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Epitope Identification in BEFV Gene for Detecting Effective Points
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Shima Molazadeh1  , Hadi Keivanfar 2, Mehran Bakhshesh3 , Gholamreza Nikbakht Brujeni4 |
1- Department of Pathobiology, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Department of Pathobiology, Science and Research Branch, Islamic Azad University, Tehran, Iran , hadi.99keivanfar@gmail.com
3- Department of Animal Virology, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Organization (AREEO), Karaj, Iran
4- Department of Microbiology and Immunology, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran |
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Abstract: (465 Views) |
Background & Objective: The most common cause of milk production loss in cattle and water buffalo is bovine ephemeral fever (BEF). Previous cases have been reported in Iran's south regions, with a low mortality rate. As a result, studying BEFV and identifying ideal epitopes for further developing diagnostic paths is important.
Materials & Methods: To investigate BEFV N protein epitopes, we collected samples, extracted and sequenced DNA, and then used the ExPaSy translate method to deduce the amino acid sequence. Various immunoinformatics techniques were used to analyze physical/chemical properties, secondary structure of protein sequences, membrane topology, antigenic property, and 3D structure. BCPRED and the DiscoTope server, respectively, predicted linear and discontinuous epitopes of BEFV N protein. Finally, the PatchDock server was used to dock peptides and antibodies.
Result: Three linear epitopes and sixteen discontinuous epitopic positions were discovered. Furthermore, molecular docking between epitopes and low-binding-energy antibodies revealed that they have easy access to the immune system.
Conclusion: In this study, bioinformatics techniques were used to predict epitopes of the BEFV N protein for further developing BEFV diagnostic paths. Furthermore, experimental validation is needed for these epitopes.
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| Keywords: Epitopes, Immunoinformatics, Docking |
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Full-Text [PDF 503 kb]
(114 Downloads)
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Type of Study: Research |
Subject:
Immunology
Received: 2021/06/17 | Accepted: 2021/11/17 | Published: 2022/04/13
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