Development of a multi-epitope vaccine candidate against Sindbis virus through integrated immunoinformatics approaches and molecular dynamics simulations
Date
2026-01-05Author
Ishaque Ira, Nabila
Jaishee, Nishika
Saha, Ayan
Naidoo, Devashan
Islam, Shazneen Tasnim
Tani, Tazneen Hossain
Roy, Ayan
Metadata
Show full item recordAbstract
Sindbis virus (SINV), belonging to the genus Alphavirus, is the causative agent of Pogosta disease in humans. The
clinical infection is characterized by fever, malaise, rash, myalgia, and arthralgia, which is generally self
limiting. Chronic infection with SINV triggers autoimmune conditions that lead to persistent arthritis. Despite
its clinical relevance, no licensed vaccine is currently available for the prevention of SINV infection. To the best
of our knowledge, this study presents the first in silico design and evaluation of a multi-epitope vaccine candidate
against SINV. Using an integrated immunoinformatics framework, the SINV structural polyprotein was sys
tematically screened, leading to the identification of twelve highly antigenic immunological hotspots, derived
from both experimentally validated and computationally predicted B-cell and T-cell epitopes. These epitopes
were rationally assembled into a 317–amino acid multi-epitope vaccine construct using suitable linkers and the
human β-defensin 2 as an immunostimulatory adjuvant. The designed construct exhibited favorable antigenicity,
non-toxicity, stability, and physicochemical properties. Molecular docking and molecular dynamics simulations
demonstrated encouraging interactions between the vaccine construct and innate immune receptors TLR-2 and
TLR-4, highlighting its potential to trigger immune responses. Immune simulation predicted robust humoral and
cell-mediated immune responses, while codon optimization and in silico cloning into the pETite vector indicated
expression feasibility in Escherichia coli K12. This work proposes a novel immunoinformatics and molecular
dynamics–based vaccine design pipeline for Sindbis virus and presents a computationally validated multi-epitope
vaccine candidate, providing a foundation for future experimental validation toward effective vaccine
development.
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