About: Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach

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About: Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach
Creator	Alam, Mohammad Fariha, Atqiya Hami, Ithmam Islam, Mahafujul Khalil Afif, Ibrahim Munim, Roy, Arpita Shahadat Hossain, Tonmoy, Quadery
topic	covid:094ceeee930e8ed5f23280096a3c6efd4c92237a#this
Source	BioRxiv
abstract	Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the novel coronavirus responsible for the ongoing pandemic of coronavirus disease (COVID-19). No sustainable treatment option is available so far to tackle such a public health threat. Therefore, designing a suitable vaccine to overcome this hurdle asks for immediate attention. In this study, we targeted for a design of multi-epitope based vaccine using immunoinformatics tools. We considered the structural proteins S, E and, M of SARS-CoV-2, since they facilitate the infection of the virus into host cell and using different bioinformatics tools and servers, we predicted multiple B-cell and T-cell epitopes having potential for the required vaccine design. Phylogenetic analysis provided insight on ancestral molecular changes and molecular evolutionary relationship of S, E, and M proteins. Based on the antigenicity and surface accessibility of these proteins, eight epitopes were selected by various B cell and T cell epitope prediction tools. Molecular docking was executed to interpret the binding interactions of these epitopes and three potential epitopes WTAGAAAYY, YVYSRVKNL, and GTITVEELK were selected for their noticeable higher binding affinity scores −9.1, −7.4, and −7.0 kcal/mol, respectively. Targeted epitopes had 91.09% population coverage worldwide. In summary, we identified three epitopes having the most significant properties of designing the peptide-based vaccine against SARS-CoV-2.
has issue date	2020-06-13(xsd:dateTime)
bibo:doi	10.1101/2020.06.13.149880
has license	biorxiv
sha1sum (hex)	094ceeee930e8ed5f23280096a3c6efd4c92237a
schema:url	https://doi.org/10.1101/2020.06.13.149880
resource representing a document's title	Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach
schema:publication	bioRxiv
resource representing a document's body	covid:094ceeee930e8ed5f23280096a3c6efd4c92237a#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/094ceeee930e8ed5f23280096a3c6efd4c92237a
is schema:about of	named entity 'SARS-CoV-2' named entity 'vaccine' named entity 'antigenicity' named entity 'tools' named entity 'Severe Acute Respiratory Syndrome Coronavirus' named entity 'executed' named entity 'bioinformatics' named entity 'Vaccine' named entity 'MULTI' named entity 'OVERCOME' named entity 'ATTENTION' named entity 'PROVIDED' named entity 'MOLECULAR DOCKING' named entity 'PHYLOGENETIC ANALYSIS' named entity 'PUBLIC HEALTH' named entity 'EPITOPES' named entity 'TARGETED' named entity 'EXECUTED' named entity 'DIFFERENT' named entity 'VACCINE' named entity 'VIRUS' named entity 'BINDING' named entity 'INFECTION' named entity 'POTENTIAL' named entity 'ongoing' named entity 'B-cell' named entity 'public health' named entity 'interactions' named entity 'pandemic' named entity 'epitope' named entity 'epitopes' named entity 'responsible' named entity 'B-cell' named entity 'infection' named entity 'bioinformatics' named entity 'vaccine' named entity 'SARS-CoV-2' named entity 'epitopes' named entity 'binding affinity' named entity 'T-cell' named entity 'host' named entity 'SARS-CoV-2' named entity 'potential' named entity 'antigenicity' named entity 'virus' named entity 'protein' named entity 'vaccine design' named entity 'phylogenetic tree' named entity 'immune response' named entity 'virus' named entity 'infection' named entity 'cell mediated' named entity 'Vaccine' named entity 'protein' named entity 'virus' named entity 'peptide' named entity 'epitope' named entity 'HLA' named entity 'phylogenetic trees' named entity 'Betacoronavirus' named entity 'hydrophilicity' named entity '2019-nCoV' named entity 'T-cell' named entity 'amino acids' named entity 'peptide' named entity 'HLA' named entity 'proteome' named entity 'envelope proteins' named entity 'Hydrophilicity' named entity 'SARS-Cov-2' named entity '229E' named entity 'SARS-CoV-2' named entity 'SARS-CoV' named entity 'COVID 19'

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