In silico prediction of B- and T- cell epitope on Lassa virus proteins for peptide based subunit vaccine design

Authors

1 Department of Biotechnology, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India

2 Department of Biotechnology, Faculty of Engineering and Technology, Rama University, Kanpur, Uttar Pradesh, India

Abstract

Background: Lassa fever is a severe, often-fatal and one of the most virulent disease in primates. However, the mechanism of escape of virus from the T-cell mediated immune response of the host cell is not explained in any studies yet. In our studies we had aimed to predict B- and T- cell epitope of Lassa virus protein, for impaling the futuristic approach of developing preventive measures against this disease, further we can also study its presumed viral- host mechanism.
Materials and Methods: Peptide based subunit vaccine was developed from all four protein against Lassa virus. We adopted sequence, 3D structure and fold level in silico analysis to predict B-cell and T-cell epitopes. The 3-D structure was determined for all protein by homology modeling and the modeled structure validated.
Results: One T-cell epitope from Glycoprotein (WDCIMTSYQ) and one from Nucleoprotein (WPYIASRTS) binds to maximum no of MHC class I and MHC class II alleles. They also specially bind to HLA alleles namely, A*0201, A*2705, DRB*0101 and DRB*0401.
Conclusions: Taken together, the results indicate the Glycoprotein and nucleoprotein are most suitable vaccine candidates against Lassa virus.

Keywords

1.
Frame JD, Baldwin JM, Gocke DJ, Troup JM. Lassa fever, a new virus disease of man from West Africa. I. Clinical description and pathological findings. Am J Trop Med Hyg 1970;19:670-6.  Back to cited text no. 1
    
2.
McCormick JB, King IJ, Webb PA, Scribner CL, Craven RB, Johnson KM, et al. Lassa fever: Effective therapy with Ribavirin. New Eng J Med 1986;314:20-6.  Back to cited text no. 2
    
3.
McCormick JB, King IJ, Webb PA, Johnson KM, O'Sullivan R, Smith ES, et al. A case-control study of the clinical diagnosis and course of Lassa fever. J Infect Dis 1987;155:445-55.  Back to cited text no. 3
    
4.
Johnson KM, McCormick JB, Webb PA, Smith ES, Elliot LH, King IJ. Clinical virology of Lassa fever in hospitalized patients. J Infect Dis 1987;155:456-64.  Back to cited text no. 4
    
5.
Carey DE, Kemp GE, White HA, Pinneo L, Addy RF, Fom AL, et al. Lassa fever. Epidemiological aspects of the 1970 epidemic, Jos, Nigeria. Trans R Soc Trop Med Hyg 1972;66:402-8.  Back to cited text no. 5
    
6.
Bowen GS, Tomori O, Wulff H, Casals J, Noonan A, Downs WG. Lassa fever in Onitsha, East Central State, Nigeria in 1974. Bull World Health Organ 1975;52:599-604.  Back to cited text no. 6
    
7.
Monath TP. Lassa fever: A review of the epidemiology and epizootiology. Bull World Health Organ 1975;52:577-92.  Back to cited text no. 7
    
8.
Tim M. Public health leaflets on what your need to know about Lassa fever. Abuja, Nigeria: Federal Ministry of Health; 2000.  Back to cited text no. 8
    
9.
Monath TP, Maher M, Casals J, Kissling RE, Cacciapuoti A. Lassa fever in the Eastern Province of Sierra Leone, 1970–1972. II. Clinical observations and virological studies on selected hospital cases. Am J Trop Med Hyg 1974;23:1140-9.  Back to cited text no. 9
    
10.
Schmitz H, Kohler B, Laue T, Drosten C, Veldkamp PJ, Günther S, et al. Monitoring of clinical and laboratory data in two cases of imported Lassa fever. Microbes Infect 2002;4:43-50.  Back to cited text no. 10
    
11.
Gunther S, Emmerich P, Laue T, Kuhle O, Asper M, Jung A, et al. Imported Lassa fever in Germany: Molecular characterization of a new Lassa virus strain. Emerg Infect Dis 2000;6:466-76.  Back to cited text no. 11
    
12.
Lozano ME, Posik DM, Albarino CG, Schujman G, Ghiringhelli PD, Calderon G, et al. Characterisation of arenaviruses using a family-specific primer set for RT-PCR amplification and RFLP analysis. Its potential use for detection of uncharacterised arenaviruses. Virus Res 1997;49:79-89.  Back to cited text no. 12
    
13.
Keenlyside RA, McCormick JB, Webb PA, Smith E, Elliott L, Johnson KM. Case-control study of Mastomys natalensis and humans in Lassa virus-infected households in Sierra Leone. Am J Trop Med Hyg 1983;32:829-37.  Back to cited text no. 13
    
14.
Kyte J, Doolittle FR. A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982;157:105-32.  Back to cited text no. 14
    
15.
Shehzadi A1, Ur Rehman S, Idrees M. Promiscuous prediction and conservancy analysis of CTL binding epitopes of HCV 3a viral proteome from Punjab Pakistan: An in silico approach. Virol J 2011;8:55.  Back to cited text no. 15
    
16.
EI- Manzalawy Y, Dobbs D, Honavar V. Predicting liniar B-cell epitopes using string Kernels. J Mol Recognit 2008;21:243-55.  Back to cited text no. 16
    
17.
Chen J, Liu H, Yang J, Chou KC. Prediction of liniar B-cell epitopes using amino acid pair antigenicity scale. Amino Acids 2007;33:423-8.  Back to cited text no. 17
    
18.
Singh H, Raghava GP. ProPred1: Prediction of promiscuous MHC Class-I binding sites. Bioinformatics 2003;19:1009-14.  Back to cited text no. 18
    
19.
Saraswat A, Shraddha, Jain A, Pathak A, Verma SK, Kumar A. Immuno-informatic speculation and computational modeling of novel MHC-II human leukocyte antigenic alleles to elicit vaccine for ebola virus. J Vaccin 2012;3:1-3.  Back to cited text no. 19
    
20.
Shekhar K, Dev K, Verma SK, Kumar A. In-silico screening and modeling of CTL binding epitopes of crimean congo hemorrhagic fever virus. Trends Bioinformatics 2011;514-24.  Back to cited text no. 20
    
21.
Verma SK, Yadav SP, Kumar A. In silico T cell antigenic determinants from proteome of H1N2 swine influenza A virus. Online J Bioinformatics 2011;12:371-8.  Back to cited text no. 21
    
22.
Gaun P, Doytchinova IA, Zygouri C Flower DR. MHCPred: A server for quantitative prediction of peptide MHC binding. Nuclic Acids Res 2003;31:362-4.  Back to cited text no. 22
    
23.
Kangueane P, Sakharkar MK. T-Epitope Designer: A HLA-peptide binding prediction server. Bioinformation 2005;1:21.  Back to cited text no. 23
    
24.
Sali A, Potterton L, Yuan F, Van Vlijmen H, Karplus M. Evaluation of comparative protein modeling by MODELLER. Protein Struct Funct Genet 1995;23:318-26.  Back to cited text no. 24
    
25.
Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: A program to check the stereochemical quality of protein structures. J Appl Cryst 1993;26:283-91.  Back to cited text no. 25
    
26.
Wiederstein M, Sippl MJ. ProSA-web: Interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acid Res 2007;35:407-10.  Back to cited text no. 26
    
27.
Mayrose I, Penn O, Erez E, Rubinstein ND, Shlomi T, Freund NT, et al. Pepitope: Epitope Mapping from affinity-selected peptides, Bioinformatics 2007;23:3244.  Back to cited text no. 27
    
28.
Baú D, Martin AJ, Mooney C, Vullo A, Walsh I, Pollastri G. Distill: A suite of web servers for the prediction of one-, two- and three- dimentional structural features of proteins. BMC Bioinformatics 2006;7:402.  Back to cited text no. 28
    
29.
Laskowski RA, Watsons JD, Thornton JM. ProFunc A server for predicting protein function from 3-D structure. Nucleic Acids Res 2005;33:89-93.  Back to cited text no. 29
    
30.
Goodsell DS, Morris GM, Halliday RS, Huey R, Belew RK, Olson AJ. Automated Docking using a Lamarckian Genetic Algorithm and Empirical Binding free energy function. J Comput Chem 1998;19:1639-62.  Back to cited text no. 30