Characterization of host receptor interaction with envelop protein of Kyasanur forest disease virus and predicting suitable epitopes for vaccine candidate

Dey, Sreenath; Pratibha, Manickavasagam; Dagur, Hanuman Singh; Rajakumara, Eerappa

doi:10.1080/07391102.2023.2218924

Cited by 2 publications

(2 citation statements)

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“…In this study, the envelope (E) protein of KFDV was chosen to prepare a multi-epitope vaccine candidate. Previous studies conducted on KFDV showed the suitability of the envelope protein as a candidate for newer vaccines and diagnostics 21 . The envelope protein is responsible for the entry of the virus into the host cells by receptor binding and fusion of viral and cellular membranes 8 .…”

Section: Codon Optimization and In Silico Cloningmentioning

confidence: 99%

“…The molecular docking and molecular simulations may help in understanding the binding potential of vaccine construction with host immune cell receptors 19 . Immunoinformatics has been gainfully employed for designing multi-epitope vaccine candidates against KFDV (with a relatively smaller set of genome sequences) and to understand the molecular interactions between the host receptors and virus protein recently [20][21][22] . The present work is a comprehensive phylogenomic and immunoinformatics analysis of KFDV based on 74 genome sequences to rationally design a multi-epitope vaccine candidate based on a major antigenic protein, envelope protein.…”

Section: Introductionmentioning

confidence: 99%

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Construction of an Immunoinformatics-Based Multi-Epitope Vaccine Candidate targeting Kyasanur Forest Disease Virus

Kasibhatla,

Rajan,

Shete

et al. 2024

Preprint

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Kyasanur Forest Disease (KFD) is one of the neglected tick-borne viral zoonoses. KFD virus was initially considered endemic to the Western Ghats region of Karnataka. Still, over the years, there have been reports of its spread to newer areas within and outside Karnataka. The absence of an effective treatment for KFD expedites the need for further research and development of novel vaccines. The present study was designed to develop a multi-epitope vaccine candidate against KFDV using immunoinformatic tools. After analyzing 74 complete KFDV genome sequences for genetic recombination and phylogeny, different prioritized B and T cell epitopes were combined using various linkers to construct the vaccine candidate. Docking analysis of the designed vaccine construct revealed a stable interaction with the TLR2-TLR6 receptor complex. After confirming the stability of the vaccine receptor complex, codon optimization was done to ensure the efficient translation of the designed multi-epitope vaccine in the prokaryotic host system, and the subsequentin-silicocloning into the pET30b(+) expression vector was carried out. Immunoinformatics analysis of the multi-epitope vaccine in the current study is satisfactory as it can significantly accelerate the initial stages of vaccine development by narrowing down potential vaccine candidates and providing insights into their design. Experimental validation of the potential multi-epitope vaccine candidate remains crucial to confirm effectiveness and safety in real-world conditions.

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Section: Codon Optimization and In Silico Cloningmentioning

confidence: 99%