Development and application of site-specific proteomic approach for study protein S-nitrosylation

Liu, Miao; Talmadge, James E.; Ding, Shilei

doi:10.1007/s00726-012-1279-x

Cited by 9 publications

(7 citation statements)

References 51 publications

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“…Various assays with goal-specific modifications have been developed for the characterization, identification, and quantification of S -nitrosylated proteins (Torta et al, 2008; Foster, 2012; Liu et al, 2012). Most of the work has used indirect methods, measuring free NO levels after cleavage of SNO bonds or replacing the original nitrosothiols with another detectable tag (BST).…”

Section: Detection and Identification Of S-nitrosylated Proteinsmentioning

confidence: 99%

Nitric oxide-based protein modification: formation and site-specificity of protein S-nitrosylation

Kovács¹,

Lindermayr²

2013

Front. Plant Sci.

116

113

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Nitric oxide (NO) is a reactive free radical with pleiotropic functions that participates in diverse biological processes in plants, such as germination, root development, stomatal closing, abiotic stress, and defense responses. It acts mainly through redox-based modification of cysteine residue(s) of target proteins, called protein S-nitrosylation.In this way NO regulates numerous cellular functions and signaling events in plants. Identification of S-nitrosylated substrates and their exact target cysteine residue(s) is very important to reveal the molecular mechanisms and regulatory roles of S-nitrosylation. In addition to the necessity of protein–protein interaction for trans-nitrosylation and denitrosylation reactions, the cellular redox environment and cysteine thiol micro-environment have been proposed important factors for the specificity of protein S-nitrosylation. Several methods have recently been developed for the proteomic identification of target proteins. However, the specificity of NO-based cysteine modification is still less defined. In this review, we discuss formation and specificity of S-nitrosylation. Special focus will be on potential S-nitrosylation motifs, site-specific proteomic analyses, computational predictions using different algorithms, and on structural analysis of cysteine S-nitrosylation.

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Section: Detection and Identification Of S-nitrosylated Proteinsmentioning

confidence: 99%

Nitric oxide-based protein modification: formation and site-specificity of protein S-nitrosylation

Kovács¹,

Lindermayr²

2013

Front. Plant Sci.

116

113

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“…Protein S -nitrosylation plays a central role in regulatory mechanisms by fine-tuning protein activities associated with diverse cellular processes and biochemical pathway [1,3]. In addition, S -nitrosylation appears to have major roles in the etiology of a broad range of human diseases.…”

Section: Resultsmentioning

confidence: 99%

“…Protein S -nitrosylation, the covalent attachment of a nitric oxide (NO) moiety to cysteine residues of proteins resulting in the formation of S -nitrosothiols (SNO), is a typical redox-dependent posttranslational modification that is associated with redox-based cellular signaling [1,2,3]. Protein S -nitrosylation has been reported to play roles in the in vitro / in vivo regulation of a variety of metabolic enzymes, oxidoreductases, proteases, protein kinases, and protein phosphatases, as well as in the function of regulatory factors (including G protein) [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, deregulation of S -nitrosylation has been implicated in tumor initiation and progression [4,7]. The increasing prominence of the roles of S -nitrosylation in diseases indicates a need for improved analytical methods to identify and quantify S -nitrosylated proteins under various physiological and pathophysiological conditions for investigative studies and clinical diagnosis [1,6,7]. The use of traditional mass spectrometry-based proteomics has been challenging because of the inherent chemical instability of the S -NO bond [4,8].…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Protein S-Nitrosylation Sites Based on Adapted Normal Distribution Bi-Profile Bayes and Chou’s Pseudo Amino Acid Composition

Jia

Lin

Wang

2014

IJMS

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Protein S-nitrosylation is a reversible post-translational modification by covalent modification on the thiol group of cysteine residues by nitric oxide. Growing evidence shows that protein S-nitrosylation plays an important role in normal cellular function as well as in various pathophysiologic conditions. Because of the inherent chemical instability of the S-NO bond and the low abundance of endogenous S-nitrosylated proteins, the unambiguous identification of S-nitrosylation sites by commonly used proteomic approaches remains challenging. Therefore, computational prediction of S-nitrosylation sites has been considered as a powerful auxiliary tool. In this work, we mainly adopted an adapted normal distribution bi-profile Bayes (ANBPB) feature extraction model to characterize the distinction of position-specific amino acids in 784 S-nitrosylated and 1568 non-S-nitrosylated peptide sequences. We developed a support vector machine prediction model, iSNO-ANBPB, by incorporating ANBPB with the Chou’s pseudo amino acid composition. In jackknife cross-validation experiments, iSNO-ANBPB yielded an accuracy of 65.39% and a Matthew’s correlation coefficient (MCC) of 0.3014. When tested on an independent dataset, iSNO-ANBPB achieved an accuracy of 63.41% and a MCC of 0.2984, which are much higher than the values achieved by the existing predictors SNOSite, iSNO-PseAAC, the Li et al. algorithm, and iSNO-AAPair. On another training dataset, iSNO-ANBPB also outperformed GPS-SNO and iSNO-PseAAC in the 10-fold crossvalidation test.

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“…Nitric oxide (NO) has been reported to be an important signaling molecule which involves physiological and pathophysiological regulations of some cellular processes, such as cardiovascular, respiratory, gastrointestinal, reproductive, and host defense [1–4]. Protein S-nitrosylation which is covalently modified by NO has recently been discovered to play important roles in regulating diverse pathways [5–7] and other biological activities [8], such as chromatin remodeling [9], transcriptional regulation [10], cellular trafficking [11], and apoptosis [12].…”

Section: Introductionmentioning

confidence: 99%

Prediction of S-Nitrosylation Modification Sites Based on Kernel Sparse Representation Classification and mRMR Algorithm

Huang

Lin

Kong

et al. 2014

BioMed Research International

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Protein S-nitrosylation plays a very important role in a wide variety of cellular biological activities. Hitherto, accurate prediction of S-nitrosylation sites is still of great challenge. In this paper, we presented a framework to computationally predict S-nitrosylation sites based on kernel sparse representation classification and minimum Redundancy Maximum Relevance algorithm. As much as 666 features derived from five categories of amino acid properties and one protein structure feature are used for numerical representation of proteins. A total of 529 protein sequences collected from the open-access databases and published literatures are used to train and test our predictor. Computational results show that our predictor achieves Matthews' correlation coefficients of 0.1634 and 0.2919 for the training set and the testing set, respectively, which are better than those of k-nearest neighbor algorithm, random forest algorithm, and sparse representation classification algorithm. The experimental results also indicate that 134 optimal features can better represent the peptides of protein S-nitrosylation than the original 666 redundant features. Furthermore, we constructed an independent testing set of 113 protein sequences to evaluate the robustness of our predictor. Experimental result showed that our predictor also yielded good performance on the independent testing set with Matthews' correlation coefficients of 0.2239.

show abstract

Development and application of site-specific proteomic approach for study protein S-nitrosylation

Cited by 9 publications

References 51 publications

Nitric oxide-based protein modification: formation and site-specificity of protein S-nitrosylation

Nitric oxide-based protein modification: formation and site-specificity of protein S-nitrosylation

Prediction of Protein S-Nitrosylation Sites Based on Adapted Normal Distribution Bi-Profile Bayes and Chou’s Pseudo Amino Acid Composition

Prediction of S-Nitrosylation Modification Sites Based on Kernel Sparse Representation Classification and mRMR Algorithm

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