- Open Access
De Novo modeling of Envelope 2 protein of HCV isolated from Pakistani patient and epitopes prediction for vaccine development
© Afzal et al.; licensee BioMed Central Ltd. 2014
- Received: 17 January 2014
- Accepted: 26 March 2014
- Published: 7 May 2014
Hepatitis C virus (HCV) is a universal health issue and a significant risk factor leading to hepatocellular carcinoma. HCV has infected approximately 170 million individuals worldwide. It is a member of Flaviviridae with positive sense RNA genome. In the absence of any effective vaccine against HCV, pegylated interferon with ribavirin is the standard of treatment against HCV infection. In this study, sequence and structural analysis of envelope 2 (E2) protein was performed which was isolated from patients of HCV genotype 3a in Pakistan. Then, epitopes were predicted which were specific for both B-cells and T-cells. Later, conservancy of epitopes was checked with the HCV 3a and 1a sequences from different countries. A total of 6 conserved epitopes were found from extra-membranous regions of E2 protein. Presence of conserved epitopes in E2 protein generates the possibility that these epitopes can be used to elicit the immune response against HCV.
- E2 protein
Hepatitis C virus (HCV) is a universal health issue and a significant risk factor developing hepatocellular carcinoma (HCC). World Health Organization reported that hepatic cancer caused by HCV scored about 300,000 deaths in 2004 only . It has affected approximately 170 million individuals worldwide . In United States, HCV is most common blood-borne infection with over 4 million individuals infected . According to a recent study, an alarming 17 million people in Pakistan are infected with HCV and about 8-10% of individuals are carriers of HCV pathogen . Prevalence analysis of Pakistani population shows that HCV genotype 3a is the most common genotype in all provinces except in Balochistan where HCV genotype 1a is most prevalent .
HCV is a member of Flaviviridae and closely related to Dengue, West Nile and Yellow Fever virus. It has a positive sense single stranded RNA genome of about 9.6 kb size . HCV genome encodes a large polyprotein of 3010 to 3033 amino acid residues [7, 8]. This polyprotein is subsequently cleaved into four structural (Core, E1, E2 and P7) and 6 non structural proteins (NS2, NS3, NS4A, NS4B, NS5A and NS5B) .
However, the structural details of the HCV virus are still elusive , but it is known that infectious viral particles contains lipid envelope and glycoproteins E1 and E2, close to the surface . E2 is highly glycosylated with most of the glycosylation sites well conserved . In addition to these conserved residues, E2 has hypervariable regions which vary up to 80% among HCV of different genotypes and even between the subtypes of same genotype . However, E2 protein interacts with DC-SIGN and L-SIGN (mannose binding proteins) but detailed mechanism of viral entry is unclear. It is suggested that glycosylated motifs of E2 protein interacts with surface receptor enabling the viral entry into the cell . Hence, E2 protein is a potent target to stop viral entry into healthy cells .
Currently, the pegylated interferon (IFN) alpha, separately or in combination with ribavirin, is standard HCV treatment [16–18]. The efficacy of IFN treatment depends on many factors related to viral genotype and patient’s health status. Clinical studies show that in 30-50% of cases HCV remain non-responsive to IFN treatment and there might be a number of serious adverse events associated with treatment . In spite of advancements in drug designing technologies, there is still no vaccine against HCV. Variability across the HCV genotypes is also a significant hindrance in vaccine development.
For the development of potential inhibitors against envelope proteins, it is required to have knowledge of sequence and structure of protein. With the development of computational biology, novel approaches have been developed to get insights from biological data. This study was designed to isolate E2 glycoprotein sequence from HCV genotype 3a infected patient; and to predict and to analyze the epitopes related to B-cells and T-cells. The conservation and variability analysis was included to find spectrum of activity of epitopes in HCV genotype 3a and 1a.
Source of serum samples
HCV genotype 3a samples were collected from patients diagnosed with HCV at Molecular Diagnostics Lab. CEMB, Lahore. The informed consent was taken from the patients and blood sample was taken according to provision of Ethical Committee, Molecular Virology Division, National Centre of Excellence in Molecular Biology, Lahore. The patients were selected on the basis of elevated serum ALT and AST levels at least for six months, histological examination, and detection of serum HCV RNA anti-HCV antibodies (3rd generation ELISA).
RNA isolation from serum, cDNA synthesis and sequencing of HCV E2 gene
Total RNA was isolated from patients’ serum samples using Gentra RNA isolation kit (Puregene, Minneapolis, MN55441 USA) according to the kit protocol. Then, extracted RNA was reverse transcribed to cDNA using MMLV-RTase (Moloney murine leukemia virus reverse transcriptase). By using the E2 specific primers, E2 gene was amplified using cDNA of HCV genotype 3a. For this, PCR protocol involved 35 cycling steps at annealing temperature 54°C. The amplified PCR product was resolved using 1.2% TAE agarose gel and molecular weight was compared with 1 kb DNA ladder. Then, DNA was purified from gel using QIA quick gel extraction kit (Qiagen, USA) using the kit protocol. Purified PCR product was cloned in pCR2.1-TOPO (TA vectors) obtained from Invitrogen, USA. Successful cloning was confirmed by PCR using E2 specific primers and by digestion of construct using EcoR1 at 37°C for 1 hr. Later, a sequencing reaction was performed using BigDye™ Terminator v3.0 sequencing kit (Applied Biosystems, Germany). Both positive and negative strands were sequenced at automated sequencer (Applied Biosystems 3700 DNA Analyzer, Germany). Then, the gene sequence was submitted at NCBI GenBank, having accession no. ADP55199.
Sequence analysis of E2 protein
HCV 3a E2 gene sequence ADP55199 was used for primary structure analysis and for the prediction of secondary as well as three-dimensional structure. The E2 gene sequence was in-silico translated to obtain primary structure (amino acid sequence) of protein. Primary structure parameters of E2 protein which include molecular weight, theoretical pI, atomic composition, extinction coefficient, estimated half-life, aliphatic index and Grand average of hydropathicity (GRAVY) were computed using ProtParam online tool . Secondary structure of the protein was analyzed using Jpred, Psipred and “Sequence Annotated by Structure” (SAS) tool [20–22]. Disulfide connectivity of the protein was checked using DiANNA tool which is a neural network application and predicts cysteine states of a protein . The knowledge of cys-cys linkages is important in understanding the secondary and tertiary structure of protein because it plays significant role in fold stabilization. Glycosylation sites were predicted using NetNGlyc 1.0 server and their conservancy was checked using multiple sequence alignment by MEGA5.0 .
De novo protein modeling and quality assessment
For the prediction of three dimensional structure of E2 protein both homology modeling and de novo modeling approaches were used. For the homology modeling, BlastP was used for searching suitable template in Protein Data Bank (http://www.rcsb.org/pdb/home/home.do). In our search, the appropriate template was not found, so we used iTASSER server for de novo modeling of E2 protein . Using iTASSER, five models were predicted and one best model was chosen for further structural analysis. The selection of model was done using three criteria: C-score, DFIRE2 energy profile  and stereochemical properties using PROCHECK tool . The visual analysis of structure was done on Swiss-PDB-viewer  and Visual Molecular Dynamics (VMD) program .
Epitopes prediction from E2 protein
A systematic approach was employed for the prediction of potential epitopes in E2 protein. Vexijen 1.0 was used to determine overall antigenicity of E2 protein using cut-off value of 0.4 . Then, topology of E2 protein was determined using TMHMM Server v 2.0 . With the help of membrane topology data, E2 protein regions inside the membrane and transmembrane were eradicated from epitopes prediction. BCPRED server was used for the prediction of B-cell epitopes of the length of 12 amino acids . For the prediction of T-cell epitopes ProPred was used with proteasome cleavage site filter of 5% threshold. In this analysis, 47 alleles of MHC-class I and 54 alleles of MHC-class II were included . Once the B-cells and T-cells (MHC-class I and MHC-class II) epitopes were predicted, their antigenicity was checked using Vexijen. The antigenicity score of the predicted epitopes was checked using Vexijen v 1.0 server. Later, only antigenic epitopes were included in conservancy analysis.
The conservancy of epitopes
The E2 protein sequences of HCV genotype 3a and 1a were retrieved from NCBI sequence database. The HCV 3a sequences were from India (AGQ17416), Japan (BAN67274), United Kingdom (ACZ61116) and USA (ABD85062) and HCV 1a sequences were from Pakistan (GU736411), USA (EU482831), United Kingdom (AY958057), France (AF529293) and Japan (AB520610). The conservancy and variability of the predicted antigenic epitopes was determined by “IEDB conservancy analysis tool”  in E2 protein sequences retrieved from different regions of world. Then, all highly conserved epitopes were checked for their localization in predicted protein structure.
cDNA synthesis and cloning of E2 protein
Sequence analysis of E2 protein
Predicted disulfide bonds
46 – 267
RTALNCNDSIN – RLSAACNWTRG
69 – 104
FNSTGCPSMLS – DDKPYCWHYAP
76 – 187
SMLSSCKPITF – CGAPSCDIYGG
112 – 275
YAPRSCSTVPA – TRGERCDIEDR
121 – 170
PASSVCGPVYC – GRWFGCVWMNS
126 – 208
CGPVYCFTPSP – FCPTDCFRKHP
160 – 204
FLLESCGPPSG – DTDLFCPTDCF
220 – 300
ATYSRCGAGPW – LAILPCSFTPM
230 – 243
WLTPRCMVDYP – LWHYPCTVNFT
De novo models and quality assessment
Assessment of iTASSER predicted E2 protein models
Epitopes prediction for the vaccine development
Humoral and cellular immunity are the two arms of immunity provided by B-cells and T-cells, respectively. The recognition of pathogenic epitopes by B-cell and T-cells lies at the heart of immune response. Such recognition starts the mechanism of activation of humoral and cellular response and leads to ultimate destruction of pathogenic organism . Epitopes are principal components of both subunit and poly-epitopic vaccines. Thus, it is a pivotal challenge for immune-informatics to accurately predict the B-cell and T-cells epitopes .
It is important for a protein to expose in outside environment to interact with soluble antibodies, B-cells and T-cells. So, the membrane topology of the E2 protein was determined using TMHMM server. In this analysis, a total of 2 transmembrane helices with, 23 amino acids each, were predicted. First helix spans from residue 293 to residue 315 while second helix spans from residue 328 to residue 350. A large 1 to 292 portion of the protein was outside of the membrane and a small loop like structure was present inside the membrane. For the prediction of B-cell and T-cell epitopes, only extra-membranous region was selected. The antigenicity score of selected (1 – 292) region was 0.4911 which indicated that this region as a probable antigen.
B-cell epitopes prediction
B-cell epitopes with their antigenicity score
T cell epitopes prediction
MHC Class I epitopes with their antigenicity scores
HLA-A24, HLA-B_3801, HLA-B_3902, HLA-B_5301, HLA-B_5401, HLA-B_51, HLA-B_0702, HLA-Cw_0401, MHC-Kd
HLA-B_3501, HLA-B_5101, HLA-B_5102, HLA-B_5103, MHC-Ld
HLA-B _3701, HLA-B _3902, HLA-B _5801, HLA-B60, HLA-B7, HLA-Cw _0602, MHC-Kb
HLA-B _5103, HLA-B _5301, HLA-B _51, HLA-B _5801, HLA-B61
MHC Class II epitopes with antigenicity scores
DRB1_0101, DRB1_0102, DRB1_0301, DRB1_0305, DRB1_0306, DRB1_0307, DRB1_0308, DRB1_0309, DRB1_0311, DRB1_0401, DRB1_0402, DRB1_0404, DRB1_0405, DRB1_0408, DRB1_0410, DRB1_0421, DRB1_0423, DRB1_0426, DRB1_0802, DRB1_0804, DRB1_0806, DRB1_0813, DRB1_1101, DRB1_1102, DRB1_1104, DRB1_1106, DRB1_1107, DRB1_1114, DRB1_1120, DRB1_1121, DRB1_1128, DRB1_1301, DRB1_1302, DRB1_1304, DRB1_1305, DRB1_1307, DRB1_1311, DRB1_1321, DRB1_1322, DRB1_1323, DRB1_1327, DRB1_1328, DRB1_1506, DRB5_0101, DRB5_0105
DRB1_0101, DRB1_0701, DRB1_0703,
DRB1_0102, DRB1_0402, DRB1_0701, DRB1_0703,
DRB1_0102, DRB1_0423, DRB1_1501, DRB1_1506
DRB1_0102, DRB1_0404, DRB1_0408, DRB1_0410, DRB1_0421, DRB1_0423,
DRB1_0301, DRB1_0305, DRB1_0309, DRB1_0801, DRB1_0802, DRB1_0804, DRB1_0806, DRB1_0813, DRB1_0817, DRB1_1101, DRB1_1102, DRB1_1104, DRB1_1106, DRB1_1107, DRB1_1114, DRB1_1120, DRB1_1121, DRB1_1301, DRB1_1302, DRB1_1304, DRB1_1307, DRB1_1311, DRB1_1322, DRB1_1323, DRB1_1327, DRB1_1328, DRB1_1501, DRB1_1506
DRB1_0301, DRB1_0305, DRB1_0309, DRB1_1107
DRB1_0301, DRB1_0305, DRB1_0306, DRB1_0307, DRB1_0308, DRB1_0311, DRB1_1107,
DRB1_0305, DRB1_0309, DRB1_0401, DRB1_0405, DRB1_0408, DRB1_0410, DRB1_0421, DRB1_0426, DRB1_0801, DRB1_0802, DRB1_0806, DRB1_0817, DRB1_1101, DRB1_1114, DRB1_1120, DRB1_1128, DRB1_1302, DRB1_1304, DRB1_1305, DRB1_1307, DRB1_1321, DRB1_1323
DRB1_0305, DRB1_0309, DRB1_0401, DRB1_0405, DRB1_0408, DRB1_0421, DRB1_0426, DRB1_0801, DRB1_0802, DRB1_1101, DRB1_1120, DRB1_1128, DRB1_1302, DRB1_1305, DRB1_1307, DRB1_1321,
DRB1_0305, DRB1_0306, DRB1_0307, DRB1_0308, DRB1_0309, DRB1_0311, DRB1_0801, DRB1_0802, DRB1_0813, DRB1_1101, DRB1_1107, DRB1_1114, DRB1_1120, DRB1_1128, DRB1_1302, DRB1_1305, DRB1_1307, DRB1_1323
DRB1_0305, DRB5_0101, DRB5_0105
DRB1_0309, DRB1_0405, DRB1_0421, DRB1_0703
DRB1_0401, DRB1_0408, DRB1_1101
DRB1_0402, DRB1_0405, DRB1_0408, DRB1_0421, DRB1_0801, DRB1_0802, DRB1_0806, DRB1_0813, DRB1_0817, DRB1_1120, DRB1_1302, DRB1_1502
DRB1_0402, DRB1_0701, DRB1_0703, DRB1_0801, DRB1_0802, DRB1_1101, DRB1_1102, DRB1_1114, DRB1_1120, DRB1_1121, DRB1_1128, DRB1_1301, DRB1_1302, DRB1_1304, DRB1_1305, DRB1_1307, DRB1_1323, DRB1_1327, DRB1_1328
DRB1_0402, DRB1_1102, DRB1_1114, DRB1_1120, DRB1_1121, DRB1_1301, DRB1_1302, DRB1_1304, DRB1_1322, DRB1_1323, DRB1_1327, DRB1_1328
DRB1_0405, DRB1_0410, DRB1_0801, DRB1_0806, DRB1_0817, DRB1_1304, DRB1_1321, DRB1_1501, DRB1_1502, DRB1_1506
DRB1_0801, DRB1_0802, DRB1_0813
DRB1_1114, DRB1_1120, DRB1_1302, DRB1_1323
DRB1_1114, DRB1_1120, DRB1_1302, DRB1_1304, DRB1_1323
DRB1_1114, DRB1_1120, DRB1_1302, DRB1_1323,
DRB1_1501, DRB1_1502, DRB1_1506
Conservancy and structural analysis of predicted epitopes
Highly conserved epitopes from E2 of 3a and 1a
T-cell (HLA-B_3501, HLA-B_5101, HLA-B_5102, HLA-B_5103, MHC-Ld)
T-cell (DRB1_0102, DRB1_0423, DRB1_1501, DRB1_1506)
T-cell (DRB1_0309, DRB1_0421)
T-cell (DRB1_0701, DRB1_0703)
T-cell (DRB1_1502, DRB1_1506)
Moreover, it is generally desirable that a vaccine formulation may have one or more B-cell and T-cell epitopes because a wide immune response can efficiently eradicate the invading pathogen. Sometimes, a small protein motif with overlapping epitopes for B-cells and T-cells can stimulate the humoral and cell-mediated immune response. The conserved epitopes in HCV E2 protein showed that the loop-sheet motif from 123 to 136 region contains 5 overlapping epitopes for both B-cells and T-cells (Figure 5). This motif has one B-cell and 4 T-cell epitopes. T-cell epitopes include one MHC class I specific and three MHC class II specific epitopes. Hence, this motif of 13 amino acids can induce broad immune response against HCV pathogen.
HCV is prevalent worldwide and there is no vaccine developed against this virus. There are multiple antigenic components which can be used for vaccine development. In Pakistan, HCV genotype 3a is most common followed by 1a. The sequence, structural and epitope analysis has revealed a number of conserved epitopes in both 3a and 1a genotypes. These epitopes may not only help in diagnosing the pathogens but also may help in developing vaccine against HCV 3a and 1a. Presence of overlapping epitopes generates the hope that a small fragment of peptide in vaccine formulation can elicit broad immune response and may result in efficient clearing of pathogen.
- Jafri W, Subhan A: Hepatitis C in Pakistan: magnitude, genotype, disease characteristics and therapeutic response. Tropical Gastroenterol. 2010, 29: 194-201.Google Scholar
- Al Naamani K, Al Sinani S, Deschenes M: Epidemiology and treatment of hepatitis C genotypes 5 and 6. Can J Gastroenterol. 2013, 27: 8-12.Google Scholar
- Alter MJ: Epidemiology of hepatitis C virus infection. W J Gastroenterol. 2007, 13: 2436-View ArticleGoogle Scholar
- Hussain A, Idrees M: The first complete genome sequence of HCV-1a from Pakistan and a phylogenetic analysis with complete genomes from the rest of the world. Virol J. 2013, 10: 211-10.1186/1743-422X-10-211.PubMed CentralView ArticlePubMedGoogle Scholar
- Ashfaq UA, Javed T, Rehman S, Nawaz Z, Riazuddin S: An overview of HCV molecular biology, replication and immune responses. Virol J. 2011, 8: 161-10.1186/1743-422X-8-161.PubMed CentralView ArticlePubMedGoogle Scholar
- Jhaveri R, Kundu P, Shapiro AM, Venkatesan A, Dasgupta A: Effect of heptitis C virus core protein on cellular gene expression: specific inhibition of cyclooxygenase 2. J Infec Dis. 2005, 191: 1498-1506. 10.1086/429301.View ArticleGoogle Scholar
- Brass V, Moradpour D, Blum HE: Molecular virology of hepatitis C virus (HCV): 2006 update. Int J Med Sci. 2006, 3: 29-PubMed CentralView ArticlePubMedGoogle Scholar
- Penin F, Dubuisson J, Rey FA, Moradpour D, Pawlotsky JM: Structural biology of hepatitis C virus. Hepatol. 2004, 39: 5-19. 10.1002/hep.20032.View ArticleGoogle Scholar
- Afzal S, Idrees M, Ali M, Ilyas M, Hussain A, Akram M, Butt S, Saleem S, Rehman I, Ali L, Shahid M: Envelope 2 protein phosphorylation sites S75 & 277 of hepatitis C virus genotype 1a and interferon resistance: A sequence alignment approach. Virol J. 2011, 8: 71-10.1186/1743-422X-8-71.PubMed CentralView ArticlePubMedGoogle Scholar
- Budkowska A: Mechanism of cell infection with hepatitis C virus (HCV)–a new paradigm in virus-cell interaction. Pol J Microbiol. 2009, 58: 93-98.PubMedGoogle Scholar
- Idrees S, Ashfaq UA, Idrees N: Development of global consensus sequence of HCV glycoproteins involved in viral entry. Theor Biol Med Model. 2013, 10: 24-10.1186/1742-4682-10-24.PubMed CentralView ArticlePubMedGoogle Scholar
- Bartosch B, Dubuisson J, Cosset F-L: Infectious hepatitis C virus pseudo-particles containing functional E1–E2 envelope protein complexes. J Exp Med. 2003, 197: 633-642. 10.1084/jem.20021756.PubMed CentralView ArticlePubMedGoogle Scholar
- Ashfaq UA, Masoud MS, Nawaz Z, Riazuddin S: Glycyrrhizin as antiviral agent against Hepatitis C Virus. J Trans Med. 2011, 9: 112-10.1186/1479-5876-9-112.View ArticleGoogle Scholar
- Gardner JP, Durso RJ, Arrigale RR, Donovan GP, Maddon PJ, Dragic T, Olson WC: L-SIGN (CD 209 L) is a liver-specific capture receptor for hepatitis C virus. Proceed Nat Acad Sci. 2003, 100: 4498-4503. 10.1073/pnas.0831128100.View ArticleGoogle Scholar
- Helle F, Dubuisson J: Hepatitis C virus entry into host cells. Cell and Mol Life Sci. 2008, 65: 100-112. 10.1007/s00018-007-7291-8.View ArticleGoogle Scholar
- Aman W, Mousa S, Shiha G, Mousa SA: Current status and future directions in the management of chronic hepatitis C. Virol J. 2012, 9: 57-10.1186/1743-422X-9-57.PubMed CentralView ArticlePubMedGoogle Scholar
- Susser S, Welsch C, Wang Y, Zettler M, Domingues FS, Karey U, Huges E, Ralston R, Tong X, Herrman E, Zeuzem S, Sarrazin C: Characterization of resistance to the protease inhibitor boceprevir in hepatitis C virus–infected patients. Hepatol. 2009, 50: 1709-1718. 10.1002/hep.23192.View ArticleGoogle Scholar
- Shiffman ML, Esteban R: Triple therapy for HCV genotype 1 infection: telaprevir or boceprevir?. Liver Int. 2012, 32: 54-60.View ArticlePubMedGoogle Scholar
- Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A: Protein Identification and Analysis Tools on the ExPASy Server. The Proteomics Protocols Handbook. 2005, Totowa: Springer, 571-607.View ArticleGoogle Scholar
- Cuff JA, Clamp ME, Siddiqui AS, Finlay M, Barton GJ: JPred: a consensus secondary structure prediction server. Bioinform. 1998, 14: 892-893. 10.1093/bioinformatics/14.10.892.View ArticleGoogle Scholar
- McGuffin LJ, Bryson K, Jones DT: The PSIPRED protein structure prediction server. Bioinforma. 2000, 16: 404-405. 10.1093/bioinformatics/16.4.404.View ArticleGoogle Scholar
- Milburn D, Laskowski RA, Thornton JM: Sequences annotated by structure: a tool to facilitate the use of structural information in sequence analysis. Prot Eng. 1998, 11: 855-859. 10.1093/protein/11.10.855.View ArticleGoogle Scholar
- Ferrè F, Clote P: DiANNA: a web server for disulfide connectivity prediction. Nucleic Acids Res. 2005, 33: W230-W232. 10.1093/nar/gki412.PubMed CentralView ArticlePubMedGoogle Scholar
- Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S: MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011, 28: 2731-2739. 10.1093/molbev/msr121.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang Y: I-TASSER server for protein 3D structure prediction. BMC Bioinform. 2008, 9: 40-10.1186/1471-2105-9-40.View ArticleGoogle Scholar
- Yang Y, Zhou Y: Specific interactions for ab initio folding of protein terminal regions with secondary structures. Proteins. 2008, 72: 793-803. 10.1002/prot.21968.View ArticlePubMedGoogle Scholar
- Laskowski RA, MacArthur MW, Moss DS, Thornton JM: PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Cryst. 1993, 26: 283-291. 10.1107/S0021889892009944.View ArticleGoogle Scholar
- Guex N, Peitsch MC: SWISS-MODEL and the Swiss-Pdb Viewer: an environment for comparative protein modeling. Electrophor. 1997, 18: 2714-2723. 10.1002/elps.1150181505.View ArticleGoogle Scholar
- Humphrey W, Dalke A, Schulten K: VMD: visual molecular dynamics. J Mol Graph. 1996, 14: 33-38. 10.1016/0263-7855(96)00018-5.View ArticlePubMedGoogle Scholar
- Doytchinova IA, Flower DR: VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 2007, 8: 4-10.1186/1471-2105-8-4.View ArticleGoogle Scholar
- Krogh A, Larsson B, Von Heijne G, Sonnhammer EL: Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001, 305: 567-580. 10.1006/jmbi.2000.4315.View ArticlePubMedGoogle Scholar
- EL‒Manzalawy Y, Dobbs D, Honavar V: Predicting linear B-cell epitopes using string kernels. J Mol Recog. 2008, 21: 243-255. 10.1002/jmr.893.View ArticleGoogle Scholar
- Singh H, Raghava G: ProPred: prediction of HLA-DR binding sites. Bioinform. 2001, 17: 1236-1237. 10.1093/bioinformatics/17.12.1236.View ArticleGoogle Scholar
- Bui H-H, Sidney J, Li W, Fusseder N, Sette A: Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines. BMC Bioinform. 2007, 8: 361-10.1186/1471-2105-8-361.View ArticleGoogle Scholar
- Lazoura E, Lodding J, Farrugia W, Ramsland PA, Stevens J, Wilson IA, Pietersz GA, Apostolopoulos V: Enhanced major histocompatibility complex class I binding and immune responses through anchor modification of the non-canonical tumour-associated mucin 1–8 peptide. Immunol. 2006, 119: 306-316. 10.1111/j.1365-2567.2006.02434.x.View ArticleGoogle Scholar
- Niemann HH, Schubert W-D, Heinz DW: Adhesins and invasins of pathogenic bacteria: a structural view. Microb Infect. 2004, 6: 101-112. 10.1016/j.micinf.2003.11.001.View ArticleGoogle Scholar
- Pietersz GA, Pouniotis DS, Apostolopoulos V: Design of peptide-based vaccines for cancer. Curr Med Chem. 2006, 13: 1591-1607. 10.2174/092986706777441922.View ArticlePubMedGoogle Scholar
- Bhasin M, Raghava G: A hybrid approach for predicting promiscuous MHC class I restricted T cell epitopes. J Biosci. 2007, 32: 31-42. 10.1007/s12038-007-0004-5.View ArticlePubMedGoogle Scholar
- Sturniolo T, Bono E, Ding J, Raddrizzani L, Tuereci O, Sahin U, Braxenthaler M, Gallazzi F, Protti MP, Sinigaglia F, Hammer J: Generation of tissue-specific and promiscuous HLA ligand databases using DNA microarrays and virtual HLA class II matrices. Nat Biotechnol. 1999, 17: 555-561. 10.1038/9858.View ArticlePubMedGoogle Scholar
- Remaut H, Waksman G: Structural biology of bacterial pathogenesis. Curr Opin Struct Biol. 2004, 14: 161-170. 10.1016/j.sbi.2004.03.004.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.