In silico prediction of epitopes for Chikungunya viral strains
Tóm tắt
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.
Tài liệu tham khảo
AbuBakar S, Sam IC, Wong PF, MatRahim N, Hooi PS, Roslan N (2007) Reemergence of endemic chikungunya, Malaysia. Emerg Infect Dis 13:147–149
Cerdeño-Tárraga AM, Efstratiou A, Dover LG et al (2003) The complete genome sequence and analysis of Corynebacterium diphtheriae NCTC13129. Nucleic Acids Res 31(22):6516–6523
Chhabra M, Mittal V, Bhattacharya D, Rana U, Lal S (2008) Chikungunya fever: a re-emerging viral infection. Indian J Med Microbiol 26(1):5–12
Cruse Julius M, Lewis Robert E (1998) Atlas of immunology. CRC Press, Boca Raton
Dannenberg AM (2010) Perspectives on clinical and preclinical testing of new tuberculosis vaccines. Clin Microbiol 23:781–794
Dimitrov I, Panayot G, Darren RF, Irini D (2010) EpiTOP—a proteochemometric tool for MHC class II binding prediction. Bioinformatics 26(16):2066–2068
Doytchinova IA, Flower DR (2007) VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform 8:4
Germain RN (1994) MHC-dependent antigen processing and peptide presentation: providing ligands for T lymphocyte activation. Cell 76(2):287–299
Grammatikos Alexandros P, Mantadakis Elpis, Falagas Matthew E (2009) Meta-analyses on pediatric infections and vaccines. Infect Dis Clin North Am 23(2):431–457
Groot De, Bosma AS, Chinai N (2001) From genome to vaccine: In silico predictions, ex vivo verification. Vaccine 19:4385–4395
Hussain KM, Chu JJH (2011) Insights into the interplay between chikungunya virus and its human host. Future Virol 6(10):1211–1223
Kaur H, Garg A, Raghava GPS (2007) PEPstr: a de novo method for tertiary structure prediction of small bioactive peptides. Protein Pept Lett 14:626–630
Kringelum JV, Nielsen M, Padkjaer SB, Lund O (2013) Structural analysis of B-cell epitopes in antibody: protein complexes. Mol Immunol 53:24–34
Krogh A, Larsson B, Von Heijne G, Sonnhammer ELL (2001) Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol 305(3):567–580
Larsen MV, Lundegaard C, Lamberth K et al (2005) An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions. Eur J Immunol 35(8):2295–2303
Larsen MV, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M (2007) NetCTL-1.2: large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinform 8:424
Menaka R, Bertil S, Lin F, Vladimir B (2007) Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms. BMC Bioinform 8:459
Mulyanto C, Saleh R (2011) Prediction of a neutralizing epitope of a H5N1 virus hemagglutinin complexed with an antibody variable fragment using molecular dynamics simulation. J Biophys Chem 2:258–267
Pallavi S, Seth PK (2009) Prediction of T cell epitopes for the utility of vaccine development from structural proteins of dengue virus variants using in silico methods. Indian J Biotechnol 8:193–198
Peter B, Sette A (2005) Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinform 31(6):132
Pialoux G, Gaüzère B, Jauréguiberry S, Strobel M (2007) Chikungunya, an epidemic arbovirus. Lancet Infect Dis 7:319–327
Pratheek BM, Suryawanshi AR, Chattopadhyay S, Chattopadhyay S (2015) In silico analysis of MHC-I restricted epitopes of Chikungunya virus proteins: Implication in understanding anti-CHIKV CD8+ T cell response and advancement of epitope based immunotherapy for CHIKV infection. Infect Genet Evol 31:118–126
Sadnam S, Rehman I, Mahbud HAKM, Nurun NAHM (2014) Prediction of Epitope-based peptides for the utility of vaccine development from fusion and glycoprotein of Nipah virus using in silico approach. Adv Bioinform 2014:1–17
Saha S, Raghava GPS (2006) Prediction of continuous B‐cell epitopes in an antigen using recurrent neural network. Proteins 65(1):40–48
Sahu A, Das B, Das M, Patra A, Biswal S, Kar SK, Hazra RK (2013) Genetic characterization of E2 region of Chikungunya virus circulating in Odisha, Eastern India from 2010 to 2011. Infect Genet Evol 18:113–124
Schlesinger S, Schlesinger MJ (2001) Togaviridae: the viruses and their replication. Fields Virol 1:895–916
Sourisseau M, Schilte C, Casartelli N, Trouillet C, Guivel-Benhassine F, Rudnicka D (2007) Characterization of re-emerging chikungunya virus. PLoS Pathog 3(6):e89
Sreekumar E, Issac A, Nair S, Hariharan R, Janki MB, Arathy DS, Regu R, Mathew T, Anoop M, Niyas KP, Pillai MR (2010) Genetic characterization of 2006-2008 isolates of Chikungunya virus from Kerala, South India, by whole genome sequence analysis. Virus Genes 40:14–27
Subramanian N, Chinnappan S (2013) Prediction of promiscuous epitopes in the e6 protein of three risk human papilloma viruses: a computational approach. Asian Pac J Cancer Prev 14(7):4167–4175
Susannah L (2014) The painful, mosquito borne chikungunya virus has reached the US. http://www.vox.com/2014/7/19/5916249/chikungunya-fever-virus-caribbean-florida-disease-symptoms-explained
Tomar N, De RK (2010) Immunoinformatics: an integrated scenario. Immunology 131:153–168
Watts C (1997) Capture and processing of exogenous antigens for presentation on MHC molecules. Annu Rev Immunol 15:821–850
WHO (2014) Chikungunya—Fact sheet. European Centre for Disease Prevention and Control (ECDC)
Xing JW (2013) sequence analysis and b cell epitope prediction of duck hepatitis a virus 1 vp1 gene. Adv Mater Res 647:217
Yao B, Zhang L, Liang S, Zhang C (2012) SVMTriP: a method to predict antigenic epitopes using support vector machine to integrate tri-peptide similarity and propensity. PLoS One 7(9):e45152
Yao L, Meng G, Xian-Ming P (2014) EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression. BMC Bioinform 15:414
Yasser EM, Vasant H (2010) Recent advances in B-cell epitope prediction methods. Immunome Res 6(Suppl2):S2