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Simplified diagram of 20 types of PLMs with molecular structures of ligands conjugated to lysine residues. AeC: Twenty types of PLMs classified into three categories: UbUbLs (A), acylation (B) and other PLMs (C). Ub-UbLs, ubiquitin and ubiquitin-like modifications.
Source publication
Post-translational modifications (PTMs) occurring at protein lysine residues, or protein lysine modifications (PLMs), play critical roles in regulating biological processes. Due to the explosive expansion of the amount of PLM substrates and the discovery of novel PLM types, here we greatly updated our previous studies, and presented a much more int...
Contexts in source publication
Context 1
... we found 284,780 PLM events occurring at 234,062 lysine residues of 53,501 proteins for 20 types of PLMs across 176 eukaryotes and prokaryotes (Table S1). Then we classified the PLMs into three categories: 1) four types of ubiquitin and ubiquitin-like modifications (Ub-UbLs), 2) nine types of acylations, and 3) seven types of other PLMs (Fig. 2). Among them, acylations and Ub-UbLs account for the vast majority of PLM events: the former possesses 141,276 (49.61%) acylation sites and the latter contains 130,194 (45.72%) sites. More specifically, ubiquitination (121,742 sites, 42.75%) and acetylation (111,253 sites, 39.07%), two extensively studied PLMs, still occupy a large ...
Context 2
... acylations depend on the similar acyl-CoA metabolic intermediates, such as acetyl-CoA (Ac-CoA), succinyl-CoA and malony-CoA (Hirschey and Zhao, 2015), it can be expected that they are more likely to occur in the same locations. Furthermore, a comprehensive analysis of the crosstalks among different PLMs in same tissues or cell lines was performed (Fig. S2). The result showed that the co-occurrences of multiple PLMs on the same lysine residue significantly occurred in majority of tissues or cell lines. Moreover, the in situ crosstalks between different PLMs in same tissues or cell lines are consistent with that in all identified PLM sites. Since multiple PLMs are significantly ...
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Citations
... HDACs are classified into class I (HDAC1, 2, 3, and 8), class IIa (HDAC4, 5, 7, and 9), class IIb (HDAC6 and 10), and class IV (HDAC11), according to differences in structure, enzymatic function, subcellular localization, and expression pattern. HDACs catalyze the removal of acyl groups from lysine residues of histones, non-histone proteins, and polyamines [1][2][3][4], thus playing a crucial role in various diseases [5]. The dysregulation of HDAC activity, especially that of class I HDACs, has been related to the development of different kinds of cancers, both hematological and solid tumors. ...
Histone deacetylase 6 (HDAC6) is increasingly recognized for its potential in targeted disease therapy. This study delves into the mechanistic and structural nuances of HDAC6 inhibition by difluoromethyl-1,3,4-oxadiazole (DFMO) derivatives, a class of non-hydroxamic inhibitors with remarkable selectivity and potency. Employing a combination of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS) kinetic experiments, comprehensive enzymatic characterizations, and X-ray crystallography, we dissect the intricate details of the DFMO-HDAC6 interaction dynamics. More specifically, we find that the chemical structure of a DMFO and the binding mode of its difluoroacetylhydrazide derivative are crucial in determining the predominant hydrolysis mechanism. Our findings provide additional insights into two different mechanisms of DFMO hydrolysis, thus contributing to a better understanding of the HDAC6 inhibition by oxadiazoles in disease modulation and therapeutic intervention.
... 34 and the web-based GPS-Uber databases (http:// gpsuber.biocuckoo.cn/online.php), 35 predicting that ITPKB K793 and K818 might be potential ubiquitination sites near their binding domain with Trim25. The ITPKB K793R and K818R mutants were then generated, and the single-site mutation (K793R or K818R) showed little effect on polyubiquitination, while the two K to R mutations (2KR) almost completely abolished K48-linked polyubiquitination in ITPKB (Fig. 5l-m). ...
Temozolomide (TMZ) represents a standard-of-care chemotherapeutic agent in glioblastoma (GBM). However, the development of drug resistance constitutes a significant hurdle in the treatment of malignant glioma. Although specific innovative approaches, such as immunotherapy, have shown favorable clinical outcomes, the inherent invasiveness of most gliomas continues to make them challenging to treat. Consequently, there is an urgent need to identify effective therapeutic targets for gliomas to overcome chemoresistance and facilitate drug development. This investigation used mass spectrometry to examine the proteomic profiles of six pairs of GBM patients who underwent standard-of-care treatment and surgery for both primary and recurrent tumors. A total of 648 proteins exhibiting significant differential expression were identified. Gene Set Enrichment Analysis (GSEA) unveiled notable alterations in pathways related to METABOLISM_OF_LIPIDS and BIOLOGICAL_OXIDATIONS between the primary and recurrent groups. Validation through glioma tissue arrays and the Xiangya cohort confirmed substantial upregulation of inositol 1,4,5-triphosphate (IP3) kinase B (ITPKB) in the recurrence group, correlating with poor survival in glioma patients. In TMZ-resistant cells, the depletion of ITPKB led to an increase in reactive oxygen species (ROS) related to NADPH oxidase (NOX) activity and restored cell sensitivity to TMZ. Mechanistically, the decreased phosphorylation of the E3 ligase Trim25 at the S100 position in recurrent GBM samples accounted for the weakened ITPKB ubiquitination. This, in turn, elevated ITPKB stability and impaired ROS production. Furthermore, ITPKB depletion or the ITPKB inhibitor GNF362 effectively overcome TMZ chemoresistance in a glioma xenograft mouse model. These findings reveal a novel mechanism underlying TMZ resistance and propose ITPKB as a promising therapeutic target for TMZ-resistant GBM.
... For differential expression analysis of acetylated proteins (DAPs), we applied strict criteria, including a p-value less than 0.05 and a fold change greater than 1.5 or less than 0.67, to identify DAPs. To analyze correlations of posttranslational modifications (PTMs) in our data, identify novel acetylation sites, and explore overlaps with other PTM types, we utilized the protein lysine modifications database (PLMD; version 3.0 4 ) (Xu et al., 2017). Protein domains were analyzed using the InterPro database, 5 while subcellular distribution prediction was performed using the Wolf Psort tool (version 1.0 6 ). ...
Introduction
Chronic intermittent hypoxia (CIH) can negatively affect hippocampal function through various molecular mechanisms. Protein acetylation, a frequently occurring modification, plays crucial roles in synaptic plasticity and cognitive processes. However, the global protein acetylation induced by CIH in the hippocampus and its specific effects on hippocampal function and behavior remain poorly understood.
Methods
To address this gap, we conducted a study using liquid chromatography-tandem mass spectrometry to analyze the lysine acetylome and proteome of the hippocampus in healthy adult mice exposed to intermittent hypoxia for 4 weeks (as a CIH model) compared to normoxic mice (as a control).
Results
We identified and quantified a total of 2,184 lysine acetylation sites in 1,007 proteins. Analysis of these acetylated proteins revealed disturbances primarily in oxidative phosphorylation, the tricarboxylic acid (TCA) cycle, and glycolysis, all of which are localized exclusively to mitochondria. Additionally, we observed significant changes in the abundance of 21 proteins, some of which are known to be associated with cognitive impairments.
Discussion
This study helps to elucidate the molecular mechanisms underlying CIH-induced changes in protein acetylation in the hippocampus. By providing valuable insights into the pathophysiological processes associated with CIH and their impacts on hippocampal function, our findings contribute to a better understanding of the consequences of CIH-induced changes in protein acetylation in the hippocampus and the potential role of CIH in cognitive impairment.
... Researchers in the field of scientific computations can use available experimental PTM data in publicly available databases for building different prediction models for example or running some experimental operations (6). To assure the quality of the data, they can use available databases to collect experimentally validated malonylation sites of proteins such as database PTM (dbPTM) (34), Protein lysine/k modification database (PLMD) (35) and compendium of protein lysine/k modification (CPLM) (36) as follows. In addition to the basic information and specifics on PLM sites of each protein entry, augmented annotations from 102 additional resources have been included to cover 13 aspects. ...
The post-translational modifications occur as crucial molecular regulatory mechanisms utilized to regulate diverse cellular processes. Malonylation of proteins, a reversible post-translational modification of lysine/k residues, is linked to a variety of biological functions, such as cellular regulation and pathogenesis. This modification plays a crucial role in metabolic pathways, mitochondrial functions, fatty acid oxidation and other life processes. However, accurately identifying malonylation sites is crucial to understand the molecular mechanism of malonylation, and the experimental identification can be a challenging and costly task. Recently, approaches based on machine learning (ML) have been suggested to address this issue. It has been demonstrated that these procedures improve accuracy while lowering costs and time constraints. However, these approaches also have specific shortcomings, including inappropriate feature extraction out of protein sequences, high-dimensional features and inefficient underlying classifiers. As a result, there is an urgent need for effective predictors and calculation methods. In this study, we provide a comprehensive analysis and review of existing prediction models, tools and benchmark datasets for predicting malonylation sites in protein sequences followed by a comparison study. The review consists of the specifications of benchmark datasets, explanation of features and encoding methods, descriptions of the predictions approaches and their embedding ML or deep learning models and the description and comparison of the existing tools in this domain. To evaluate and compare the prediction capability of the tools, a new bunch of data has been extracted based on the most updated database and the tools have been assessed based on the extracted data. Finally, a hybrid architecture consisting of several classifiers including classical ML models and a deep learning model has been proposed to ensemble the prediction results. This approach demonstrates the better performance in comparison with all prediction tools included in this study (the source codes of the models presented in this manuscript are available in https://github.com/Malonylation).
Database URL: https://github.com/A-Golshan/Malonylation
... nih. gov/ 28529 077/) [46] was used to extract the ubiquitination, acetylation, and sumoylation sites of the selected gene. As the data were deduced, the duplicate PTM sites were removed manually as there are some sites that undergo two different functions when ubiquitinated. ...
... To get to the depth of that, firstly, the structure of BRCA1-BARD1 was retrieved from the PDB database, 1JM7, and active sites was studied for the same using FTSite. Three active sites were visualized using PyMOL, namely, Active (29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46). Moreover, as the growing characterization of BRCA1-dependent ubiquitination is widely studied on lysine residues, thus, we targeted lysine residues from these three active sites. ...
Lysine-based post-translational modification (PTM) such as acylation, acetylation, deamination, methylation, SUMOylation, and ubiquitination has proven to be a major regulator of gene expression, chromatin structure, protein stability, protein–protein interaction, protein degradation, and cellular localization. However, besides all the PTMs, ubiquitination stands as the second most common PTM after phosphorylation that is involved in the etiology of neurodegenerative diseases (NDDs) namely, Alzheimer’s disease (AD) and Parkinson’s disease (PD). NDDs are characterized by the accumulation of misfolded protein aggregates in the brain that lead to disease-related gene mutation and irregular protein homeostasis. The ubiquitin–proteasome system (UPS) is in charge of degrading these misfolded proteins, which involve an interplay of E1, E2, E3, and deubiquitinase enzymes. Impaired UPS has been commonly observed in NDDs and E3 ligases are the key members of the UPS, thus, dysfunction of the same can accelerate the neurodegeneration process. Therefore, the aim of this study is firstly, to find E3 ligases that are common in both AD and PD through data mining. Secondly, to study the impact of mutation on its structure and function. The study deciphered 74 E3 ligases that were common in both AD and PD. Later, 10 hub genes were calculated of which protein–protein interaction, pathway enrichment, lysine site prediction, domain, and motif analysis were performed. The results predicted BRCA1, PML, and TRIM33 as the top three putative lysine-modified E3 ligases involved in AD and PD pathogenesis. However, based on structural characterization, BRCA1 was taken further to study RING domain mutation that inferred K32Y, K32L, K32C, K45V, K45Y, and K45G as potential mutants that alter the structural and functional ability of BRCA1 to interact with Ube2k, E2-conjugating enzyme. The most probable mutant observed after molecular dynamics simulation of 50 ns is K32L. Therefore, our study concludes BRCA1, a potential E3 ligase common in AD and PD, and RING domain mutation at sites K32 and K45 possibly disturbs its interaction with its E2, Ube2k.
Graphical Abstract
Graphical representation of all the steps involved to study mutation in the RING domain of BRCA1 which is a common E3 ligase observed in Alzheimer’s disease and Parkinson’s disease.
... Protein posttranslational modification (PTM) of proteins includes acetylation, glycosylation, methylation, succinylation, ubiquitin, and other types [1]. Among them, protein methylation is catalyzed by methyltransferase, and the methyl donor S-adenosylmethionine transfers methyl to other substrate protein amino acid residues, thus regulating the stability and function of cells [2]. ...
Methyltransferase-like 21C (METTL21C) is a member of the non-histone methyltransferase superfamily, which mainly mediates the methylation of lysine (Lys) residues. The main types of modification are Lys dimethylation and trimethylation. However, at present, most of the studies on METTL21C are focused on humans and mice, and there are few reports on poultry. Therefore, chicken embryo fibroblasts (DF-1) were selected as the object of study. To explore the function of chicken METTL21C (chMETTL21C) in the proliferation of DF-1 cells, flow cytometry and qPCR were used to detect the function of chicken METTL21C in the proliferation of DF-1 cells. The results showed that overexpression of METTL21C blocked the cell cycle in the G1max S phase, thus inhibiting cell proliferation. In addition, based on proteomic analysis, stable overexpression of METTL21C may inhibit the proliferation of DF-1 cells by mediating lysine trimethylation of proliferation-related proteins phosphorylated adapter RNA export protein (PHAX), nucleoside diphosphate kinases (NDPKs), eukaryotic transcription extension factor (eukaryotic translation elongation factor 1A,e EF1A), and inversin (Invs). Through immunoprecipitation (co-IP) and liquid chromatography-mass spectrometry (LC-MS/MS) analysis, METTL21C-mediated PHAX Lys-381 methylation was confirmed to be involved in the regulation of DF-1 cell proliferation. The results of this study provide a reference for analyzing the methylation function of METTL21C and the mechanism of regulating the growth and development of chicken cells.
... Further studies have shown the important role of lysine acetylation in regulating bacterial metabolism Liu et al., 2021;Van-Drisse & Escalante-Semerena, 2019). When searching the acetylome database, E. coli GK has multiple lysine acetylation sites identified by proteomic studies (Xu et al., 2017). However, the role of lysine acetylation in regulating GK functions remains largely unknown. ...
... There are no lysine residues in human GK homologous to K214 and K216 of E. coli GK. K346 of human GK has been identified to be acetylated by proteomic studies (Xu et al., 2017), which is also located at the entrance of the active site. However, the opening of the human GK active site is much wider than that of E. coli GK. ...
Glucokinase (GK) catalyzes the phosphorylation of glucose to form glucose‐6‐phosphate as the substrate of glycolysis for energy production. Acetylation of lysine residues in Escherichia coli GK has been identified at multiple sites by a series of proteomic studies, but the impact of acetylation on GK functions remains largely unknown. In this study, we applied the genetic code expansion strategy to produce site‐specifically acetylated GK variants which naturally exist in cells. Enzyme assays and kinetic analyses showed that lysine acetylation decreases the GK activity, mostly resulting from acetylation of K214 and K216 at the entrance of the active site, which impairs the binding of substrates. We also compared results obtained from the glutamine substitution method and the genetic acetyllysine incorporation approach, showing that glutamine substitution is not always effective for mimicking acetylated lysine. Further genetic studies as well as in vitro acetylation and deacetylation assays were performed to determine acetylation and deacetylation mechanisms, which showed that E. coli GK could be acetylated by acetyl‐phosphate without enzymes and deacetylated by CobB deacetylase.
... The dataset was retrieved from the Protein Lysine Modification Database (PLMD) [29], which includes Mus musculus and M. tuberculosis Kglu proteins collected from two previous studies [1,4]. We initially obtained 715 Kglu sites from 211 proteins from the PLMD database, and then used CD-hit to remove similar sequences with 30% sequence identity to obtain 208 non-redundant proteins, of which 707 Kglu sites were used as positive samples and 4,369 non-Kglu sites were used as non-positive samples. ...
Background
Lysine glutarylation (Kglu) is one of the most important Post-translational modifications (PTMs), which plays significant roles in various cellular functions, including metabolism, mitochondrial processes, and translation. Therefore, accurate identification of the Kglu site is important for elucidating protein molecular function. Due to the time-consuming and expensive limitations of traditional biological experiments, computational-based Kglu site prediction research is gaining more and more attention.
Results
In this paper, we proposed GBDT_KgluSite, a novel Kglu site prediction model based on GBDT and appropriate feature combinations, which achieved satisfactory performance. Specifically, seven features including sequence-based features, physicochemical property-based features, structural-based features, and evolutionary-derived features were used to characterize proteins. NearMiss-3 and Elastic Net were applied to address data imbalance and feature redundancy issues, respectively. The experimental results show that GBDT_KgluSite has good robustness and generalization ability, with accuracy and AUC values of 93.73%, and 98.14% on five-fold cross-validation as well as 90.11%, and 96.75% on the independent test dataset, respectively.
Conclusion
GBDT_KgluSite is an effective computational method for identifying Kglu sites in protein sequences. It has good stability and generalization ability and could be useful for the identification of new Kglu sites in the future. The relevant code and dataset are available at https://github.com/flyinsky6/GBDT_KgluSite.
... The data sets were constructed by Chen et al., 13 based on the PLMD database. 25 The homologous sequences were eliminated by using CD-HIT 26 based on a threshold of sequence identity as 30%. Each sequence is a peptide of 21 residues in length centered with a residue K. ...
As one of the most important post-translational modifications (PTM), lysine acetylation (Kace) plays an important role in various biological activities. Traditional experimental methods for identifying Kace sites are inefficient and expensive. Instead, several machine learning methods have been developed for Kace site prediction, and hand-crafted features have been used to encode the protein sequences. However, there are still two challenges: the complex biological information may be under-represented by these manmade features and the small sample issue of some species needs to be addressed. We propose a novel model, MSTL-Kace, which was developed based on transfer learning strategy with pretrained bidirectional encoder representations from transformers (BERT) model. In this model, the high-level embeddings were extracted from species-specific BERT models, and a two-stage fine-tuning strategy was used to deal with small sample issue. Specifically, a domain-specific BERT model was pretrained using all of the sequences in our data sets, which was then fine-tuned, or two-stage fine-tuned based on the training data set of each species to obtain the species-specific BERT models. Afterward, the embeddings of residues were extracted from the fine-tuned model and fed to the different downstream learning algorithms. After comparison, the best model for the six prokaryotic species was built by using a random forest. The results for the independent test sets show that our model outperforms the state-of-the-art methods on all six species. The source codes and data for MSTL-Kace are available at https://github.com/leo97king/MSTL-Kace.
... It is also important to visualize the location of each identified PTMs on the protein(s) of interest and how these modifications are impacted by experimental conditions. It is also necessary to be able to easily compare experimental PTM data with publicly available PTM databases such as PhosphoSitePlus (18), Protein Lysine Modification Database (PLMD) (19), CarbonylDB (20), GlyConnect (21) and Uniprot (https://www.uniprot.org/) (22). ...
... For selection of PTM databases (Step 12, Fig 1B) we used PhosphoSitePlus (https://www.phosphosite.org/) (18), Protein Lysine Modification Database (PLMD) using downloaded data (19), CarbonylDB (http://carbonyldb.missouri.edu/CarbonylDB/index.php/) (20), GlyConnect (https://glyconnect.expasy.org/) ...
To facilitate analysis and sharing of mass spectrometry (MS)-based proteomics data we created tools called CURTAIN ( https://curtain.proteo.info ) and CURTAIN-PTM ( https://curtainptm.proteo.info ). These enable the non-MS expert to interactively peruse volcano plots; deconvolute primary experimental data to individual replicates that can be visualized in bar charts or violin plots allowing statistical analysis; and export of plots in SVG format. They also permit assessment of experimental quality by correlation matrix and profile plot. Within CURTAIN, the user can analyze domain structure, AlphaFold predicted structure, reported interactors, relative expression, disease and pharmaceutical links, and mutagenesis information on all selected hits. Moreover, CURTAIN-PTM permits the comparison of all identified PTM sites on protein(s) of interest with PTM information contained within selected databases. For phosphorylation site analysis CURTAIN-PTM links with the kinase library to predict upstream kinases that phosphorylate sites of interest. We provide examples of the utility of CURTAIN and CURTAIN-PTM in analyzing how targeted degradation of the PPM1H Rab phosphatase that counteracts the Parkinson’s LRRK2 kinase impacts cellular protein levels and phosphorylation sites. We reanalyzed a ubiquitylation dataset, characterizing the PINK1-Parkin pathway activation in primary neurons, revealing new data of interest not highlighted previously. CURTAIN and CURTAIN-PTM are free to use and open-source and will enable researchers to share and maximize the analysis and impact of their proteomics data. We advocate that differential expression proteomic data should be published containing a shareable CURTAIN web-link, allowing readers to better explore their data.
Significance Statement
To enable non-experts to better share and explore mass spectrometry data, we have generated using open-source software, interactive tools termed CURTAIN and CURTAIN-PTM. These tools enable users’ to save their analysis sessions with a sharable unique web-link, enabling other researchers to visualize and further analyze these datasets. These links can also be reported in publications allowing readers to further survey the reported data. We discuss benefits for the research community of publishing proteomic data containing a shareable web-link.
