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Strategic Development of a Next-Generation Multi-Epitope Vaccine To Prevent Nipah Virus Zoonotic Infection

Authors: Rupal Ojha; Aditi Pareek; Rajan K. Pandey; Dhaneswar Prusty; Vijay K. Prajapati;

Strategic Development of a Next-Generation Multi-Epitope Vaccine To Prevent Nipah Virus Zoonotic Infection

Abstract

Nipah virus (NiV) is an emerging zoonotic pathogen, reported for the recent severe outbreaks of encephalitis and respiratory illness in humans and animals, respectively. Many antiviral drugs have been discovered to inhibit this pathogen, but none of them were that much efficient. To overcome the complications associated with this severe pathogenic virus, we have designed a multi-epitope subunit vaccine using computational immunology strategies. Identification of structural and nonstructural proteins of Nipah virus assisted in the vaccine designing. The selected proteins are known to be involved in the survival of the virus. The antigenic binders (B-cell, HTL, and CTL) from the selected proteins were prognosticated. These antigenic binders will be able to generate the humoral as well as cell-mediated immunity. All the epitopes were united with the help of suitable linkers and with an adjuvant at the N-terminal of the vaccine, for the enhancement of immunogenicity. The physiological characterization, along with antigenicity and allergenicity of the designed vaccine candidates, was estimated. The 3D structure prediction and its validation were performed. The validated vaccine model was then docked and simulated with the TLR-3 receptor to check the stability of the docked complex. This next-generation approach will provide a new vision for the development of a high immunogenic vaccine against the NiV.

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Keywords

Chemistry, QD1-999

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
65
Top 1%
Top 10%
Top 1%
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gold