Prediction of Epitope Based Vaccine Candidates against Macaca fascicularis PV Type 2 Virus Using In-silico Approaches | ||||
| Egyptian Academic Journal of Biological Sciences. C, Physiology and Molecular Biology | ||||
| Article 5, Volume 10, Issue 1, June 2018, Page 49-57 PDF (278.3 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/eajbsc.2018.13655 | ||||
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| Author | ||||
| Mohammed Yahya Areeshi | ||||
| Research and Scientific Studies Unit, College of Nursing, Jazan University, Jazan - 45142, Saudi Arabia | ||||
| Abstract | ||||
| Papillomaviruses are the causing agents of benign tumors in their hosts, i.e., mammals and birds, across the world. They have circular double stranded DNA genome. In order to combat the viral infection in Macaca fascicularis PV type 2, a computational pipeline was employed in this study for the prediction of viral protein targeting peptides for vaccine discovery. Epitope prediction enabled the identification of multi-peptides suitable for vaccine development. Further in-depth analysis for immunogenicity and toxicity prediction scrutinized the optimal candidate for target based designing of vaccines. Immunogenic and physicochemical properties of proteins E1, E2, E4, E6, E7, L1, and L2 of Macaca fascicularis PV type 2 revealed their instability index, molecular weight, and antigenic potential. The predicted epitopes may lead to promising targets for broad spectrum vaccine designing against the viral strain of Macaca fascicularis PV type 2. | ||||
| Keywords | ||||
| Papillomavirus; epitope; antigenicity prediction; physicochemical characterization; population coverage analysis | ||||
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