METHODS: Protein sequences were obtained from the UniProt database, and evaluated through VaxiJen v2.0 to predict the B and T-cell epitopes within the RVFV glycoprotein. Gn/Gc protein sequences were analyzed with bioinformatics tools and algorithms. The predicted T-cell and B-cell epitopes were evaluated for antigenicity, allergenicity, and toxicity by the VaxiJen v2.0 system, AllerTop v2.0, and ToxinPred server, respectively.
RESULTS: We employed computational methods to screen the RVFV envelopment polyprotein encompassing N-terminal and C-terminal glycoprotein segments, to discover antigenic T- and B-cell epitopes. Our analysis unveiled multiple potential epitopes within the RVFV glycoprotein, specifically within the Gn/Gc protein sequences. Subsequently, we selected eleven cytotoxic T-lymphocytes (CTL) and four helper T-lymphocytes (HTL) for population coverage analysis, which collectively extended to cover 97.04% of the world\'s population, representing diverse ethnicities and regions. Notably, the CTL epitope VQADLTLMF exhibited binding affinity to numerous human leukocyte antigen (HLA) alleles. The identification of glycoprotein (Gn/Gc) epitopes through this immunoinformatic study bears significant implications for advancing the development of an effective RVFV vaccine.
CONCLUSIONS: These findings provide valuable insights into the immunological aspects of the disease and may contribute towards the development of broad-spectrum antiviral therapies targeting other RNA viruses with similar polymerase enzymes.
方法:从UniProt数据库获得蛋白质序列,并通过VaxiJenv2.0进行评估,以预测RVFV糖蛋白内的B和T细胞表位。使用生物信息学工具和算法分析Gn/Gc蛋白序列。评估预测的T细胞和B细胞表位的抗原性,变应原性,和VaxiJenv2.0系统的毒性,AllerTopv2.0和ToxinPred服务器,分别。
结果:我们采用计算方法来筛选包含N端和C端糖蛋白片段的RVFV包膜多蛋白,发现抗原T细胞和B细胞表位。我们的分析揭示了RVFV糖蛋白中的多个潜在表位,特别是在Gn/Gc蛋白序列内。随后,我们选择了11个细胞毒性T淋巴细胞(CTL)和4个辅助T淋巴细胞(HTL)进行群体覆盖率分析,总共覆盖了世界上97.04%的人口,代表不同的种族和地区。值得注意的是,CTL表位VQADLTLMF表现出对许多人白细胞抗原(HLA)等位基因的结合亲和力。通过该免疫信息学研究鉴定糖蛋白(Gn/Gc)表位对于推进有效的RVFV疫苗的开发具有重要意义。
结论:这些发现为该疾病的免疫学方面提供了有价值的见解,并可能有助于开发针对具有相似聚合酶的其他RNA病毒的广谱抗病毒疗法。