鲍曼不动杆菌多重耐药菌株中与生物膜形成相关的ompA基因的分子表征和基于表位的疫苗预测。

In Silico Pharmacology Pub Date : 2021-01-24 eCollection Date: 2021-01-01 DOI:10.1007/s40203-020-00074-7
Deepthi Sogasu, A S Smiline Girija, Shoba Gunasekaran, J Vijayashree Priyadharsini
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引用次数: 9

摘要

本研究旨在通过免疫信息学方法对鲍曼不动杆菌耐药菌株生物膜相关ompA基因进行分子表征,并预测其免疫显性疫苗表位。用PCR从基因组DNA中扩增出ompA并测序。使用ORF,检索ompA蛋白序列,并进行IEDB T细胞和B细胞表位分析以选择表位肽。选用合适的服务器和工具评估所选肽的抗原性、溶解度、理化性质、毒性和i类免疫原性倾向。对HLA等位基因进行MHC I类和II类限制。48% (n = 24)的菌株携带ompA基因。通过选择E1- FDGVNRGTRGTSEEGTLGNA和e2 - klseypnataright dntgprkl两个表位成功地检索了蛋白结构。最终与TLR-2对接,结果表明E2为最佳候选表位,氢键数最多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Molecular characterization and epitope-based vaccine predictions for <i>ompA</i> gene associated with biofilm formation in multidrug-resistant strains of <i>A.baumannii</i>.

Molecular characterization and epitope-based vaccine predictions for <i>ompA</i> gene associated with biofilm formation in multidrug-resistant strains of <i>A.baumannii</i>.

Molecular characterization and epitope-based vaccine predictions for <i>ompA</i> gene associated with biofilm formation in multidrug-resistant strains of <i>A.baumannii</i>.

Molecular characterization and epitope-based vaccine predictions for ompA gene associated with biofilm formation in multidrug-resistant strains of A.baumannii.

The present study was conducted to molecularly characterize the biofilm associated ompA gene from the drug resistant strains of A. baumannii and its immuno-dominant vaccine epitope predictions through immuno-informatic approach. ompA was amplified by PCR from the genomic DNA and was sequenced. Using the ORF, ompA protein sequence was retrieved and was subjected for IEDB T cell and B cell epitope analysis for the selection of the epitope peptides. Selected peptides were evaluated using appropriate servers and tools to assess the propensity for its antigenicity, solubility, physico-chemical property, toxigenicity and class-I immunogenicity. MHC class I and II restriction of HLA alleles was also performed. 48% (n = 24) of the strains possessed ompA gene. Protein structure was successfully retrieved with the selection of two epitopes viz., E1- FDGVNRGTRGTSEEGTLGNA and E2-KLSEYPNATARIEGHTDNTGPRKL. Final docking with TLR-2, showed E2 as the best epitope candidate predicted with the highest number of hydrogen bonds.

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