Jain Amisha, Tripathi Pranav, Shrotriya Aniket, Chaudhary Ritu, Singh Ajeet
Department of Biotechnology, G B Pant Engineering College, Pauri Garhwal, Uttarakhand, India.
Department of Biotechnology, Delhi Technological University, Delhi, India.
3 Biotech. 2015 Aug;5(4):497-503. doi: 10.1007/s13205-014-0247-4. Epub 2014 Aug 26.
The sandfly fever Toscana virus is an important etiological agent known to cause human neurological infections in endemic Mediterranean countries during summer season. In the present study, prediction and modeling of T cell epitopes of Toscana virus (TOSV) antigenic proteins followed by the binding simulation studies of predicted highest binding scorers with their corresponding MHC class II alleles were done. Immunoinformatics was applied in computational vaccinology to analyze the viral proteins which generate possible outcomes to elicit vaccine for TOSV. Here, immunoinformatic tool ProPred was used to predict the promiscuous MHC class II epitopes of viral antigenic proteins. The molecular modeling of the selected epitopes as well as MHC alleles was done at CPH model 3.2 server. Molecular dynamics (MD) simulation studies were performed through the NAMD graphical user interface embedded in visual molecular dynamics. The epitope/peptide VKMMIVLNL of viral nucleoprotein as well as VMILGLLSS of viral glycoprotein has shown the highest binding score with the same DRB1*1104 MHC II allele. These two predicted peptides are highly potential to induce T cell-mediated immune response and are expected to be useful in designing epitope-based vaccines after further testing. The results signify that the nucleoprotein, glycoprotein or the combination of both could be useful for future development of a vaccine controlling the spread of this emerging virus that could pose a new threat for humans.
托斯卡纳白蛉热病毒是一种重要的病原体，已知在夏季流行的地中海国家会引发人类神经感染。在本研究中，对托斯卡纳病毒（TOSV）抗原蛋白的T细胞表位进行了预测和建模，随后对预测出的具有最高结合得分的表位与其相应的II类主要组织相容性复合体（MHC）等位基因进行了结合模拟研究。免疫信息学应用于计算疫苗学，以分析病毒蛋白，从而得出可能引发针对TOSV疫苗的结果。在此，使用免疫信息学工具ProPred预测病毒抗原蛋白的混杂性II类MHC表位。在CPH模型3.2服务器上对所选表位以及MHC等位基因进行了分子建模。通过嵌入可视化分子动力学中的NAMD图形用户界面进行分子动力学（MD）模拟研究。病毒核蛋白的表位/肽VKMMIVLNL以及病毒糖蛋白的VMILGLLSS与相同的DRB1*1104 MHC II等位基因显示出最高的结合得分。这两种预测的肽极有可能诱导T细胞介导的免疫反应，预计在经过进一步测试后可用于设计基于表位的疫苗。结果表明，核蛋白、糖蛋白或两者的组合可能有助于未来开发一种控制这种新兴病毒传播的疫苗，该病毒可能对人类构成新的威胁。
