About: Immunoinformatic approach to assess SARS-CoV-2 protein S epitopes recognised by the most frequent MHC-I alleles in the Brazilian population

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About: Immunoinformatic approach to assess SARS-CoV-2 protein S epitopes recognised by the most frequent MHC-I alleles in the Brazilian population 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	Immunoinformatic approach to assess SARS-CoV-2 protein S epitopes recognised by the most frequent MHC-I alleles in the Brazilian population
Creator	Crovella, Sergio Agrelli, Almerinda Assunção, Bruno Benko-Iseppon, Ana Brandão, Lucas Santos-Silva, Carlos Silva, Natália Rodrigues De Moura, Ronald
Source	Medline; PMC
abstract	AIMS: Brazil is nowadays one of the epicentres of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and new therapies are needed to face it. In the context of specific immune response against the virus, a correlation between Major Histocompatibility Complex Class I (MHC-I) and the severity of the disease in patients with COVID-19 has been suggested. Aiming at better understanding the biology of the infection and the immune response against the virus in the Brazilian population, we analysed SARS-CoV-2 protein S peptides in order to identify epitopes able to elicit an immune response mediated by the most frequent MHC-I alleles using in silico methods. METHODS: Our analyses consisted in searching for the most frequent Human Leukocyte Antigen (HLA)-A, HLA-B and HLA-C alleles in the Brazilian population, excluding the genetic isolates; then, we performed: molecular modelling for unsolved structures, MHC-I binding affinity and antigenicity prediction, peptide docking and molecular dynamics of the best fitted MHC-I/protein S complexes. RESULTS: We identified 24 immunogenic epitopes in the SARS-CoV-2 protein S that could interact with 17 different MHC-I alleles (namely, HLA-A01:01; HLA-A02:01; HLA-A11:01; HLA-A24:02; HLA-A68:01; HLA-A23:01; HLA-A26:01; HLA-A30:02; HLA-A31:01; HLA-B07:02; HLA-B51:01; HLA-B35:01; HLA-B44:02; HLA-B35:03; HLA-C05:01; HLA-C07:01 and HLA-C*15:02) in the Brazilian population. CONCLUSIONS: Being aware of the intrinsic limitations of in silico analysis (mainly the differences between the real and the Protein Data Bank (PDB) structure; and accuracy of the methods for simulate proteasome cleavage), we identified 24 epitopes able to interact with 17 MHC-I more frequent alleles in the Brazilian population that could be useful for the development of strategic methods for vaccines against SARS-CoV-2.
has issue date	2020-08-05(xsd:dateTime)
bibo:doi	10.1136/jclinpath-2020-206946
bibo:pmid	32759312
has license	no-cc
sha1sum (hex)	48baa7cf2bc04bdd98f4abc8311732ff557febd3
schema:url	https://doi.org/10.1136/jclinpath-2020-206946
resource representing a document's title	Immunoinformatic approach to assess SARS-CoV-2 protein S epitopes recognised by the most frequent MHC-I alleles in the Brazilian population
has PubMed Central identifier	PMC7409971
has PubMed identifier	32759312
schema:publication	J Clin Pathol
resource representing a document's body	covid:48baa7cf2bc04bdd98f4abc8311732ff557febd3#body_text
is schema:about of	named entity 'alleles' named entity 'MHC-I' named entity 'SARS-CoV-2' named entity 'extracellular' named entity 'PDB' named entity 'vaccines' named entity 'COVID-19' named entity 'GROMACS' named entity 'proteasomal' named entity 'peptides' named entity 'antigenicity' named entity 'endoplasmic reticulum' named entity 'alleles' named entity 'HLA-C' named entity 'N-terminal' named entity 'solvent accessible surface area' named entity 'hydrogen bonds' named entity 'proteasome' named entity 'immunogenic' named entity 'nucleocapsid' named entity 'alleles' named entity 'HLA-A' named entity 'MHC-I' named entity 'immune response' named entity 'receptor binding' named entity 'epidemic' named entity 'antigenicity' named entity 'Coronaviridae' named entity 'protein' named entity 'HLA-B' named entity 'transporter associated with antigen processing' named entity 'Quilombos' named entity 'CD8 +' named entity 'inflammatory cascade' named entity 'peptides' named entity 'alleles' named entity 'alleles' named entity 'peptides' named entity 'binding affinity' named entity 'antigen presentation' named entity 'MHC-I' named entity 'binding affinity' named entity 'CD8 +' named entity 'fatality rate' named entity 'peptidase' named entity 'Betacoronavirus' named entity 'antigenic peptides' named entity 'kidney' named entity 'alleles' named entity 'HLA-C' named entity 'SARS-CoV-2' named entity 'antigenic peptides' named entity 'SARS-CoV-2' named entity 'Wuhan' named entity 'HLA-A' named entity 'SARS-CoV-2' named entity 'Hubei province, China' named entity 'peptides' named entity 'kilobases' named entity 'nucleocapsid' named entity 'MHC-I' named entity 'alleles' named entity 'epitope' named entity 'protein' named entity 'protein' named entity 'vaccine' named entity 'FASTA' named entity 'vaccines' named entity 'host cell' named entity '15:02' named entity 'Brazil' named entity 'nonstructural proteins' named entity 'HLA' named entity 'C-terminal'

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