PGluS: prediction of protein S-glutathionylation sites with multiple features and analysis

A novel approach for predicting protein S-glutathionylation

Background

S-glutathionylation is the formation of disulfide bonds between the tripeptide glutathione and cysteine residues of the protein, protecting them from irreversible oxidation and in some cases causing change in their functions. Regulatory glutathionylation of proteins is a controllable and reversible process associated with cell response to the changing redox status. Prediction of cysteine residues that undergo glutathionylation allows us to find new target proteins, which function can be altered in pathologies associated with impaired redox status. We set out to analyze this issue and create new tool for predicting S-glutathionylated cysteine residues.

Results

One hundred forty proteins with experimentally proven S-glutathionylated cysteine residues were found in the literature and the RedoxDB database. These proteins contain 1018 non-S-glutathionylated cysteines and 235 S-glutathionylated ones. Based on 235 S-glutathionylated cysteines, non-redundant positive dataset of 221 heptapeptide sequences of S-glutathionylated cysteines was made. Based on 221 heptapeptide sequences, a position-specific matrix was created by analyzing the protein sequence near the cysteine residue (three amino acid residues before and three after the cysteine). We propose the method for calculating the glutathionylation propensity score, which utilizes the position-specific matrix and a criterion for predicting glutathionylated peptides.

Conclusion

Non-S-glutathionylated sites were enriched by cysteines in − 3 and + 3 positions. The proposed prediction method demonstrates 76.6% of correct predictions of S-glutathionylated cysteines. This method can be used for detecting new glutathionylation sites, especially in proteins with an unknown structure.

Regulation of titin-based cardiac stiffness by unfolded domain oxidation (UnDOx)

Titin oxidation alters titin stiffness, which greatly contributes to overall myocardial stiffness. This stiffness is frequently increased in heart disease, such as diastolic heart failure. We have quantified the degree of oxidative titin changes in several murine heart and skeletal muscle models exposed to oxidant stress and mechanical load. Importantly, strain enhances in vivo oxidation of titin in the elastic region, but not the inextensible segment. The functional consequences include oxidation type-dependent effects on cardiomyocyte stiffness, titin-domain folding, phosphorylation, and inter-titin interactions. Thus, oxidative modifications stabilize the titin spring in a dynamic and reversible manner and help propagate changes in titin-based myocardial stiffness. Our findings pave the way for interventions that target the pathological stiffness of titin in disease.

The relationship between oxidative stress and cardiac stiffness is thought to involve modifications to the giant muscle protein titin, which in turn can determine the progression of heart disease. In vitro studies have shown that S-glutathionylation and disulfide bonding of titin fragments could alter the elastic properties of titin; however, whether and where titin becomes oxidized in vivo is less certain. Here we demonstrate, using multiple models of oxidative stress in conjunction with mechanical loading, that immunoglobulin domains preferentially from the distal titin spring region become oxidized in vivo through the mechanism of unfolded domain oxidation (UnDOx). Via oxidation type-specific modification of titin, UnDOx modulates human cardiomyocyte passive force bidirectionally. UnDOx also enhances titin phosphorylation and, importantly, promotes nonconstitutive folding and aggregation of unfolded domains. We propose a mechanism whereby UnDOx enables the controlled homotypic interactions within the distal titin spring to stabilize this segment and regulate myocardial passive stiffness.

Dysregulation of the glutaredoxin/S-glutathionylation redox axis in lung diseases

Glutathione is a major redox buffer, reaching millimolar concentrations within cells and high micromolar concentrations in airways. While glutathione has been traditionally known as an antioxidant defense mechanism that protects the lung tissue from oxidative stress, glutathione more recently has become recognized for its ability to become covalently conjugated to reactive cysteines within proteins, a modification known as S-glutathionylation (or S-glutathiolation or protein mixed disulfide). S-glutathionylation has the potential to change the structure and function of the target protein, owing to its size (the addition of three amino acids) and charge (glutamic acid). S-glutathionylation also protects proteins from irreversible oxidation, allowing them to be enzymatically regenerated. Numerous enzymes have been identified to catalyze the glutathionylation/deglutathionylation reactions, including glutathione S-transferases and glutaredoxins. Although protein S-glutathionylation has been implicated in numerous biological processes, S-glutathionylated proteomes have largely remained unknown. In this paper, we focus on the pathways that regulate GSH homeostasis, S-glutathionylated proteins, and glutaredoxins, and we review methods required toward identification of glutathionylated proteomes. Finally, we present the latest findings on the role of glutathionylation/glutaredoxins in various lung diseases: idiopathic pulmonary fibrosis, asthma, and chronic obstructive pulmonary disease.

Analysis and prediction of human acetylation using a cascade classifier based on support vector machine

Background

Acetylation on lysine is a widespread post-translational modification which is reversible and plays a crucial role in some biological activities. To better understand the mechanism, it is necessary to identify acetylation sites in proteins accurately. Computational methods are popular because they are more convenient and faster than experimental methods. In this study, we proposed a new computational method to predict acetylation sites in human by combining sequence features and structural features including physicochemical property (PCP), position specific score matrix (PSSM), auto covariation (AC), residue composition (RC), secondary structure (SS) and accessible surface area (ASA), which can well characterize the information of acetylated lysine sites. Besides, a two-step feature selection was applied, which combined mRMR and IFS. It finally trained a cascade classifier based on SVM, which successfully solved the imbalance between positive samples and negative samples and covered all negative sample information.

Results

The performance of this method is measured with a specificity of 72.19% and a sensibility of 76.71% on independent dataset which shows that a cascade SVM classifier outperforms single SVM classifier.

Conclusions

In addition to the analysis of experimental results, we also made a systematic and comprehensive analysis of the acetylation data.

Research progress in protein posttranslational modification site prediction

Posttranslational modifications (PTMs) play an important role in regulating protein folding, activity and function and are involved in almost all cellular processes. Identification of PTMs of proteins is the basis for elucidating the mechanisms of cell biology and disease treatments. Compared with the laboriousness of equivalent experimental work, PTM prediction using various machine-learning methods can provide accurate, simple and rapid research solutions and generate valuable information for further laboratory studies. In this review, we manually curate most of the bioinformatics tools published since 2008. We also summarize the approaches for predicting ubiquitination sites and glycosylation sites. Moreover, we discuss the challenges of current PTM bioinformatics tools and look forward to future research possibilities.

Detecting Succinylation sites from protein sequences using ensemble support vector machine

Background

Lysine succinylation is a new kind of post-translational modification which plays a key role in protein conformation regulation and cellular function control. To understand the mechanism of succinylation profoundly, it is necessary to identify succinylation sites in proteins accurately. However, traditional methods, experimental approaches, are labor-intensive and time-consuming. Computational prediction methods have been proposed recent years, and they are popular because of their convenience and high speed. In this study, we developed a new method to predict succinylation sites in protein combining multiple features, including amino acid composition, binary encoding, physicochemical property and grey pseudo amino acid composition, with a feature selection scheme (information gain). And then, it was trained using SVM (Support Vector Machine) and an ensemble learning algorithm.

Results

The performance of this method was measured with an accuracy of 89.14% and a MCC (Matthew Correlation Coefficient) of 0.79 using 10-fold cross validation on training dataset and an accuracy of 84.5% and a MCC of 0.2 on independent dataset.

Conclusions

The conclusions made from this study can help to understand more of the succinylation mechanism. These results suggest that our method was very promising for predicting succinylation sites. The source code and data of this paper are freely available athttps://github.com/ningq669/PSuccE.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2249-4) contains supplementary material, which is available to authorized users.

Features of reactive cysteines discovered through computation: from kinase inhibition to enrichment around protein degrons

Large-scale characterisation of cysteine modification is enabling study of the physicochemical determinants of reactivity. We find that location of cysteine at the amino terminus of an α-helix, associated with activity in thioredoxins, is under-represented in human protein structures, perhaps indicative of selection against background reactivity. An amino-terminal helix location underpins the covalent linkage for one class of kinase inhibitors. Cysteine targets for S-palmitoylation, S-glutathionylation, and S-nitrosylation show little correlation with pKa values predicted from structures, although flanking sequences of S-palmitoylated sites are enriched in positively-charged amino acids, which could facilitate palmitoyl group transfer to substrate cysteine. A surprisingly large fraction of modified sites, across the three modifications, would be buried in native protein structure. Furthermore, modified cysteines are (on average) closer to lysine ubiquitinations than are unmodified cysteines, indicating that cysteine redox biology could be associated with protein degradation and degron recognition.

Prediction of reversible disulfide based on features from local structural signatures

Background

Disulfide bonds are traditionally considered to play only structural roles. In recent years, increasing evidence suggests that the disulfide proteome is made up of structural disulfides and reversible disulfides. Unlike structural disulfides, reversible disulfides are usually of important functional roles and may serve as redox switches. Interestingly, only specific disulfide bonds are reversible while others are not. However, whether reversible disulfides can be predicted based on structural information remains largely unknown.

Methods

In this study, two datasets with both types of disulfides were compiled using independent approaches. By comparison of various features extracted from the local structural signatures, we identified several features that differ significantly between reversible and structural disulfides, including disulfide bond length, along with the number, amino acid composition, secondary structure and physical-chemical properties of surrounding amino acids. A SVM-based classifier was developed for predicting reversible disulfides.

Results

By 10-fold cross-validation, the model achieved accuracy of 0.750, sensitivity of 0.352, specificity of 0.953, MCC of 0.405 and AUC of 0.751 using the RevSS_PDB dataset. The robustness was further validated by using RevSS_RedoxDB as independent testing dataset. This model was applied to proteins with known structures in the PDB database. The results show that one third of the predicted reversible disulfide containing proteins are well-known redox enzymes, while the remaining are non-enzyme proteins. Given that reversible disulfides are frequently reported from functionally important non-enzyme proteins such as transcription factors, the predictions may provide valuable candidates of novel reversible disulfides for further experimental investigation.

Conclusions

This study provides the first comparative analysis between the reversible and the structural disulfides. Distinct features remarkably different between these two groups of disulfides were identified, and a SVM-based classifier for predicting reversible disulfides was developed accordingly. A web server named RevssPred can be accessed freely from: http://biocomputer.bio.cuhk.edu.hk/RevssPred.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3668-8) contains supplementary material, which is available to authorized users.

Assessment of disulfide and hinge modifications in monoclonal antibodies

During the last years there was a substantial increase in the use of antibodies and related proteins as therapeutics. The emphasis of the pharmaceutical industry is on IgG1, IgG2, and IgG4 antibodies, which are therefore in the focus of this article. In order to ensure appropriate quality control of such biopharmaceuticals, deep understanding of their chemical degradation pathways and the resulting impact on potency, pharmacokinetics, and safety is required. Criticality of modifications may be specific for individual antibodies and has to be assessed for each molecule. However, some modifications of conserved structure elements occur in all or at least most IgGs. In these cases, criticality assessment may be applicable to related molecules or molecule formats. The relatively low dissociation energy of disulfide bonds and the high flexibility of the hinge region frequently lead to modifications and cleavages. Therefore, the hinge region and disulfide bonds require specific consideration during quality assessment of mAbs. In this review, available literature knowledge on underlying chemical reaction pathways of modifications, analytical methods for quantification and criticality are discussed. The hinge region is prone to cleavage and is involved in pathways that lead to thioether bond formation, cysteine racemization, and iso‐Asp (Asp, aspartic acid) formation. Disulfide or sulfhydryl groups were found to be prone to reductive cleavage, trisulfide formation, cysteinylation, glutathionylation, disulfide bridging to further light chains, and disulfide scrambling. With regard to potency, disulfide cleavage, hinge cleavage, disulfide bridging to further light chains, and cysteinylation were found to influence antigen binding and fragment crystallizable (Fc) effector functionalities. Renal clearance of small fragments may be faster, whereas clearance of larger fragments appears to depend on their neonatal Fc receptor (FcRn) functionality, which in turn may be impeded by disulfide bond cleavage. Certain modifications such as disulfide induced aggregation and heterodimers from different antibodies are generally regarded critical with respect to safety. However, the detection of some modifications in endogenous antibodies isolated from human blood and the possibility of in vivo repair mechanisms may reduce some safety concerns.

Proteomic approaches to quantify cysteine reversible modifications in aging and neurodegenerative diseases

Cysteine is a highly reactive amino acid and is subject to a variety of reversible post-translational modifications (PTMs), including nitrosylation, glutathionylation, palmitoylation, as well as formation of sulfenic acid and disulfides. These modifications are not only involved in normal biological activities, such as enzymatic catalysis, redox signaling, and cellular homeostasis, but can also be the result of oxidative damage. Especially in aging and neurodegenerative diseases, oxidative stress leads to aberrant cysteine oxidations that affect protein structure and function leading to neurodegeneration as well as other detrimental effects. Methods that can identify cysteine modifications by type, including the site of modification, as well as the relative stoichiometry of the modification can be very helpful for understanding the role of the thiol proteome and redox homeostasis in the context of disease. Cysteine reversible modifications however, are challenging to investigate as they are low abundant, diverse, and labile especially under endogenous conditions. Thanks to the development of redox proteomic approaches, large-scale quantification of cysteine reversible modifications is possible. These approaches cover a range of strategies to enrich, identify, and quantify cysteine reversible modifications from biological samples. This review will focus on nongel-based redox proteomics workflows that give quantitative information about cysteine PTMs and highlight how these strategies have been useful for investigating the redox thiol proteome in aging and neurodegenerative diseases.

Cy-preds: An algorithm and a web service for the analysis and prediction of cysteine reactivity

Cysteine (Cys) is a critically important amino acid, serving a variety of functions within proteins including structural roles, catalysis, and regulation of function through post-translational modifications. Predicting which Cys residues are likely to be reactive is a very sought after feature. Few methods are currently available for the task, either based on evaluation of physicochemical features (e.g., pKa and exposure) or based on similarity with known instances. In this study, we developed an algorithm (named HAL-Cy) which blends previous work with novel implementations to identify reactive Cys from nonreactive. HAL-Cy present two major components: (i) an energy based part, rooted on the evaluation of H-bond network contributions and (ii) a knowledge based part, composed of different profiling approaches (including a newly developed weighting matrix for sequence profiling). In our evaluations, HAL-Cy provided significantly improved performances, as tested in comparisons with existing approaches. We implemented our algorithm in a web service (Cy-preds), the ultimate product of our work; we provided it with a variety of additional features, tools, and options: Cy-preds is capable of performing fully automated calculations for a thorough analysis of Cys reactivity in proteins, ranging from reactivity predictions (e.g., with HAL-Cy) to functional characterization. We believe it represents an original, effective, and very useful addition to the current array of tools available to scientists involved in redox biology, Cys biochemistry, and structural bioinformatics.

"Oxygen Sensing" by Na,K-ATPase: These Miraculous Thiols

Control over the Na,K-ATPase function plays a central role in adaptation of the organisms to hypoxic and anoxic conditions. As the enzyme itself does not possess O2 binding sites its "oxygen-sensitivity" is mediated by a variety of redox-sensitive modifications including S-glutathionylation, S-nitrosylation, and redox-sensitive phosphorylation. This is an overview of the current knowledge on the plethora of molecular mechanisms tuning the activity of the ATP-consuming Na,K-ATPase to the cellular metabolic activity. Recent findings suggest that oxygen-derived free radicals and H2O2, NO, and oxidized glutathione are the signaling messengers that make the Na,K-ATPase "oxygen-sensitive." This very ancient signaling pathway targeting thiols of all three subunits of the Na,K-ATPase as well as redox-sensitive kinases sustains the enzyme activity at the "optimal" level avoiding terminal ATP depletion and maintaining the transmembrane ion gradients in cells of anoxia-tolerant species. We acknowledge the complexity of the underlying processes as we characterize the sources of reactive oxygen and nitrogen species production in hypoxic cells, and identify their targets, the reactive thiol groups which, upon modification, impact the enzyme activity. Structured accordingly, this review presents a summary on (i) the sources of free radical production in hypoxic cells, (ii) localization of regulatory thiols within the Na,K-ATPase and the role reversible thiol modifications play in responses of the enzyme to a variety of stimuli (hypoxia, receptors' activation) (iii) redox-sensitive regulatory phosphorylation, and (iv) the role of fine modulation of the Na,K-ATPase function in survival success under hypoxic conditions. The co-authors attempted to cover all the contradictions and standing hypotheses in the field and propose the possible future developments in this dynamic area of research, the importance of which is hard to overestimate. Better understanding of the processes underlying successful adaptation strategies will make it possible to harness them and use for treatment of patients with stroke and myocardial infarction, sleep apnoea and high altitude pulmonary oedema, and those undergoing surgical interventions associated with the interruption of blood perfusion.

Basal Glutathionylation of Na,K-ATPase α-Subunit Depends on Redox Status of Cells during the Enzyme Biosynthesis

Many viruses induce oxidative stress and cause S-glutathionylation of Cys residues of the host and viral proteins. Changes in cell functioning during viral infection may be associated with glutathionylation of a number of key proteins including Na,K-ATPase which creates a gradient of sodium and potassium ions. It was found that Na,K-ATPase α-subunit has a basal glutathionylation which is not abrogated by reducing agent. We have shown that acute hypoxia leads to increase of total glutathionylation level of Na,K-ATPase α-subunit; however, basal glutathionylation of α-subunit increases under prolonged hypoxia only. The role of basal glutathionylation in Na,K-ATPase function remains unclear. Understanding significance of basal glutathionylation is complicated by the fact that there are no X-ray structures of Na,K-ATPase with the identified glutathione molecules. We have analyzed all X-ray structures of the Na,K-ATPase α-subunit from pig kidney and found that there are a number of isolated cavities with unresolved electron density close to the relevant cysteine residues. Analysis of the structures showed that this unresolved density in the structure can be occupied by glutathione associated with cysteine residues. Here, we discuss the role of basal glutathionylation of Na,K-ATPase α-subunit and provide evidence supporting the view that this modification is cotranslational.

iSulf-Cys: Prediction of S-sulfenylation Sites in Proteins with Physicochemical Properties of Amino Acids

Cysteine S-sulfenylation is an important post-translational modification (PTM) in proteins, and provides redox regulation of protein functions. Bioinformatics and structural analyses indicated that S-sulfenylation could impact many biological and functional categories and had distinct structural features. However, major limitations for identifying cysteine S-sulfenylation were expensive and low-throughout. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor iSulf-Cys which incorporated 14 kinds of physicochemical properties of amino acids was proposed. With the 10-fold cross-validation, the value of area under the curve (AUC) was 0.7155 ± 0.0085, MCC 0.3122 ± 0.0144 on the training dataset for 20 times. iSulf-Cys also showed satisfying performance in the independent testing dataset with AUC 0.7343 and MCC 0.3315. Features which were constructed from physicochemical properties and position were carefully analyzed. Meanwhile, a user-friendly web-server for iSulf-Cys is accessible at http://app.aporc.org/iSulf-Cys/.

Identification of S-glutathionylation sites in species-specific proteins by incorporating five sequence-derived features into the general pseudo-amino acid composition

As a selective and reversible protein post-translational modification, S-glutathionylation generates mixed disulfides between glutathione (GSH) and cysteine residues, and plays an important role in regulating protein activity, stability, and redox regulation. To fully understand S-glutathionylation mechanisms, identification of substrates and specific S-Glutathionylated sites is crucial. Experimental identification of S-glutathionylated sites is labor-intensive and time consuming, so establishing an effective computational method is much desirable due to their convenient and fast speed. Therefore, in this study, a new bioinformatics tool named SSGlu (Species-Specific identification of Protein S-glutathionylation Sites) was developed to identify species-specific protein S-glutathionylated sites, utilizing support vector machines that combine multiple sequence-derived features with a two-step feature selection. By 5-fold cross validation, the performance of SSGlu was measured with an AUC of 0.8105 and 0.8041 for Homo sapiens and Mus musculus, respectively. Additionally, SSGlu was compared with the existing methods, and the higher MCC and AUC of SSGlu demonstrated that SSGlu was very promising to predict S-glutathionylated sites. Furthermore, a site-specific analysis showed that S-glutathionylation intimately correlated with the features derived from its surrounding sites. The conclusions derived from this study might help to understand more of the S-glutathionylation mechanism and guide the related experimental validation. For public access, SSGlu is freely accessible at http://59.73.198.144:8080/SSGlu/.

Three-dimensional structure and molecular dynamics studies of prorrenin/renin receptor: description of the active site

The recent finding of a specific receptor for prorrenin/renin (PRR) has brought new insights into the physiology of the renin-angiotensin-aldosterone system. No undoubtable role has been described for this receptor so far. Its role seems to be important in chronic illnesses such as hypertension, possibly participating in the cardiovascular remodeling process, and diabetes where participation in inflammation development has been described. It is not possible, however, to explore the PRR function using classical pharmacological approaches due to the lack of specific agonists or antagonists. Two synthetic peptides have been described to accomplish these roles, but no conclusive data have been provided. There are no X-ray crystallography studies available to describe the structure and potential sites for drug development. So, the aim of this work was to model and theoretically describe the PRR. We describe and characterize the whole receptor protein, its spatial conformation and the potential interactions of PRR with the synthetic peptides available, describing the amino acid residues responsible for these interactions. This information provides the basis for directed development of drugs, seeking to agonize or antagonize PRR activity and study its function in health and ill stages.