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一种基于已知疫苗候选物的计算机模拟表位筛选的多表位理论融合构建体,用于预防广泛的肠杆菌病原体感染。

A multiepitopic theoretical fusion construct based on in-silico epitope screening of known vaccine candidates for protection against wide range of enterobacterial pathogens.

机构信息

Department of Microbiology, Panjab University, Chandigarh, India.

Department of Microbiology, Panjab University, Chandigarh, India.

出版信息

Hum Immunol. 2019 Jul;80(7):493-502. doi: 10.1016/j.humimm.2019.02.008. Epub 2019 Feb 12.

Abstract

Enterobacterial pathogens that have acquired antibiotic resistance genes are a leading cause of community and hospital acquired infections. In such a situation vaccination is considered as a better option to prevent such infections. In the current study reverse vaccinology approach has been used to select peptides from already known immunogenic proteins to design a chimeric construct. We selected Yersiniabactin receptor of Escherichia coli UMN026 and Flagellin of Stenotrophomonas maltophila. B-cell linear epitopes were predicted using Bepipred prediction tool. Peptide binding with reference sets of 27 alleles of MHC class I and class II was also analyzed. The predicted peptides-MHC complexes were further validated using simulation dynamics. The in-silico construction of chimera was done by restriction mapping and codon optimization. Chimera was evaluated using the immunoinformatic approach as done for the selected proteins. From the 673 amino acids of FyuA protein, a region from 1 to 492 was selected for containing more linear epitopes and the processing scores obtained were significant for MHC class I and class II binding. Similarly, from Flagellin, a region between 60 and 328 amino acids was selected and the peptides present in the selected region showed lower percentile ranks for binding with MHC molecules. The simulation studies validated the predictions of peptide-MHC complexes. The selected gene fragments accommodating maximum part of these peptides were used to design a chimaeric construct of 2454 bp. From the immunoinformatic analysis, the chimera was found to be more immunogenic in terms of increased number of B-cell and T-cell epitopes along with increased coverage of global populations with allelic variability.

摘要

已经获得抗生素耐药基因的肠杆菌病原体是社区和医院获得性感染的主要原因。在这种情况下,接种疫苗被认为是预防此类感染的更好选择。在当前的研究中,反向疫苗学方法已被用于从已知免疫原性蛋白中选择肽来设计嵌合构建体。我们选择了大肠杆菌 UMN026 的耶尔森氏菌外毒素受体和嗜麦芽寡养单胞菌的鞭毛蛋白。使用 Bepipred 预测工具预测 B 细胞线性表位。还分析了肽与 MHC 类 I 和 II 参考集合的结合。使用模拟动力学进一步验证了预测的肽-MHC 复合物。通过限制图谱和密码子优化进行嵌合体的计算机构建。使用针对所选蛋白质进行的免疫信息学方法评估嵌合体。从 FyuA 蛋白的 673 个氨基酸中,选择 1 到 492 个氨基酸的区域,因为它包含更多的线性表位,并且获得的加工分数对于 MHC 类 I 和 II 结合是显著的。同样,从鞭毛蛋白中,选择 60 到 328 个氨基酸的区域,所选区域中存在的肽与 MHC 分子的结合显示出较低的百分比等级。模拟研究验证了肽-MHC 复合物的预测。使用容纳这些肽最大部分的选定基因片段设计了一个 2454bp 的嵌合构建体。从免疫信息学分析来看,该嵌合体在 B 细胞和 T 细胞表位数量增加以及具有等位基因变异性的全球人群覆盖率增加方面具有更高的免疫原性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09e8/7115567/b8bbc0604c80/gr1_lrg.jpg

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