NBA-Palm: prediction of palmitoylation site implemented in Na?ve Bayes algorithm

Background  

Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design.     

CSS-Palm: palmitoylation site prediction with a clustering and scoring strategy (CSS)

SUMMARY: Palmitoylation is an important post-translational lipid modification of proteins. Unlike prenylation and myristoylation, palmitoylation is a reversible covalent modification, allowing for dynamic regulation of multiple complex cellular systems. However, in vivo or in vitro identification of palmitoylation sites is usually time-consuming and labor-intensive. So in silico predictions could help to narrow down the possible palmitoylation sites, which can be used to guide further experimental design. Previous studies suggested that there is no unique canonical motif for palmitoylation sites, so we hypothesize that the bona fide pattern might be compromised by heterogeneity of multiple structural determinants with different features. Based on this hypothesis, we partition the known palmitoylation sites into three clusters and score the similarity between the query peptide and the training ones based on BLOSUM62 matrix. We have implemented a computer program for palmitoylation site prediction, Clustering and Scoring Strategy for Palmitoylation Sites Prediction (CSS-Palm) system, and found that the program's prediction performance is encouraging with highly positive Jack-Knife validation results (sensitivity 82.16% and specificity 83.17% for cut-off score 2.6). Our analyses indicate that CSS-Palm could provide a powerful and effective tool to studies of palmitoylation sites. AVAILABILITY: CSS-Palm is implemented in PHP/PERL+MySQL and can be freely accessed at http://bioinformatics.lcd-ustc.org/css_palm/ CONTACT: yaoxb@ustc.edu.cn; xuyn@bmb.uga.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bionformatics online.     

A general user interface for prediction servers of proteins' post-translational modification sites

Post-translational modifications (PTMs) of proteins play essential roles in governing the functions and dynamics of proteins and are implicated in many cellular processes. Several types of PTMs have been investigated through computational approaches, including phosphorylation, sumoylation, palmitoylation, and lysine and arginine methylation, among others. Because the large diversity in the user interfaces (UIs) of different prediction servers for PTMs could possibly hinder experimental biologists in using these servers, we propose to develop a protocol for a unified UI for PTM prediction servers, based on our own work and that of other groups on PTM site prediction. By following this protocol, tool developers can provide a uniform UI regardless of the PTM types and the underlying computational algorithms. With such uniformity in the UI, experimental biologists would be able to use any PTM prediction server compliant with this protocol once they had learned to use one of them. It takes a typical PTM prediction server compliant with this unified UI several minutes to calculate the prediction results for a protein 1,000 amino acids in length.     

Prediction and analysis of protein palmitoylation sites

Palmitoylation is a universal and important lipid modification, involving a series of basic cellular processes, such as membrane trafficking, protein stability and protein aggregation. With the avalanche of new protein sequences generated in the post genomic era, it is highly desirable to develop computational methods for rapidly and effectively identifying the potential palmitoylation sites of uncharacterized proteins so as to timely provide useful information for revealing the mechanism of protein palmitoylation. By using the Incremental Feature Selection approach based on amino acid factors, conservation, disorder feature, and specific features of palmitoylation site, a new predictor named IFS-Palm was developed in this regard. The overall success rate thus achieved by jackknife test on a newly constructed benchmark dataset was 90.65%. It was shown via an in-depth analysis that palmitoylation was intimately correlated with the feature of the upstream residue directly adjacent to cysteine site as well as the conservation of amino acid cysteine. Meanwhile, the protein disorder region might also play an import role in the post-translational modification. These findings may provide useful insights for revealing the mechanisms of palmitoylation.     

Assays of protein palmitoylation

Protein palmitoylation plays an important role in the structure and function of a wide array of proteins. Unlike other lipid modifications, protein palmitoylation is highly dynamic and cycles of palmitoylation and depalmitoylation can regulate protein function and localization. The dynamic nature of palmitoylation is poorly resolved because of limitations in assay methods. Here, we discuss various methods that can be used to measure protein palmitoylation and identify sites of palmitoylation. We describe new methodology based on "fatty acyl exchange labeling" in which palmitate is removed via hydroxylamine-mediated cleavage of the palmitoyl-thioester bond and then exchanged with a sulfhydryl-specific labeling compound. The techniques are highly sensitive and allow for quantitative estimates of palmitoylation. Unlike other techniques used to assay posttranslational modifications, the techniques we have developed can label all sites of modification with a variety of probes, radiolabeled or non-radioactive, and can be used to assay the palmitoylation of proteins from tissue samples.     

棕榈酰化蛋白及蛋白质的棕榈酰化研究进展

蛋白质S-棕榈酰化是最常见的具有16碳脂肪酸棕榈酸酯的脂质修饰形式,调节蛋白质的运输和功能。文中主要概括从植物到哺乳动物中发现的具有棕榈酰基转移酶活性的保守DHHC蛋白家族,并介绍蛋白质棕榈酰化的研究方法,及检测棕榈酰化蛋白质的位点预测方法(CSS-Palm、NBA-Palm、TermiNator2)、放射性标记法(用3H棕榈酸酯或125I-IC16棕榈酸酯)和非放射性标记法(化学标记和质谱法),总结蛋白棕榈酰化的抑制技术以及抑制剂类型(包括2-溴棕榈酸酯、浅蓝菌素和衣霉素)。同时概括蛋白棕榈酰化在植物胁迫中的响应,展望其在植物抗逆中的应用前景。     

Structure-based computational analysis of protein binding sites for function and druggability prediction

Protein binding sites are the places where molecular interactions occur. Thus, the analysis of protein binding sites is of crucial importance to understand the biological processes proteins are involved in. Herein, we focus on the computational analysis of protein binding sites and present structure-based methods that enable function prediction for orphan proteins and prediction of target druggability. We present the general ideas behind these methods, with a special emphasis on the scopes and limitations of these methods and their validation. Additionally, we present some successful applications of computational binding site analysis to emphasize the practical importance of these methods for biotechnology/bioeconomy and drug discovery.     

Glycosylation site prediction using ensembles of Support Vector Machine classifiers

Background  

Glycosylation is one of the most complex post-translational modifications (PTMs) of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of glycosylation sites from amino acid sequences.     

Presynaptic trafficking of synaptotagmin I is regulated by protein palmitoylation

Protein palmitoylation plays a critical role in sorting and targeting of several proteins to pre- and postsynaptic sites. In this study, we have analyzed the role of palmitoylation in trafficking of synaptotagmin I and its modulation by synaptic activity. We found that palmitoylation of N-terminal cysteines contributed to sorting of synaptotagmin I to an intracellular vesicular compartment at the presynaptic terminal. Presynaptic targeting is a unique feature of N-terminal sequences of synaptotagmin I because the palmitoylated N terminus of synaptotagmin VII failed to localize to presynaptic sites. We also found that palmitate was stably associated with both synaptotagmin I and SNAP-25 and that rapid neuronal depolarization did not affect palmitate turnover on these proteins. However, long-term treatment with drugs that either block synaptic activity or disrupt SNARE complex assembly modulated palmitoylation and accumulation of synaptotagmin I at presynaptic sites. We conclude that palmitoylation is involved in trafficking of specific elements involved in transmitter release and that distinct mechanisms regulate addition and removal of palmitate on select neuronal proteins.     

Palmitoylation and its effect on the GTPase-activating activity and conformation of RGS2

Regulator of G protein signaling (RGS) proteins act as negative regulators of G protein coupled signaling by accelerating the GTPase activity of the G proteins subunits. Reversible palmitoylation, a common post-translational modification for various components of the G protein-coupled signaling pathway, plays an important role in the modulation of protein activity. RGS2 appears to act selectively to increase the GTPase activity of Gq when single turnover assays are preformed in solution. However, less attention has been paid to the effects of palmitoylation of RGS2 on its conformation and GTPase-activating activity. Studies of palmitoylation on a series of RGS2 mutants in which alanine was substituted for cysteine revealed cysteine 106, 116 and 199 to be multiple putative palmitoylation sites in RGS2, the efficiency of palmitate incorporation being about 60% at each individual palmitoylation site. Palmitoylation of RGS2 inhibited the GTPase-activating activity toward a GTPase-deficient R183C mutant of Gq in vitro, but mutation of cysteine 116 eliminated the inhibition of palmitoylation on GTPase-activating activity of RGS2. The effect of palmitoylation on conformation of RGS2 was examined by monitoring spectra of the intrinsic fluorescence and Circular Dichroism. The results suggested that GTPase-activating activity change of RGS2 might be related to conformational change of RGS2 upon palmitoylation. Taken together, these results provided clear and strong experimental evidence for palmitoylation sites in RGS2 as well as for effect of palmitoylation on the GTPase-activating activity and conformation of RGS2.     

Validation of the reliability of computational O-GlcNAc prediction

O-GlcNAcylation is an inducible, highly dynamic and reversible posttranslational modification, which regulates numerous cellular processes such as gene expression, translation, immune reactions, protein degradation, protein–protein interaction, apoptosis, and signal transduction. In contrast to N-linked glycosylation, O-GlcNAcylation does not display a strict amino acid consensus sequence, although serine or threonine residues flanked by proline and valine are preferred sites of O-GlcNAcylation. Based on this information, computational prediction tools of O-GlcNAc sites have been developed. Here, we retrospectively assessed the performance of two available O-GlcNAc prediction programs YinOYang 1.2 server and OGlcNAcScan by comparing their predictions for recently discovered experimentally validated O-GlcNAc sites. Both prediction programs efficiently identified O-GlcNAc sites situated in an environment resembling the consensus sequence P-P-V-[ST]-T-A. However, both prediction programs revealed numerous false negative O-GlcNAc predictions when the site of modification was located in an amino acid sequence differing from the known consensus sequence. By searching for a common sequence motif, we found that O-GlcNAcylation of nucleocytoplasmic proteins preferably occurs at serine and threonine residues flanked downstream by proline and valine and upstream by one to two alanines followed by a stretch of serine and threonine residues. However, O-GlcNAcylation of proteins located in the mitochondria or in the secretory lumen occurs at different sites and does not follow a distinct consensus sequence. Thus, our study indicates the limitations of the presently available computational prediction methods for O-GlcNAc sites and suggests that experimental validation is mandatory. Continuously update and further development of available databases will be the key to improve the performance of O-GlcNAc site prediction.     

Computational Prediction of Candidate Proteins for S-Nitrosylation in Arabidopsis thaliana

Nitric oxide (NO) is an important signaling molecule that regulates many physiological processes in plants. One of the most important regulatory mechanisms of NO is S-nitrosylation—the covalent attachment of NO to cysteine residues. Although the involvement of cysteine S-nitrosylation in the regulation of protein functions is well established, its substrate specificity remains unknown. Identification of candidates for S-nitrosylation and their target cysteine residues is fundamental for studying the molecular mechanisms and regulatory roles of S-nitrosylation in plants. Several experimental methods that are based on the biotin switch have been developed to identify target proteins for S-nitrosylation. However, these methods have their limits. Thus, computational methods are attracting considerable attention for the identification of modification sites in proteins. Using GPS-SNO version 1.0, a recently developed S-nitrosylation site-prediction program, a set of 16,610 candidate proteins for S-nitrosylation containing 31,900 S-nitrosylation sites was isolated from the entire Arabidopsis proteome using the medium threshold. In the compartments “chloroplast,” “CUL4-RING ubiquitin ligase complex,” and “membrane” more than 70% of the proteins were identified as candidates for S-nitrosylation. The high number of identified candidates in the proteome reflects the importance of redox signaling in these compartments. An analysis of the functional distribution of the predicted candidates showed that proteins involved in signaling processes exhibited the highest prediction rate. In a set of 46 proteins, where 53 putative S-nitrosylation sites were already experimentally determined, the GPS-SNO program predicted 60 S-nitrosylation sites, but only 11 overlap with the results of the experimental approach. In general, a computer-assisted method for the prediction of targets for S-nitrosylation is a very good tool; however, further development, such as including the three dimensional structure of proteins in such analyses, would improve the identification of S-nitrosylation sites.     

Palmitoylated TMX and calnexin target to the mitochondria-associated membrane

The mitochondria-associated membrane (MAM) is a domain of the endoplasmic reticulum (ER) that mediates the exchange of ions, lipids and metabolites between the ER and mitochondria. ER chaperones and oxidoreductases are critical components of the MAM. However, the localization motifs and mechanisms for most MAM proteins have remained elusive. Using two highly related ER oxidoreductases as a model system, we now show that palmitoylation enriches ER-localized proteins on the MAM. We demonstrate that palmitoylation of cysteine residue(s) adjacent to the membrane-spanning domain promotes MAM enrichment of the transmembrane thioredoxin family protein TMX. In addition to TMX, our results also show that calnexin shuttles between the rough ER and the MAM depending on its palmitoylation status. Mutation of the TMX and calnexin palmitoylation sites and chemical interference with palmitoylation disrupt their MAM enrichment. Since ER-localized heme oxygenase-1, but not cytosolic GRP75 require palmitoylation to reside on the MAM, our findings identify palmitoylation as key for MAM enrichment of ER membrane proteins.     

Dual role of the cysteine-string domain in membrane binding and palmitoylation-dependent sorting of the molecular chaperone cysteine-string protein

S-palmitoylation occurs on intracellular membranes and, therefore, membrane anchoring of proteins must precede palmitate transfer. However, a number of palmitoylated proteins lack any obvious membrane targeting motifs and it is unclear how this class of proteins become membrane associated before palmitoylation. Cysteine-string protein (CSP), which is extensively palmitoylated on a "string" of 14 cysteine residues, is an example of such a protein. In this study, we have investigated the mechanisms that govern initial membrane targeting, palmitoylation, and membrane trafficking of CSP. We identified a hydrophobic 31 amino acid domain, which includes the cysteine-string, as a membrane-targeting motif that associates predominantly with endoplasmic reticulum (ER) membranes. Cysteine residues in this domain are not merely sites for the addition of palmitate groups, but play an essential role in membrane recognition before palmitoylation. Membrane association of the cysteine-string domain is not sufficient to trigger palmitoylation, which requires additional downstream residues that may regulate the membrane orientation of the cysteine-string domain. CSP palmitoylation-deficient mutants remain "trapped" in the ER, suggesting that palmitoylation may regulate ER exit and correct intracellular sorting of CSP. These results reveal a dual function of the cysteine-string domain: initial membrane binding and palmitoylation-dependent sorting.     

Palmitoylation of virus proteins

The article summarises the results of more than 30 years of research on palmitoylation (S-acylation) of viral proteins, the post-translational attachment of fatty acids to cysteine residues of integral and peripheral membrane proteins. Analysing viral proteins is not only important to characterise the cellular pathogens but also instrumental to decipher the palmitoylation machinery of cells. This comprehensive review describes methods to identify S-acylated proteins and covers the fundamental biochemistry of palmitoylation: the location of palmitoylation sites in viral proteins, the fatty acid species found in S-acylated proteins, the intracellular site of palmitoylation and the enzymology of the reaction. Finally, the functional consequences of palmitoylation are discussed regarding binding of proteins to membranes or membrane rafts, entry of enveloped viruses into target cells by spike-mediated membrane fusion as well as assembly and release of virus particles from infected cells. The topics are described mainly for palmitoylated proteins of influenza virus, but proteins of other important pathogens, such as the causative agents of AIDS and severe acute respiratory syndrome, and of model viruses are discussed.     

GPS-PUP: computational prediction of pupylation sites in prokaryotic proteins

Recent experiments revealed the prokaryotic ubiquitin-like protein (PUP) to be a signal for the selective degradation of proteins in Mycobacterium tuberculosis (Mtb). By covalently conjugating the PUP, pupylation functions as a critical post-translational modification (PTM) conserved in actinomycetes. Here, we designed a novel computational tool of GPS-PUP for the prediction of pupylation sites, which was shown to have a promising performance. From small-scale and large-scale studies we collected 238 potentially pupylated substrates for which the exact pupylation sites were still not determined. As an example application, we predicted ～85% of these proteins with at least one potential pupylation site. Furthermore, through functional analysis, we observed that pupylation can target various substrates so as to regulate a broad array of biological processes, such as the response to stress, sulfate and proton transport, and metabolism. The prediction and analysis results prove to be useful for further experimental investigation. The GPS-PUP 1.0 is freely available at: .     

Predicting DNA-binding sites of proteins based on sequential and 3D structural information

Protein–DNA interactions play important roles in many biological processes. To understand the molecular mechanisms of protein–DNA interaction, it is necessary to identify the DNA-binding sites in DNA-binding proteins. In the last decade, computational approaches have been developed to predict protein–DNA-binding sites based solely on protein sequences. In this study, we developed a novel predictor based on support vector machine algorithm coupled with the maximum relevance minimum redundancy method followed by incremental feature selection. We incorporated not only features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, solvent accessibility, but also five three-dimensional (3D) structural features calculated from PDB data to predict the protein–DNA interaction sites. Feature analysis showed that 3D structural features indeed contributed to the prediction of DNA-binding site and it was demonstrated that the prediction performance was better with 3D structural features than without them. It was also shown via analysis of features from each site that the features of DNA-binding site itself contribute the most to the prediction. Our prediction method may become a useful tool for identifying the DNA-binding sites and the feature analysis described in this paper may provide useful insights for in-depth investigations into the mechanisms of protein–DNA interaction.     

Palmitoylation of stathmin family proteins domain A controls Golgi versus mitochondrial subcellular targeting

Background information. Precise localization of proteins to specialized subcellular domains is fundamental for proper neuronal development and function. The neural microtubule‐regulatory phosphoproteins of the stathmin family are such proteins whose specific functions are controlled by subcellular localization. Whereas stathmin is cytosolic, SCG10, SCLIP and RB3/RB3′/RB3″ are localized to the Golgi and vesicle‐like structures along neurites and at growth cones. We examined the molecular determinants involved in the regulation of this specific subcellular localization in hippocampal neurons in culture. Results. We show that their conserved N‐terminal domain A carrying two palmitoylation sites is dominant over the others for Golgi and vesicle‐like localization. Using palmitoylation‐deficient GFP (green fluorescent protein) fusion mutants, we demonstrate that domains A of stathmin proteins have the particular ability to control protein targeting to either Golgi or mitochondria, depending on their palmitoylation. This regulation involves the co‐operation of two subdomains within domain A, and seems also to be under the control of its SLD (stathmin‐like domain) extension. Conclusions. Our results unravel that, in specific biological conditions, palmitoylation of stathmin proteins might be able to control their targeting to express their functional activities at appropriate subcellular sites. They, more generally, open new perspectives regarding the role of palmitoylation as a signalling mechanism orienting proteins to their functional subcellular compartments.     

Predicting pupylation sites in prokaryotic proteins using semi-supervised self-training support vector machine algorithm

As one important post-translational modification of prokaryotic proteins, pupylation plays a key role in regulating various biological processes. The accurate identification of pupylation sites is crucial for understanding the underlying mechanisms of pupylation. Although several computational methods have been developed for the identification of pupylation sites, the prediction accuracy of them is still unsatisfactory. Here, a novel bioinformatics tool named IMP–PUP is proposed to improve the prediction of pupylation sites. IMP–PUP is constructed on the composition of k-spaced amino acid pairs and trained with a modified semi-supervised self-training support vector machine (SVM) algorithm. The proposed algorithm iteratively trains a series of support vector machine classifiers on both annotated and non-annotated pupylated proteins. Computational results show that IMP–PUP achieves the area under receiver operating characteristic curves of 0.91, 0.73, and 0.75 on our training set, Tung's testing set, and our testing set, respectively, which are better than those of the different error costs SVM algorithm and the original self-training SVM algorithm. Independent tests also show that IMP–PUP significantly outperforms three other existing pupylation site predictors: GPS–PUP, iPUP, and pbPUP. Therefore, IMP–PUP can be a useful tool for accurate prediction of pupylation sites. A MATLAB software package for IMP–PUP is available at https://juzhe1120.github.io/.     

Global analysis of protein palmitoylation in African trypanosomes

Many eukaryotic proteins are posttranslationally modified by the esterification of cysteine thiols to long-chain fatty acids. This modification, protein palmitoylation, is catalyzed by a large family of palmitoyl acyltransferases that share an Asp-His-His-Cys Cys-rich domain but differ in their subcellular localizations and substrate specificities. In Trypanosoma brucei, the flagellated protozoan parasite that causes African sleeping sickness, protein palmitoylation has been observed for a few proteins, but the extent and consequences of this modification are largely unknown. We undertook the present study to investigate T. brucei protein palmitoylation at both the enzyme and substrate levels. Treatment of parasites with an inhibitor of total protein palmitoylation caused potent growth inhibition, yet there was no effect on growth by the separate, selective inhibition of each of the 12 individual T. brucei palmitoyl acyltransferases. This suggested either that T. brucei evolved functional redundancy for the palmitoylation of essential palmitoyl proteins or that palmitoylation of some proteins is catalyzed by a noncanonical transferase. To identify the palmitoylated proteins in T. brucei, we performed acyl biotin exchange chemistry on parasite lysates, followed by streptavidin chromatography, two-dimensional liquid chromatography-tandem mass spectrometry protein identification, and QSpec statistical analysis. A total of 124 palmitoylated proteins were identified, with an estimated false discovery rate of 1.0%. This palmitoyl proteome includes all of the known palmitoyl proteins in procyclic-stage T. brucei as well as several proteins whose homologues are palmitoylated in other organisms. Their sequences demonstrate the variety of substrate motifs that support palmitoylation, and their identities illustrate the range of cellular processes affected by palmitoylation in these important pathogens.