SPRINT-Gly: predicting<i>N-</i>and<i>O-</i>linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties

Taherzadeh, Ghazaleh; Dehzangi, Abdollah; Golchin, Maryam; Zhou, Yaoqi; Campbell, Matthew P.

doi:10.1093/bioinformatics/btz215

Cited by 57 publications

(51 citation statements)

References 51 publications

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“…The immunosignals mostly appeared as a doublet at approximately 140 and 150 kDa (Figure 1A), which is probably due to the described pair of N-glycosylation sites in the external loop of human TRPA1, which is flanked by the transmembrane regions TM1 and TM2 (721-960) [56]. Computer analysis indicated this possibility for murine TRPA1 [57] and in vitro, PGNase F abolished the 150 kDa band augmenting the intensity of the expected 140 kDa (Figure 1B).…”

Section: Resultsmentioning

confidence: 93%

Calmodulin Supports TRPA1 Channel Association with Opioid Receptors and Glutamate NMDA Receptors in the Nervous Tissue

Cortés-Montero

Rodríguez-Muñoz

Ruiz-Cantero

et al. 2020

IJMS

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Transient receptor potential ankyrin member 1 (TRPA1) belongs to the family of thermo TRP cation channels that detect harmful temperatures, acids and numerous chemical pollutants. TRPA1 is expressed in nervous tissue, where it participates in the genesis of nociceptive signals in response to noxious stimuli and mediates mechanical hyperalgesia and allodynia associated with different neuropathies. The glutamate N-methyl-d-aspartate receptor (NMDAR), which plays a relevant role in allodynia to mechanical stimuli, is connected via histidine triad nucleotide-binding protein 1 (HINT1) and type 1 sigma receptor (σ1R) to mu-opioid receptors (MORs), which mediate the most potent pain relief. Notably, neuropathic pain causes a reduction in MOR antinociceptive efficacy, which can be reversed by blocking spinal NMDARs and TRPA1 channels. Thus, we studied whether TRPA1 channels form complexes with MORs and NMDARs that may be implicated in the aforementioned nociceptive signals. Our data suggest that TRPA1 channels functionally associate with MORs, delta opioid receptors and NMDARs in the dorsal root ganglia, the spinal cord and brain areas. These associations were altered in response to pharmacological interventions and the induction of inflammatory and also neuropathic pain. The MOR-TRPA1 and NMDAR-TRPA1 associations do not require HINT1 or σ1R but appear to be mediated by calcium-activated calmodulin. Thus, TRPA1 channels may associate with NMDARs to promote ascending acute and chronic pain signals and to control MOR antinociception.

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Section: Resultsmentioning

confidence: 93%

Calmodulin Supports TRPA1 Channel Association with Opioid Receptors and Glutamate NMDA Receptors in the Nervous Tissue

Cortés-Montero

Rodríguez-Muñoz

Ruiz-Cantero

et al. 2020

IJMS

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“…Deep learning has been used in the prediction of PTM sites for phosphorylation, [96][97][98][99][100] ubiquitination, [101,102] acetylation, [103][104][105][106] glycosylation, [107] malonylation, [108,109] succinylation, [110,111] glycation, [112] nitration/nitrosylation, [113] crotonylation [114] and other modifications [115][116][117]224] as shown in Table 3. MusiteDeep, the first deep learning-based PTM prediction tool, provides both general phosphosite prediction and kinase-specific phosphosite prediction for five kinase families, each with more than 100 known substrates.…”

Section: Deep Learning For Post-translational Modification Predictionmentioning

confidence: 99%

Deep Learning in Proteomics

et al. 2020

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Proteomics, the study of all the proteins in biological systems, is becoming a data-rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS) technology, protein expression and post-translational modifications (PTMs) can be studied in a variety of biological systems at the global scale. Sophisticated computational algorithms are needed to translate the vast amount of data into novel biological insights. Deep learning automatically extracts data representations at high levels of abstraction from data, and it thrives in data-rich scientific research domains. Here, a comprehensive overview of deep learning applications in proteomics, including retention time prediction, MS/MS spectrum prediction, de novo peptide sequencing, PTM prediction, major histocompatibility complex-peptide binding prediction, and protein structure prediction, is provided. Limitations and the future directions of deep learning in proteomics are also discussed. This review will provide readers an overview of deep learning and how it can be used to analyze proteomics data.

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“…Protein glycosylation is one of the most abundant post-translational modifications, which affects almost every aspect of protein from synthesis to playing physiological function [10]. According to the amino acid atom where sugar moiety attached to, the glycosylation is classified as different types including N-, O-and C-linked glycosylation [11].…”

Section: Intrudction：mentioning

confidence: 99%

Altered N-/O-Glycosylation Sites On The Receptor-Binding Domain (RBD) in COVID-19 Are Related To Coronavirus Infection And Pathogenesis.

Wang

Xiao

et al. 2021

Preprint

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Objective: To discuss the possible significances of N-Linked and O-Linked glycosylation on the RBD of COVID-19Methods: Amino acid sequences multiple alignments of RBD used Clustal Omega (v.1.2.4) using default parameters. Prediction of potential N-linked glycosylation sites by NetNGlyc 1.0 server. Prediction of potential O-linked glycosylation sites by NetOGlyc 4.0 Server.Result: COVID-19 Spike glycoprotein has 22 potential N-linked glycosylation sites and 3 O-linked glycosylation sites. 2 of 22 N-linked glycosylation sites distributed in RBD. None of the 3 O-linked glycosylation sites distributed in RBD, which is markedly different from SARS and other bat coronavirus using ACE2 as a receptor. Comparing with its close coronavirus, but which can’t use ACE2 as a receptor, the COVID-19 has little N- and O-linked glycosylation sites.Conclusion: we show the obvious differences in glycosylation sites in RBD between COVID-19 and other coronaviruses. We speculate that altered N-/O-glycosylation sites on RBD in COVID-19 are related to its infection and pathogenesis.

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SPRINT-Gly: predictingN-andO-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties

Cited by 57 publications

References 51 publications

Calmodulin Supports TRPA1 Channel Association with Opioid Receptors and Glutamate NMDA Receptors in the Nervous Tissue

Calmodulin Supports TRPA1 Channel Association with Opioid Receptors and Glutamate NMDA Receptors in the Nervous Tissue

Deep Learning in Proteomics

Altered N-/O-Glycosylation Sites On The Receptor-Binding Domain (RBD) in COVID-19 Are Related To Coronavirus Infection And Pathogenesis.

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