Shigellosis is a diarrheal disease that causes high mortality every year, especially in children, elderly and immunocompromised patients. Recently, resistance strains to antibiotic therapy are in the rise and the World Health Organization prioritizes the development of a safe vaccine against the most common causal agent of shigellosis, Shigella flexneri. This pathogen uses autotransporter proteins such as SigA, Pic and Sap to increase virulence and some of them have been described as highly immunogenic proteins. In this study, we used immune-informatics analysis to identify the most antigenic epitope as a vaccine candidate on three passenger domains of auto-transporter proteins encoded on the pathogenic island SHI-1, to induce immunity against S. flexneri. Epitope identification was done using various servers such as Bepipred, Bcepred, nHLAPRED, NetMHCII, Rankpep and IEDB and the final selection was done based on its antigenicity using the VaxiJen server. Moreover, to enhance immunity, the GroEL adjuvant was added to the final construct as a Toll-like receptor 2 (TLR2) agonist. On the other hand, to predict the tertiary structure, the I-TASSER server was used, and the best model was structurally validated using the ProSA-web software and the Ramachandran plot. Subsequently, the model was refined and used for docking and molecular dynamics analyses with TLR2, which demonstrated an appropriate and stable interaction. In summary, a potential subunit vaccine candidate, that contains B and T cell epitopes with proper physicochemical properties was designed. This multiepitope vaccine is expected to elicit robust humoral and cellular immune responses and vest protective immunity against S. flexneri.

中文翻译：

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基于自动转运蛋白和HSP的抗志贺菌病致病因子弗氏志贺氏菌疫苗的计算机设计。

志贺氏菌病是一种腹泻病，每年都会导致高死亡率，尤其是在儿童，老年人和免疫功能低下的患者中。最近，对抗生素治疗的耐药性菌株正在增加，世界卫生组织优先开发针对志贺氏菌病最常见病原体志贺氏菌的安全疫苗。该病原体使用自转运蛋白（例如SigA，Pic和Sap）来增加毒力，其中一些被描述为高度免疫原性蛋白。在这项研究中，我们使用免疫信息学分析来确定最具抗原性的抗原决定簇，作为在病原岛SHI-1上编码的自转运蛋白的三个乘客域上的候选疫苗，以诱导针对弗氏链球菌的免疫力。使用多种服务器（例如Bepipred，Bcepred，nHLAPRED，NetMHCII，Rannkepp和IEDB，并使用VaxiJen服务器根据其抗原性进行最终选择。此外，为了增强免疫力，将GroEL佐剂作为Toll样受体2（TLR2）激动剂添加到最终构建物中。另一方面，为了预测三级结构，使用了I-TASSER服务器，并且使用ProSA-web软件和Ramachandran图对最佳模型进行了结构验证。随后，对该模型进行了改进，并用于与TLR2的对接和分子动力学分析，证明了适当且稳定的相互作用。总之，设计了潜在的亚单位疫苗候选物，其中包含具有适当理化特性的B和T细胞表位。该多表位疫苗有望引发强大的体液和细胞免疫反应，并赋予针对S的保护性免疫。