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ORIGINAL ARTICLE
Year : 2022  |  Volume : 15  |  Issue : 1  |  Page : 35-43

An immunoglobulin Y that specifically binds to an in silico-predicted unique epitope of Zika virus non-structural 1 antigen


1 Department of Biochemistry and Molecular Biology, College of Medicine, University of the Philippines, Manila; Department of Biochemistry, Faculty of Pharmacy; Research Center for Natural and Applied Sciences, University of Santo Tomas, Philippines
2 Department of Biochemistry and Molecular Biology, College of Medicine, University of the Philippines, Manila, Philippines
3 Department of Biochemistry, Faculty of Pharmacy, University of Santo Tomas, Philippines

Correspondence Address:
Leonardo A Guevarra
Department of Biochemistry and Molecular Biology, College of Medicine, University of the Philippines, Manila; Department of Biochemistry, Faculty of Pharmacy; Research Center for Natural and Applied Sciences, University of Santo Tomas
Philippines
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1995-7645.335701

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Objective: To identify unique immunogenic epitopes of Zika virus non-structural 1 (NS1) antigen and produce immunoglobulin Y (IgY) for potential use in he diagnosis of of Zika virus infection. Methods: Immunogenic epitopes were identified using in silico B-cell epitope prediction. A synthetic peptide analog of the predicted epitope was used to induce antipeptide IgY production in hens which was purified using affinity chromatography. Presence of purified IgY and its binding specificity were performed by gel electrophoresis and ELISA, respectively. Results: Out of the nine continuous epitopes identified, the sequence at position 193-208 (LKVREDYSLECDPAVI) was selected and used to produce anti-peptide IgY. The produced IgY was found to bind to the synthetic analog of the Zika virus NS1 immunogenic epitope but not to other flaviviruses and random peptides from other pathogens. Conclusions: In this study, we identified an immunogenic epitope unique to Zika virus that can be used to develop a serodiagnostic tool that specifically detect Zika virus infection.


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