About: Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV

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About: Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV
Creator	Hasan, Shihab Khan, Amran Gazi, Md Anik, Ashfaq Golam Kibria, Md Morshed, Mohammed Musa, Tuhin Ali, Mohammad Uddin, Jashim
Source	Medline; PMC
abstract	Middle East Respiratory Syndrome Coronavirus (MERS-CoV) belongs to the coronaviridae family. In spite of several outbreaks in the very recent years, no vaccine against this deadly virus is developed yet. In this study, the receptor binding domain (RBD) of Spike (S) glycoprotein of MERS-CoV was analyzed through Computational Immunology approach to identify the antigenic determinants (epitopes). In order to do so, the sequences of S glycoprotein that belong to different geographical regions were aligned to observe the conservancy of MERS-CoV RBD. The immune parameters of this region were determined using different in silico tools and Immune Epitope Database (IEDB). Molecular docking study was also employed to check the affinity of the potential epitope towards the binding cleft of the specific HLA allele. The N-terminus RBD (S367-S606) of S glycoprotein was found to be conserved among all the available strains of MERS-CoV. Based on the lower IC(50) value, a total of eight potential T-cell epitopes and 19 major histocompatibility complex (MHC) class-I alleles were identified for this conserved region. A 9-mer epitope CYSSLILDY displayed interactions with the maximum number of MHC class-I molecules and projected the highest peak in the B-cell antigenicity plot which concludes that it could be a better choice for designing an epitope based peptide vaccine against MERSCoV considering that it must undergo further in vitro and in vivo experiments. Moreover, in molecular docking study, this epitope was found to have a significant binding affinity of -8.5 kcal/mol towards the binding cleft of the HLA-C*12:03 molecule.
has issue date	2014-08-30(xsd:dateTime)
bibo:doi	10.6026/97320630010533
bibo:pmid	25258490
has license	no-cc
sha1sum (hex)	f898a667de6c7ad8916d2e542498e953589be8d7
schema:url	https://doi.org/10.6026/97320630010533
resource representing a document's title	Computer aided prediction and identification of potential epitopes in the receptor binding domain (RBD) of spike (S) glycoprotein of MERS-CoV
has PubMed Central identifier	PMC4166774
has PubMed identifier	25258490
schema:publication	Bioinformation
resource representing a document's body	covid:f898a667de6c7ad8916d2e542498e953589be8d7#body_text
is schema:about of	named entity 'MERS-CoV' named entity 'deadly' named entity 'outbreaks' named entity 'peak' named entity 'Immunology' named entity 'plot' named entity 'RBD' named entity '28S' named entity 'DOMAIN' named entity 'POTENTIAL' named entity 'COMPUTER' named entity 'MHC' named entity '28S' named entity 'IMMUNE PARAMETERS' named entity 'RECENT' named entity 'ALIGNED TO' named entity 'CONSERVED REGION' named entity 'HIGHEST' named entity 'B-CELL' named entity 'LOWER' named entity 'REGION' named entity 'CHECK' named entity 'MOLECULES' named entity 'ANALYZED' named entity 'YEARS' named entity 'APPROACH' named entity 'PROJECTED' named entity 'MOLECULAR DOCKING' named entity 'HLA-C' named entity 'IC50' named entity 'IMMUNE' named entity 'CONCLUDES' named entity 'MAJOR HISTOCOMPATIBILITY COMPLEX' named entity 'PEAK' named entity 'COMPUTATIONAL IMMUNOLOGY' named entity 'TOTAL' named entity 'EXPERIMENTS' named entity 'VACCINE' named entity 'FAMILY' named entity 'DATABASE' named entity 'STUDY' named entity 'BINDING' named entity 'GLYCOPROTEIN' named entity 'MERS-COV' named entity 'IDENTIFICATION' named entity 'GEOGRAPHICAL REGIONS' named entity 'EPITOPES' named entity 'HAVE' named entity 'RECEPTOR BINDING' named entity 'TOOLS' named entity 'BETTER' named entity 'DOMAIN' named entity 'PLOT' named entity 'ORDER' named entity 'GLYCOPROTEIN' named entity 'PREDICTION' named entity 'HYPOTHESIS' named entity 'EPITOPES' named entity 'SPIKE' named entity 'STRAINS' named entity 'OUTBREAKS' named entity 'SIGNIFICANT' named entity 'EMPLOYED' named entity 'MAXIMUM' named entity 'MIDDLE EAST RESPIRATORY SYNDROME CORONAVIRUS' named entity 'TO IDENTIFY' named entity 'PEPTIDE VACCINE' named entity 'FOUND' named entity 'T-CELL' named entity 'RECEPTOR BINDING' named entity 'SEQUENCES' named entity 'IN VIVO' named entity 'COULD BE'

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