In silico evidence of superantigenic features in ORF8 protein from COVID-19
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Abstract
Very early on COVID-19 pandemic outbreak, it was noted that the some of the virus-induced clinical conditions resembled features of toxaemia caused by the toxic shock syndrome toxin type 1, which is a soluble superantigen produced by Staphylococcus aureus . Among all SARS proteins, the ORF8 protein from SARS-2 virus is significantly different from other known SARS-like coronaviruses, and therefore could exhibit unique pathogenic properties. We assess if ORF8 protein bears super antigenic features using in silico tools. We show that ORF8 has properties of an extracellular soluble protein and shares a significant degree of amino acid sequence identity with toxic shock syndrome toxin. Besides, docking and binding affinity analyses between monomeric and homodimeric ORF-8 with Vβ 2.1 and TRBV11-2 reveal strong interaction and high binding affinity. ORF8-TRBV11-2 strong interaction can contribute to the observed clonal expansion of that chain during COVID-19-associated multisystem inflammatory syndrome. Taken together, the evidence presented here supports the hypothesis that ORF8 protein from SARS-2 bears super antigenic properties.
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SciScore for 10.1101/2021.12.14.472240: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The signal peptide in ORF8 was predicted using SignalP 5, an algorithm software that predicts signal peptides and cleavage site [25]. SignalPsuggested: (SignalP, RRID:SCR_015644)Basic secondary structure of ORF8 was predicted using PredictProtein, an algorithm software that predict secondary structure of proteins based on a wide array of protein features [26] PredictProteinsuggested: NoneAmino acid similarity analysis: The amino acid (aa) similarity analyses between ORF8 and TSST were performed using protein BLAST, [27] and Clustal Omega [28], with default settings. BLASTsuggested: (BLASTX, …SciScore for 10.1101/2021.12.14.472240: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources The signal peptide in ORF8 was predicted using SignalP 5, an algorithm software that predicts signal peptides and cleavage site [25]. SignalPsuggested: (SignalP, RRID:SCR_015644)Basic secondary structure of ORF8 was predicted using PredictProtein, an algorithm software that predict secondary structure of proteins based on a wide array of protein features [26] PredictProteinsuggested: NoneAmino acid similarity analysis: The amino acid (aa) similarity analyses between ORF8 and TSST were performed using protein BLAST, [27] and Clustal Omega [28], with default settings. BLASTsuggested: (BLASTX, RRID:SCR_001653)Clustal Omegasuggested: (Clustal Omega, RRID:SCR_001591)Modelling of monomeric ORF8: Model of monomeric ORF8 was developed using Galaxy TBM (33) [33], followed by energy minimization using Swiss PDB Viewer version 4.1.0 and refinement using Galaxy refine tool of Galaxy web [34]. Galaxysuggested: (Galaxy, RRID:SCR_006281)Ramachandran analyses were carried out using ProCheck [37]. ProChecksuggested: (PROCHECK, RRID:SCR_019043)Binding sites determination: Binding sites determination for Homodimer ORF8, Vβ 2.1, TRBV11-2 and monomeric ORF8 was carried using SPPIDER [38] and Meta-PPISP [39] and common binding site residues from both servers were used as binding sites residues for docking. SPPIDERsuggested: NoneThe interacting amino acids residues analysis were done using PyMol version 2.4.1 [30] PyMolsuggested: (PyMOL, RRID:SCR_000305)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- No funding statement was detected.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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