Nipah Open Library

An Immunoinformatic-Based In Silico Identification on the Creation of a Multiepitope-Based Vaccination Against the Nipah Virus

Revision as of 02:16, 7 February 2026 by Nhmkerala (talk | contribs) (Created paper page - 2026-02-07T07:46:12.726960)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Authors: Beant Kaur, Arun Karnwal, Anu Bansal, Tabarak Malik

Year: 2024

Journal: BioMed Research International

DOI: 10.1155/2024/4066641

Summary

This paper describes an in silico study that identifies epitopes from the conserved region of NiV proteins and constructs a multiepitope-based vaccine candidate. The final vaccine candidate has a total combined coverage range of 80.53%.

Key Findings

  • Two B cell epitopes, seven cytotoxic T lymphocyte (CTL) epitopes, and seven helper T lymphocyte (HTL) epitope interactions from the NiV proteomic inventory were identified
  • The tertiary structure of the constructed vaccine was optimized, its stability confirmed with molecular simulation, and molecular docking performed to check binding affinity and energy with TLR-3 and TLR-5

Methodology

  • Study Type: In Silico Study

Topics

Immunoinformatics, Vaccine Development, Nipah Virus

Relevance

The development of a multiepitope-based vaccine against the Nipah virus could provide a potential strategy for preventing and controlling NiV infections.

Source

View the entire paper: File:BMRI2024-4066641.pdf

Retrieved from "https://nipahlib.phenomi.co/index.php?title=An_Immunoinformatic-Based_In_Silico_Identification_on_the_Creation_of_a_Multiepitope-Based_Vaccination_Against_the_Nipah_Virus&oldid=304"