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Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome

Dengue virus (DENV) is a major mosquito vector based human pathogenic flavivirus which is causing major threat worldwide, yet the availability of therapeutic treatment and several vaccines, still called for advance treatment and vaccine development. The present top down computational approach is a v...

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Autores principales: Sharma, Priti, Sharma, Pawan, Sheeba, Kumar, Ajay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921607/
https://www.ncbi.nlm.nih.gov/pubmed/33679273
http://dx.doi.org/10.1007/s10989-021-10184-1
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author Sharma, Priti
Sharma, Pawan
Sheeba
Kumar, Ajay
author_facet Sharma, Priti
Sharma, Pawan
Sheeba
Kumar, Ajay
author_sort Sharma, Priti
collection PubMed
description Dengue virus (DENV) is a major mosquito vector based human pathogenic flavivirus which is causing major threat worldwide, yet the availability of therapeutic treatment and several vaccines, still called for advance treatment and vaccine development. The present top down computational approach is a vaccine development step to find novel super antigenic HLA binding epitopes from DENV proteome. The approach used sequence based screening to find complete conserve and high population coverage, common epitopes among all DENV serotype. Propred and Immune Epitope Data Base were used for sequence based screening with recommended parameters. Among top 29 identified epitopes, five structural protein epitopes viz. (33)LQGRGPLKL(41), (249)VVVLGSQEG(257), (172)LVGIVTLYL(180), (146)MKILIGVVI(154), (72)YIIVGVEPG(80) and one nonstructural protein epitope (18)LKNDIPMTG(26) were showed high conserve nature and high population coverage from complete DENV proteome. Further structure based study involving docking and molecular dynamic simulation to confirm stable behavior of HLA allele–peptide complex to give potent cell mediated immune response. Docking of epitope (72)YIIVGVEPG(80)–DRB1 0401 allele and epitope (33)LQGRGPLKL(41)–B*5101 allele complexes showed the best binding energy of − 7.71 and − 7.20 kcal/mol, respectively and stable binding pattern over the time window during molecular dynamic simulation. This computational approach resulted novel epitopes which can be used in the design and development of short epitope based vaccines as well as diagnosis tools for dengue infection.
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spelling pubmed-79216072021-03-02 Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome Sharma, Priti Sharma, Pawan Sheeba Kumar, Ajay Int J Pept Res Ther Article Dengue virus (DENV) is a major mosquito vector based human pathogenic flavivirus which is causing major threat worldwide, yet the availability of therapeutic treatment and several vaccines, still called for advance treatment and vaccine development. The present top down computational approach is a vaccine development step to find novel super antigenic HLA binding epitopes from DENV proteome. The approach used sequence based screening to find complete conserve and high population coverage, common epitopes among all DENV serotype. Propred and Immune Epitope Data Base were used for sequence based screening with recommended parameters. Among top 29 identified epitopes, five structural protein epitopes viz. (33)LQGRGPLKL(41), (249)VVVLGSQEG(257), (172)LVGIVTLYL(180), (146)MKILIGVVI(154), (72)YIIVGVEPG(80) and one nonstructural protein epitope (18)LKNDIPMTG(26) were showed high conserve nature and high population coverage from complete DENV proteome. Further structure based study involving docking and molecular dynamic simulation to confirm stable behavior of HLA allele–peptide complex to give potent cell mediated immune response. Docking of epitope (72)YIIVGVEPG(80)–DRB1 0401 allele and epitope (33)LQGRGPLKL(41)–B*5101 allele complexes showed the best binding energy of − 7.71 and − 7.20 kcal/mol, respectively and stable binding pattern over the time window during molecular dynamic simulation. This computational approach resulted novel epitopes which can be used in the design and development of short epitope based vaccines as well as diagnosis tools for dengue infection. Springer Netherlands 2021-03-02 2021 /pmc/articles/PMC7921607/ /pubmed/33679273 http://dx.doi.org/10.1007/s10989-021-10184-1 Text en © The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Sharma, Priti
Sharma, Pawan
Sheeba
Kumar, Ajay
Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome
title Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome
title_full Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome
title_fullStr Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome
title_full_unstemmed Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome
title_short Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome
title_sort top down computational approach: a vaccine development step to find novel superantigenic hla binding epitopes from dengue virus proteome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7921607/
https://www.ncbi.nlm.nih.gov/pubmed/33679273
http://dx.doi.org/10.1007/s10989-021-10184-1
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