder., Methods: KSFinder learns the semantic relationships in a phosphoproteome knowledge graph using a knowledge graph embedding algorithm and represents the nodes in low-dimensional vectors. A multilayer perceptron (MLP) classifier is trained to discern kinase-substrate links using the embedded vectors. KSFinder uses a strategic negative generation approach that eliminates biases in entity representation and combines data from experimentally validated non-interacting protein pairs, proteins from different subcellular locations, and random sampling. We assess KSFinder's generalization capability on four different datasets and compare its performance with other state-of-the-art prediction models. We employ KSFinder to predict substrates of 68 "dark" kinases considered understudied by the Illuminating the Druggable Genome program and use our text-mining tool, RLIMS-P along with manual curation, to search for literature evidence for the predictions. In a case study, we performed functional enrichment analysis for two dark kinases - HIPK3 and CAMKK1 using their predicted substrates., Results: KSFinder shows improved performance over other kinase-substrate prediction models and generalized prediction ability on different datasets. We identified literature evidence for 17 novel predictions involving an understudied kinase. All of these 17 predictions had a probability score ≥0.7 (nine at >0.9, six at 0.8-0.9, and two at 0.7-0.8). The evaluation of 93,593 negative predictions (probability ≤0.3) identified four false negatives. The top enriched biological processes of HIPK3 substrates relate to the regulation of extracellular matrix and epigenetic gene expression, while CAMKK1 substrates include lipid storage regulation and glucose homeostasis., Conclusions: KSFinder outperforms the current kinase-substrate prediction tools with higher kinase coverage. The strategically developed negatives provide a superior generalization ability for KSFinder. We predicted substrates of 432 kinases, 68 of which are understudied, and hypothesized the potential functions of two dark kinases using their predicted substrates., Competing Interests: The authors declare there are no competing interests., (©2023 Anandakrishnan et al.)

Bioorthogonal labeling and click chemistry techniques allow the detailed examination of cellular physiology through tagging and visualizing newly synthesized proteins. Here, we describe three methods applying bioorthogonal non-canonical amino acid tagging and fluorescent non-canonical amino acid tagging to quantify protein synthesis in microglia. We describe steps for cell seeding and labeling. We then detail microscopy, flow cytometry, and Western blotting techniques. These methods can be easily adapted for other cell types to explore cellular physiology in health and disease. For complete details on the use and execution of this protocol, please refer to Evans et al. (2021). 1 ., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)