Abstract

Nipah virus is one of the most harmful emerging viruses with deadly effects on both humans and animals. Because of the severe outbreaks, in 2018, the World Health Organization focused on the urgent need for the development of effective solutions against the virus. However, up to date, there is no effective vaccine against the Nipah virus in the market. In the current study, the complete proteome of the Nipah virus (nine proteins) was analyzed for the antigenicity score and the virulence role of each protein, where we came up with fusion glycoprotein (F), glycoprotein (G), protein (V), and protein (W) as the candidates for epitope prediction. Following that, the multitope vaccine was designed based on top-ranking CTL, HTL, and BCL epitopes from the selected proteins. We used suitable linkers, adjuvant, and PADRE peptides to finalize the constructed vaccine, which was analyzed for its physicochemical features, antigenicity, toxicity, allergenicity, and solubility. The designed vaccine passed these assessments through computational analysis and, as a final step, we ran a docking analysis between the designed vaccine and TLR-3 and validated the docked complex through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for Nipah virus. Here, we describe the computational approach for design and analysis of this vaccine.

Highlights

  • Nipah virus (NiV) is a zoonotic notorious pathogen that belongs to the Paramyxoviridae family

  • Before passing to the epitope prediction stage, we concluded that there is a high degree of similarity between the sequences of V and W proteins, we selected only protein V for epitope prediction, and one of the major criteria in the filtration of the predicted epitopes from V protein was that the epitope must show cross similarity between both V and W proteins

  • The Codon Adaptation of an effective drug that can as cure patients and reduce the high fatalityof rate of NiV, the dicted through computational approaches against several microorganisms such as Mayaro virus [27], Lassa virus [28], COVID-19 [29], and E. coli [30], where the predicted vaccine of the last study was expressed and analyzed through wet lab experimental validation and showed protection against urinary tract infection caused by uropathogenic E. coli in animal models

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Summary

Introduction

Nipah virus (NiV) is a zoonotic notorious pathogen that belongs to the Paramyxoviridae family. In a recent outbreak in 2018, the fatality rate was estimated to be 91%. The journey of NiV transmission to various hosts starts from the fruit bat (Pteropus species), which represents the viral reservoir, and when these bats drop their saliva or urine on fruits that would be consumed by humans and animals, viral infection occurs [3]. Cases usually suffer from mild to moderate symptoms of headache, vomiting, and fever where these symptoms may develop into severe encephalitis or acute harmful manifestations to the respiratory system, leading eventually to death [5]. Because of the high virulence, the simple way of dissemination, and the continuously elevated rates of mortality and morbidity of the viral outbreaks, NiV was categorized as a biosafety level 4 virus [6]

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