In silico prediction of epitopes for Chikungunya viral strains

• Published in: Journal of pharmaceutical investigation 2015, 45(6), , pp.579-591
• Main Authors: Kori, Priyanka, Sajjan, Shrishailnath S., Madagi, Shivakumar B.
• Format: Article
• Language: English
• Subjects: Biomedical and Life Sciences; Biomedicine; Research Article; 약학
• ISSN: 2093-5552; 2093-6214
• DOI: 10.1007/s40005-015-0205-0

Chikungunya is a viral infection transmitted by Aedes mosquitoes in humans. Currently there is no drug available for the treatment of this infection. In absence of a proven therapeutic, vaccines provide an alternative preventive measure for the spread of viral infection in risk prone population. The identification of epitopes is an important step in designing vaccines for viral infections. Traditional methods for vaccine production can be augmented by incorporation of in silico methods at epitopes identification stage. Protein sequences were retrieved for three different viral strains from primary database. Multiple sequence alignment for the retrieved sequences was performed by using MEGA 6.06 to spot the conserved regions. Various immunological databases were utilized to determine the binding affinity with T cells and B cells from structural and non-structural proteins from three different isolates of Chikungunya virus. Five different epitopes were predicted for both structural and non-structural proteins. The epitopes “KKKPGRRERMCMKIE” and “DAEKEAEEEREAELT” and “AEEEREAEL” were predicted as core sequences for class I and class II MHC molecules whereas “SSKYDLECAQ” and “QVLKAKNIGL” were predicted as probable B cell epitopes for structural and non-structural proteins respectively. The identified epitopes can be used for developing a broad spectrum vaccines having effectiveness against different strains of Chikungunya.