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Payandeh Z, Khalesi B, Mard-Soltani M, Sefid F. OprF and OprL Conjugate as Vaccine Candidates against Pseudomonas aeruginosa; an in Silico Study. JoMMID 2018; 6 (1) :1-7
URL: http://jommid.pasteur.ac.ir/article-1-142-en.html
Department of Biology, Shahed University, Tehran, Iran
Abstract:   (5431 Views)
Introduction: Vaccine studies against Pseudomonas aeruginosa have often focused on outer membrane proteins (OPRs) due to their potent stimulation of the immune response. Using major outer membrane proteins of cell walls (mOMPs) of P. aeruginosa and other Gram-negative bacteria actively stimulate the immune system without any toxic side effects. Moreover, these antigens show immunological cross-reactivity with mOMPs of other serotypes belonging to the same species. The main OPRs of P. aeruginosa, OprF, and OprL, have received much attention from biologists as the potential OPR-based vaccine candidates. Methods: Homology modeling of OprF and OprL was done based on the template structures obtained from the BLAST search. The quality of OprF and OprL molecules was assessed using GMQE and QMEAN4 quality assessment tools. The secondary structure of the proteins was predicted as well as the structural topology, subcellular localization, functional analyses, signal peptide and B cell epitopes of proteins. Results: The structures of OprF and OprL proteins were successfully modeled and assessed using 4RLC-A and 4G4V-A as template structures. The regions of the proteins with a high B cell epitope density were identified as candidates for vaccine design. These regions contain functional and exposed amino acids. In these regions, the majority of amino acids were hydrophilic, flexible and accessible. Conclusion: It should be noted that in silico approaches are appealing alternatives for empirical methods. These approaches could pave the way for precise vaccine design efforts with lower cost and time.
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Type of Study: Original article | Subject: Microbial pathogenesis
Received: 2017/10/9 | Accepted: 2018/07/30 | Published: 2018/08/27

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.