Epitope-based immunoinformatics approach on RNA-dependent RNA polymerase (RdRp) protein complex of Nipah virus (NiV).

Nipah virus epitope-based vaccine design molecular docking molecular dynamics nucleocapsid protein phosphoprotein and polymerase

Journal

Journal of cellular biochemistry
ISSN: 1097-4644
Titre abrégé: J Cell Biochem
Pays: United States
ID NLM: 8205768

Informations de publication

Date de publication:
May 2019
Historique:
received: 03 08 2018
accepted: 04 10 2018
pubmed: 13 11 2018
medline: 13 11 2018
entrez: 13 11 2018
Statut: ppublish

Résumé

Persistent outbreaks of Nipah virus (NiV) with severe case fatality throw a major challenge on researchers to develop a drug or vaccine to combat the disease. With little knowledge of its molecular mechanisms, we utilized the proteome data of NiV to evaluate the potency of three major proteins (phosphoprotein, polymerase, and nucleocapsid protein) in the RNA-dependent RNA polymerase complex to count as a possible candidate for epitope-based vaccine design. Profound computational analysis was used on the above proteins individually to explore the T-cell immune properties like antigenicity, immunogenicity, binding to major histocompatibility complex class I and class II alleles, conservancy, toxicity, and population coverage. Based on these predictions the peptide 'ELRSELIGY' of phosphoprotein and 'YPLLWSFAM' of nulceocapsid protein were identified as the best-predicted T-cell epitopes and molecular docking with human leukocyte antigen-C (HLA-C*12:03) molecule was effectuated followed by validation with molecular dynamics simulation. The B-cell epitope predictions suggest that the sequence positions 421 to 471 in phosphoprotein, 606 to 640 in polymerase and 496 to 517 in nucleocapsid protein are the best-predicted regions for B-cell immune response. However, the further experimental circumstance is required to test and validate the efficacy of the subunit peptide for potential candidacy against NiV.

Identifiants

pubmed: 30417438
doi: 10.1002/jcb.27979
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

7082-7095

Informations de copyright

© 2018 Wiley Periodicals, Inc.

Auteurs

Lavanya Ravichandran (L)

Department of Integrative Biology, School of BioSciences and Technology (SBST), VIT, Vellore, India.

Arthi Venkatesan (A)

Department of Integrative Biology, School of BioSciences and Technology (SBST), VIT, Vellore, India.

J Febin Prabhu Dass (J)

Department of Integrative Biology, School of BioSciences and Technology (SBST), VIT, Vellore, India.

Classifications MeSH