Evidence map›Paper›PMID 42918948›Full record

ArticleVirus genes2026

In silico multi-epitope vaccine design against Irkut virus using immunoinformatic and reverse vaccinology.

Sana Rehman Cheema, Maria Laeeq, Afrah Idrees, Muhammad Shahid

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Article in Virus genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sana Rehman CheemaDivison of Molecular Virology, Centre of Excellence in Molecular Biology (CEMB), University of the Punjab, CEMB, 87-West Canal Bank Road, Thokar Niaz Baig, Lahore, Pakistan.
Maria LaeeqDivison of Molecular Virology, Centre of Excellence in Molecular Biology (CEMB), University of the Punjab, CEMB, 87-West Canal Bank Road, Thokar Niaz Baig, Lahore, Pakistan.
Afrah IdreesDivison of Molecular Virology, Centre of Excellence in Molecular Biology (CEMB), University of the Punjab, CEMB, 87-West Canal Bank Road, Thokar Niaz Baig, Lahore, Pakistan.
Muhammad ShahidDivison of Molecular Virology, Centre of Excellence in Molecular Biology (CEMB), University of the Punjab, CEMB, 87-West Canal Bank Road, Thokar Niaz Baig, Lahore, Pakistan. muhammad.shahid@cemb.edu.pk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Irkut virus (IRKV) is a member of genus Lyssavirus, which leads to fatal encephalitis in humans and is primarily found in bats and dogs that transmit the virus to humans via bites/saliva. Most cases have been reported in Russia and in Siberia and recently in China. Whole genome sequencing has shown a number of codon changes in antigenic sites common to the Rabies vaccine reducing cross-protection, which makes IRKV a serious public health threat because of its high fatality. In this study, a multi-epitope vaccine against the IRKV glycoprotein was designed via reverse vaccinology approach. Seven B-cell, seven MHC-I, and seven MHC-II epitopes were selected. These epitopes have predicted HLA binding affinity and are non-allergen, and 12 out of 21 epitopes were fully conserved across the three circulating IRKV strains, whereas remaining nine carried out one or two substitutions. The chosen epitopes covered 99.57% of the world population. The final construct which included an adjuvant (EAAAK), epitopes, and a 6xHis tag was predicted to be highly antigenic (VaxiJen score 0.8112) and non-allergenic (AllerTop), showing no sequence mimicry with human proteins by BLASTp screening. The physicochemical analysis suggested that the construct was basic, hydrophilic, and stable (aliphatic index 68.11, instability index 37.5, pI 10.43, GRAVY -0.323). The 3D structure built using SWISS-MODEL and Phyre2 and refined by GalaxyRefine depicts that 95.1% of residues lie in the favored regions of the Ramachandran plot. The structural superposition with the native viral glycoprotein showed that the native fold was well preserved (core RMSD ≈ 2.4 Å). The molecular docking with TLR4 (minimum energy -1086.3) and normal mode analysis further suggested the stability of the receptor binding and structural integrity. C-ImmSim immune simulation with two doses (prime-boost) showed an enhanced secondary immune response following boost dose, manifested by a higher level of IgM, IgG, CD4+ T-helper cells activation, and cytokine production. The immune activation profile predicted was generally similar to that for the full-length G protein, and the CD8+ T-cell response was similar between the two antigens in the one simulation run. These results indicate that the multi-epitope construct vaccine is structurally stable and immunologically promising and can be used as a vaccine candidate for further experimental evaluation against Irkut virus.

Indexed as

Immune simulationIrkut virusMolecular dockingMulti-epitope vaccineNormal mode analysisPopulation coverage

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.