Kasibhatla Sunitha Manjari, Rajan Lekshmi, Shete Anita, Jani Vinod, Yadav Savita, Joshi Yash, Sahay Rima, Patil Deepak Y, Mohandas Sreelekshmy, Majumdar Triparna, Sonavane Uddhavesh, Joshi Rajendra, Yadav Pragya
Centre for Development of Advanced Computing, Pune, India.
Indian Council of Medical Research-National Institute of Virology, Pune, India.
PeerJ. 2025 Mar 21;13:e18982. doi: 10.7717/peerj.18982. eCollection 2025.
Kyasanur forest disease (KFD) is one of the neglected tick-borne viral zoonoses. KFD virus (KFDV) was initially considered endemic to the Western Ghats region of Karnataka state in India. 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 mandates 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 immunoinformatics approaches. A total of 74 complete KFDV genome sequences were analysed for genetic recombination followed by phylogeny. Computational prediction of B- and T-cell epitopes belonging to envelope protein was performed and epitopes were prioritised based on IFN-Gamma, IL-4, IL-10 stimulation and checked for allergenicity and toxicity. The eight short-listed epitopes (three MHC-Class 1, three MHC-Class 2 and two B-cell) were then combined using various linkers to construct the vaccine candidate. Molecular docking followed by molecular simulations revealed stable interactions of the vaccine candidate with immune receptor complex namely Toll-like receptors (TLR2-TLR6). Codon optimization followed by cloning of the designed multi-epitope vaccine construct into the pET30b (+) expression vector was carried out. Immunoinformatics analysis of the multi-epitope vaccine candidate in the current study has potential to significantly accelerate the initial stages of vaccine development. Experimental validation of the potential multi-epitope vaccine candidate remains crucial to confirm effectiveness and safety in real-world conditions.
基孔肯雅森林病（KFD）是一种被忽视的蜱传病毒性人畜共患病。基孔肯雅森林病病毒（KFDV）最初被认为是印度卡纳塔克邦西高止山脉地区的地方病。多年来，有报道称其已传播到卡纳塔克邦内外的新地区。由于缺乏针对基孔肯雅森林病的有效治疗方法，因此需要进一步研发新型疫苗。本研究旨在利用免疫信息学方法开发一种针对KFDV的多表位疫苗候选物。共分析了74个完整的KFDV基因组序列的基因重组情况，随后进行了系统发育分析。对包膜蛋白的B细胞和T细胞表位进行了计算预测，并根据干扰素-γ、白细胞介素-4、白细胞介素-10刺激对表位进行了优先级排序，并检查了其致敏性和毒性。然后使用各种接头将八个入围表位（三个MHC-1类、三个MHC-2类和两个B细胞表位）组合起来构建疫苗候选物。分子对接和分子模拟显示，该疫苗候选物与免疫受体复合物即Toll样受体（TLR2-TLR6）之间存在稳定的相互作用。进行密码子优化，然后将设计的多表位疫苗构建体克隆到pET30b(+)表达载体中。本研究中对多表位疫苗候选物的免疫信息学分析有可能显著加速疫苗开发的初始阶段。对潜在的多表位疫苗候选物进行实验验证对于确认其在实际条件下的有效性和安全性仍然至关重要。
