Dar Hamza, Zaheer Tahreem, Rehman Muhammad Talha, Ali Amjad, Javed Aneela, Khan Gohar Ayub, Babar Mustafeez Mujtaba, Waheed Yasir
Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology, Islamabad 44000, Pakistan.
Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology, Islamabad 44000, Pakistan.
Asian Pac J Trop Med. 2016 Sep;9(9):844-850. doi: 10.1016/j.apjtm.2016.07.004. Epub 2016 Jul 26.
To predict immunogenic promiscuous T cell epitopes from the polyprotein of the Zika virus using a range of bioinformatics tools. To date, no epitope data are available for the Zika virus in the IEDB database.
We retrieved nearly 54 full length polyprotein sequences of the Zika virus from the NCBI database belonging to different outbreaks. A consensus sequence was then used to predict the promiscuous T cell epitopes that bind MHC 1 and MHC II alleles using PorPred1 and ProPred immunoinformatic algorithms respectively. The antigenicity predicted score was also calculated for each predicted epitope using the VaxiJen 2.0 tool.
By using ProPred1, 23 antigenic epitopes for HLA class I and 48 antigenic epitopes for HLA class II were predicted from the consensus polyprotein sequence of Zika virus. The greatest number of MHC class I binding epitopes were projected within the NS5 (21%), followed by Envelope (17%). For MHC class II, greatest number of predicted epitopes were in NS5 (19%) followed by the Envelope, NS1 and NS2 (17% each). A variety of epitopes with good binding affinity, promiscuity and antigenicity were predicted for both the HLA classes.
The predicted conserved promiscuous T-cell epitopes examined in this study were reported for the first time and will contribute to the imminent design of Zika virus vaccine candidates, which will be able to induce a broad range of immune responses in a heterogeneous HLA population. However, our results can be verified and employed in future efficacious vaccine formulations only after successful experimental studies.
使用一系列生物信息学工具从寨卡病毒的多聚蛋白中预测具有免疫原性的多反应性T细胞表位。到目前为止,国际免疫信息学数据库(IEDB)中尚无寨卡病毒的表位数据。
我们从NCBI数据库中检索了近54条属于不同疫情爆发的寨卡病毒全长多聚蛋白序列。然后使用一个共有序列,分别通过PorPred1和ProPred免疫信息学算法预测与MHC Ⅰ类和MHC Ⅱ类等位基因结合的多反应性T细胞表位。还使用VaxiJen 2.0工具为每个预测的表位计算抗原性预测分数。
通过使用ProPred1,从寨卡病毒的共有多聚蛋白序列中预测出23个HLA Ⅰ类抗原表位和48个HLA Ⅱ类抗原表位。预测出的MHC Ⅰ类结合表位数量最多的区域在NS5内(21%),其次是包膜蛋白(17%)。对于MHC Ⅱ类,预测表位数量最多的是NS5(19%),其次是包膜蛋白、NS1和NS2(各占17%)。针对这两类HLA都预测出了多种具有良好结合亲和力、多反应性和抗原性的表位。
本研究中检测到的预测保守多反应性T细胞表位首次被报道,将有助于寨卡病毒候选疫苗的紧急设计,该疫苗将能够在异质性HLA人群中诱导广泛的免疫反应。然而,只有在成功的实验研究之后,我们的结果才能得到验证并应用于未来有效的疫苗配方中。