空肠弯曲菌细胞致死性膨胀毒素（CDT）蛋白的CTL表位预测、计算机模拟及功能分析
Prediction of CTL epitope, in silico modeling and functional analysis of cytolethal distending toxin (CDT) protein of Campylobacter jejuni.
作者信息
Ingale Arun G, Goto Susumu
机构信息
Department of Biotechnology, School of Life Sciences, North Maharashtra University, Jalgaon 425001, India.
出版信息
BMC Res Notes. 2014 Feb 19;7:92. doi: 10.1186/1756-0500-7-92.
BACKGROUND
Campylobacter jejuni is a potent bacterial pathogen culpable for diarrheal disease called campylobacteriosis. It is realized as a major health issue attributable to unavailability of appropriate vaccines and clinical treatment options. As other pathogens, C. jejuni entails host cellular components of an infected individual to disseminate this disease. These host-pathogen interfaces during C. jejuni infection are complex, vibrant and involved in the nicking of host cell environment, enzymes and pathways. Existing therapies are trusted only on a much smaller number of drugs, most of them are insufficient because of their severe host toxicity or drug-resistance phenomena. To find out remedial alternatives, the identification of new biotargets is highly anticipated. Understanding the molecules involved in pathogenesis has the potential to yield new and exciting strategies for therapeutic intervention. In this direction, advances in bioinformatics have opened up new possibilities for the rapid measurement of global changes during infection and this could be exploited to understand the molecular interactions involved in campylobacteriosis.
METHODS
In this study, homology modeling, epitope prediction and identification of ligand binding sites has been explored. Further attempt to generate strapping 3D model of cytolethal distending toxin protein from C. jejuni have been described for the first time.
RESULTS
CDT protein isolated from C. jejuni was analyzed using various bioinformatics and immuno-informatics tools including sequence and structure tools. A total of fifty five antigenic determinants were predicted and prediction results of CTL epitopes revealed that five MHC ligand are found in CDT. The three potential pocket binding site are found in the sequence that can be useful for drug designing.
CONCLUSIONS
This model, we hope, will be of help in designing and predicting novel CDT inhibitors and vaccine candidates.
背景
空肠弯曲菌是一种导致弯曲菌病腹泻疾病的强效细菌病原体。由于缺乏合适的疫苗和临床治疗选择，它被认为是一个主要的健康问题。与其他病原体一样，空肠弯曲菌需要感染个体的宿主细胞成分来传播这种疾病。空肠弯曲菌感染期间的这些宿主 - 病原体界面是复杂、活跃的，并且涉及宿主细胞环境、酶和途径的破坏。现有的治疗方法仅依赖于少数几种药物，其中大多数由于其严重的宿主毒性或耐药现象而不足。为了找到补救替代方案，人们高度期待识别新的生物靶点。了解发病机制中涉及的分子有可能产生新的、令人兴奋的治疗干预策略。在这个方向上，生物信息学的进展为快速测量感染期间的全局变化开辟了新的可能性，这可以被利用来理解弯曲菌病中涉及的分子相互作用。
方法
在本研究中，探索了同源建模、表位预测和配体结合位点的识别。首次描述了进一步尝试生成空肠弯曲菌细胞致死扩张毒素蛋白的可靠三维模型。
结果
使用包括序列和结构工具在内的各种生物信息学和免疫信息学工具对从空肠弯曲菌中分离的CDT蛋白进行了分析。总共预测了55个抗原决定簇，CTL表位的预测结果显示在CDT中发现了5个MHC配体。在该序列中发现了三个潜在的口袋结合位点，可用于药物设计。
结论
我们希望这个模型将有助于设计和预测新型CDT抑制剂和候选疫苗。
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