Article Versions
Export Article
Cite this article
  • Normal Style
  • MLA Style
  • APA Style
  • Chicago Style
Research Article
Open Access Peer-reviewed

Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin

Shirin Tarahomjoo , Soheila Ghaderi
American Journal of Microbiological Research. 2017, 5(6), 118-123. DOI: 10.12691/ajmr-5-6-1
Published online: November 22, 2017

Abstract

Pneumococcal conjugate vaccines (PCVs) were constructed through chemical conjugation of pneumococcal capsules to immunogenic carrier proteins. The PCVs implementation in developing countries was prevented by their high manufacturing costs. This issue can be overcome by development of protein based vaccines against pneumococci. Antibody responses are necessary for protection against S. pneumoniae. Choline binding protein D (CBPD) was already identified as a pneumococcal surface protein able to elicit protection against S. pneumoniae and its most protective B-cell epitope region (MIBR) was determined. MIBR was highly conserved in common pneumococcal serotypes. Whole antigens are not as potent as epitope based vaccines and B-cell epitope based vaccines are more effective than whole antigen based vaccines in the prevention of infections. Bacterial flagellins are effective adjuvants that signal via Toll like receptor 5 (TLR5). The TLR5 binding site of flagellin located in the D1 domain and its proper conformation is critical for TLR5 recognition of flagellin. In the present study, therefore, we aim to design effective chimeric vaccines against pneumococci based on MIBR and flagellin of Salmonella Enteritidis (FliC) using bioinformatics tools. FliC was joined to MIBR at N-terminus (CFH), C-terminus (FCH) and the D3 domain (D3Gly202, D3Thr275). All of the constructs were immunoprotective regarding the VaxiJen score (0.8). The codon optimization for constructs was done using OPTIMIZER. Analysis of the mRNA secondary structures using Mfold tool revealed no stable hairpins at 5' ends of constructs and thus the antigens can be expressed appropriately. SCRATCH results indicated that the antigens can be expressed in the soluble form in Escherichia coli at more than 80% probability. The 3D models of antigens resulted from I-TASSER indicated the presence of alpha helix, beta sheet, turn, coil, and 310 helix as the protein structural elements. Superimposing 3D models of D1 domains of antigens with the D1 domain of FliC using FATCAT indicated no change in the D1 conformation. Therefore, FliC can exert its adjuvant effects in these constructs through TLR5 signaling. Inserting MIBR in Gly202 of FliC enhanced the protein beta sheet content remarkably, which can result in appropriate thermostability of the antigen. Our results, therefore, demonstrated that D3Gly202 is a suitable vaccine candidate, which can elicit protection against common S. pneumoniae serotypes causing invasive pneumococcal disease in children less than 5 years of age.

1. Introduction

Streptococcus pneumoniae is a major cause of diseases such as meningitis, pneumoniae and sepsis mainly in children less than 5 years of age 1, 2. World Health Organization (WHO) reported that 476000 annual deaths among children less than 5 years of age were caused by pneumococcal infections 3. Pneumococcal vaccines have been used to protect against pneumococcal infections. The capsular polysaccharides of pneumococci are main antigenic components of these vaccines. However, the capsules are weakly immunogenic in children and are not able to induce immune memory. Pneumococcal conjugate vaccines (PCVs) are then constructed through chemical conjugation of pneumococcal capsules to immunogenic carrier proteins. The conjugation process increases the antibody response and induces the immune memory. WHO recommends the inclusion of PCVs in national immunization programs for children. However, the PCVs production requires multistep processes and the elicited protection is serotype dependent. These vaccines include conjugated capsules of multiple pneumococcal serotypes. Therefore, the vaccine manufacturing costs are high and limit PCVs implementation in national immunization programs of developing countries 1, 2, 3.

The development of protein based vaccines against pneumococci offers a more affordable protective strategy against pneumococcal infections. 4. Cell surface proteins are key factors in infective processes of pathogens and have extensively been evaluated as vaccine candidates 5, 6. Several pneumococcal surface proteins such as pneumococcal surface protein A, pneumococcal surface protein C, pneumococcal surface adhesin A, pilus proteins and histidine triad proteins were able to induce protection against S. pneumoniae 7. We already identified choline binding protein D (CBPD), a pneumococcal surface protein as a suitable candidate for eliciting protection against S. pneumoniae. The candidate selection was based on the protein ability to elicit immunoprotection, the absence of autoimmunity induction and the amino acid sequence conservancy in pneumococcal strains 8. Antibody responses are essential for protection against pneumococcal infections 7. Antibodies bind specifically to a continuous amino acid sequence known as the linear B-cell epitope or to a folded structure composed of discontinuous amino acids known as the conformational B-cell epitopes. Therefore, the analysis of protective B-cell epitopes in vaccine candidates is necessary to develop effective vaccines against pneumococci 9. The majority of B-cell epitopes are conformational. Nevertheless, the identification of linear B-cell epitopes has shown promising results for selection of the vaccine constituents 10, 11. Whole antigens are not as potent as epitope based vaccines and B-cell epitope based vaccines are more effective than whole antigen based vaccines in the prevention of infections 12, 13. Compared with conventional laboratory methods, computational approaches offer the ability to undertake rapid and comprehensive epitope assessments at much lower costs 14. Simultaneous applications of B-cell epitope prediction tools enhance the epitope prediction accuracy 15. We already determined B-cell epitope regions of CBPD by simultaneous applications of widely used bioinformatics tools 16. Bacterial flagellins, the structural subunit of flagellar filaments, are effective adjuvants that signal via Toll like receptor 5 (TLR5). Structural analysis of these proteins revealed a boomerang shaped protein with four major domains. The vertical arm is constructed from domains D0 and D1, which are well conserved. The horizontal arm of the protein comprised of domains D2 and D3, which are highly variable in sequence. The TLR5 binding site of flagellin located in the D1 domain and its proper conformation is critical for TLR5 recognition of flagellin 17. In the present study, we aim to design effective vaccines against pneumococci comprising fusion proteins linking the identified B-cell epitope region of CBPD to flagellin of Salmonella Enteritidis (FliC) as built in adjuvant. The appropriate fusion strategy was then investigated through evaluating immunological, transcriptional, and structural properties of designed constructs and the suitable antigen for inclusion in the vaccine was determined.

2. Methods

The immunoprotective abilities of antigens were evaluated using VaxiJen 18. The codon optimization and calculations of the codon adaptation index (CAI) were performed using the OPTIMIZER online tool. Escherichia coli K-12 is the basic strain for the construction of E. coli based expression hosts. Therefore, the codon usage table of E. coli K-12 obtained from Kazusa codon usage database was used for the codon optimization 19. Prediction of the mRNA secondary structure was carried out using Mfold web server 20. Moreover, the probability of the protein over-expression in E. coli in the soluble form was calculated using the SCRATCH protein prediction tool 21. I-TASSER web server was used for de novo prediction of the protein tertiary structure from the amino acid sequence 22. The quality of 3D models was examined using ProSA online tool 23. YASARA was used to visualize the protein tertiary structure and to determine the protein secondary structure constituents. Superimposing protein structures was carried out using the FATCAT program 24. Ellipro was used to assess the solvent accessibility of amino acid residues 25.

3. Results and Discussion

3.1. Design of Chimeric Vaccines

The incidence of invasive pneumococcal disease (IPD) is frequently used as a measure of the incidence of severe pneumococcal disease. Pneumococcal serotypes 1, 5, 6A, 6B, 14, 19F and 23F are common causes of IPD globally in children less than 5 years of age 3. Bepipred and BCPreds are widely used bioinformatics tools for identification of linear B-cell epitopes. The CBTope program is used for the prediction of conformational B-cell epitopes using amino acid sequences 15. We already identified linear B-cell epitope regions in CBPD from serotype 19F S. pneumoniae using Bepipred. Furthurmore, conformational B-cell epitope regions of CBPD were identified by CBTope 16. The identified B-cell epitope regions overlapped linear B-cell epitopes identified by BCPreds. The B-cell epitope region containing amino acid residues 172-195 was the most probable immunoprotective B-cell epitope region (MIBR) regarding the VaxiJen score. Moreover, The MIBR amino acid sequence was highly conserved (more than 91% amino acid sequence match) among the common pneumococcal serotypes (unpublished results). VaxiJen was developed to classify antigens solely based on their physicochemical properties without the need for sequence alignments. A higher VaxiJen score refers to a higher probability for the immunoprotective ability. FliC was fused to the identified MIBR of CBPD at N-terminus (CFH), C-terminus (FCH) and the D3 domain (D3Gly202, D3Thr275). The insertion sites of D3 domain containing Glycine 202 and Threonie 275 were located in loop regions of FliC. A histidine tag was introduced at the C-terminus of constructs. VaxiJen scores of all of the constructs were about 0.8. Therefore, all of them were immunoprotective.

Adapting the gene codon usage to the host codon usage can enhance the expression level of the encoded protein. The codon optimization includes altering target gene codons so that they reflect the codon usage of the host more closely without changing the amino acid sequence of the encoded protein 19. Results of OPTIMIZER showed that CAIs of native genes of all the constructs were 0.65. However, the codon optimized gene sequences showed a CAI of 1. CAI measures the similarity between the codon usage of a gene and the codon usage of the reference set of genes. Its value is in the range of 0-1 19. Therefore, the codon usage of the optimized gene sequence was the same as the codon usage of E. coli reference group of genes and the optimized gene can be expressed at suitable levels in E. coli. GC contents of native genes of all the constructs were increased on average from 44.45% to 55.85% upon codon optimization. The GC content of the gene affects its codon usage 26. The gene expression level correlates inversely with the stability of mRNA hairpin structures close to the 5' end of mRNA 27. The 5' ends of the optimized genes mRNA did not constrain any stable hairpins as predicted by Mfold (Figure 1). Therefore the designed vaccines are expected to be expressed at appropriate levels.

E. coli is a popular host for expression of recombinant proteins owing to its superior properties including the ease of genetic manipulation and the high expression level. However, E. coli is often not able to fold foreign proteins properly and inclusion bodies are then formed. The protein recovery from inclusion bodies requires a multistep complex process, which can lead to a significant loss in the final protein yield 28, 29. SCRATCH was used for predicting the probability of the protein expression in the soluble form in E. coli. Solubility probabilities of CFH, FCH, D3Gly202 and D3Thr275 were 0.838, 0.824, 0.838 and 0.835 respectively. Therefore, the majority of proteins is expressed in the soluble form in E. coli and can then be recovered from the soluble cellular fraction instead of inclusion bodies.

3.2. Structures of chimeric Vaccines

The tertiary structures of designed vaccines were predicted using I-TASSER. I-TASSER predicts 5 models for each construct (data not shown). The most confident models given for CFH, FCH, D3Gly202, and D3Thr275 (Figure 2) had confidence scores (C-score) of -0.43, -0.99, -0.57, and -0.75 respectively. C-score is in the range of -5 to 2 and a higher C-score indicates a model with a higher confidence 22. ProSA was used to check the quality of antigens 3D models. The obtained z-scores for the 3D models of CFH, FCH, D3Gly202, and D3Thr275 were -4.1, -3.6, -5.13, and -5.33 respectively and these scores were within the range of typical scores of native proteins at the similar sizes (data not shown). Alpha helix, beta sheet, turn, coil and 310 helix were the structural elements of designed vaccines (Table 1). The percentages of structural elements in antigens secondary structures were determined using YASARA. Fusion of MIBR to the N-terminus of FliC resulted in enhancing the protein beta sheet content. Whereas joining MIBR to the C-terminus of FliC decreased the beta sheet content. D3Gly202 showed the highest beta sheet content between the designed vaccines and the lowest beta sheet content was observed in the D3Thr275 structure. It was shown that the increase in the protein beta sheet content was much more significant in hyperthermophilic proteins compared with moderately thermophilic ones. In addition, enhancing the beta sheet content increased the protein thermostability 27. Therefore, D3Gly202 is expected to have the highest thermostability among designed vaccines.

The TLR5 binding region of FliC resides in the D1 domain and its appropriate conformation is necessary for TLR5 recognition of FliC. Therefore, we compared the D1 structures in designed vaccines with that of FliC by superimposing them using FATCAT program. FATCAT results indicated that the D1 structure of D3Gly202 was significantly similar to the D1 structure of FliC (Figure 3). The D1 structures of D3Thr275, CFH and FCH were also significantly similar to the D1 structure of FliC (data not shown). Our results indicated that the conformation of the D1 domain of designed vaccines was not different from that of FliC and thus FliC can exert its adjuvant effects in these constructs via TLR5 signaling.

3.3. Solvent accessibility of MIBR residues in designed constructs

B-cell epitopes should be exposed on the protein surface to be recognized by B-cells or bind to antibodies. A higher solvent accessibility for an amino acid residue indicates its better surface exposure. The solvent accessibility of MIBR amino acid residues in designed vaccines were evaluated using Ellipro. Amino acid residues with higher scores assigned by Ellipro, were associated with a better solvent accessibility. All of the amino acid residues of MIBR in fusion proteins were solvent accessible and therefore exposed on the protein surface. However, solvent accessibilities of PHE1 to GLY10 of MIBR in FCH were higher than those of MIBR in other designed vaccines (Table 2). In addition, the solvent accessibilities of GLN12 to TYR22 of MIBR in CFH were higher than those of other antigens. The variations in the solvent accessibilities of MIBR residues correlate with alterations in FliC conformations in designed constructs.

4. Conclusions

The insertion of MIBR in FliC did not alter the conformation of D1 domain, which includes the TLR5 binding region. Therefore, FliC can exert its adjuvant effects in the designed chimeric vaccines through TLR5 signaling. The MIBR insertion in GLy202 enhanced the beta sheet content remarkably, which can improve the vaccine thermostability. Moreover, D3Gly202 can elicit protection against common serotypes of S. pneumoniae and can be expressed at appropriate levels in E. coli in the soluble form. Therefore, it is a suitable proteinaceous vaccine candidate against S. pneumoniae.

References

[1]  Mook-Kanamori, B.B., et al., Pathogenesis and pathophysiology of pneumococcal meningitis. Clinical microbiology reviews, 2011. 24(3): p. 557-591.
In article      View Article  PubMed
 
[2]  Johnson, H.L., et al., Systematic evaluation of serotypes causing invasive pneumococcal disease among children under five: the pneumococcal global serotype project. PLoS Med, 2010. 7(10): p. e1000348.
In article      View Article  PubMed
 
[3]  Publication, W., Pneumococcal vaccines WHO position paper-2012–recommendations. Vaccine, 2012. 30(32): p. 4717-4718.
In article      View Article  PubMed
 
[4]  Ginsburg, A.S., et al., Issues and challenges in the development of pneumococcal protein vaccines. Expert review of vaccines, 2012. 11(3): p. 279-285.
In article      View Article  PubMed
 
[5]  Foster, T.J., et al., Adhesion, invasion and evasion: the many functions of the surface proteins of Staphylococcus aureus. Nature Reviews Microbiology, 2014. 12(1): p. 49-62.
In article      View Article  PubMed
 
[6]  Bergmann, S. and S. Hammerschmidt, Versatility of pneumococcal surface proteins. Microbiology, 2006. 152(2): p. 295-303.
In article      View Article  PubMed
 
[7]  Tarahomjoo, S., Recent approaches in vaccine development against Streptococcus pneumoniae. Journal of molecular microbiology and biotechnology, 2014. 24(4): p. 215-227.
In article      View Article  PubMed
 
[8]  Tarahomjoo, S., Bioinformatic analysis of surface proteins of Streptococcus pneumoniae serotype 19F for identification of vaccine candidates. American Journal of Microbiological Research, 2014. 2(6): p. 174-177.
In article      View Article
 
[9]  Novotný, J.í., et al., Antigenic determinants in proteins coincide with surface regions accessible to large probes (antibody domains). Proceedings of the National Academy of Sciences, 1986. 83(2): p. 226-230.
In article      View Article
 
[10]  Quijada, L., et al., Mapping of the linear antigenic determinants of the Leishmania infantum hsp70 recognized by leishmaniasis sera. Immunology letters, 1996. 52(2): p. 73-79.
In article      View Article
 
[11]  Faria, A.R., et al., High-throughput analysis of synthetic peptides for the immunodiagnosis of canine visceral leishmaniasis. PLoS Negl Trop Dis, 2011. 5(9): p. e1310.
In article      View Article  PubMed
 
[12]  Zhao, Z., et al., Multiple B-cell epitope vaccine induces a Staphylococcus enterotoxin B-specific IgG1 protective response against MRSA infection. Scientific reports, 2015. 5.
In article      View Article
 
[13]  Lu, Y., et al., A candidate vaccine against influenza virus intensively improved the immunogenicity of a neutralizing epitope. International archives of allergy and immunology, 2002. 127(3): p. 245-250.
In article      View Article  PubMed
 
[14]  Kelly, D.F. and R. Rappuoli, Reverse vaccinology and vaccines for serogroup B Neisseria meningitidis, in Hot Topics in Infection and Immunity in Children II. 2005, Springer. p. 217-223.
In article      View Article  PubMed
 
[15]  Assis, L., et al., Bcell epitopes of antigenic proteins in Leishmania infantum: an in silico analysis. Parasite immunology, 2014. 36(7): p. 313-323.
In article      View Article  PubMed
 
[16]  Tarahomjoo, S, In silico Analysis of Surface Proteins of Streptococcus pneumoniae Serotype 19F for Identification of Immunoprotective Epitopes. American Journal of Microbiological Research, 2015. 3 (6): p. 190-196.
In article      View Article
 
[17]  Andersen – Nissen, E., K. D. Smith, K. L. Strobe, et al. Evasion of toll like receptor 5 by flagellated bacteria. Proceeding of National Academy of Science USA 2005. 102 (26): p. 9247-9252.
In article      View Article  PubMed
 
[18]  Doytchinova, I.A. and D.R. Flower, Bioinformatic approach for identifying parasite and fungal candidate subunit vaccines. Open Vaccine J, 2008. 1(1): p. 4.
In article      View Article
 
[19]  Puigbo, P., et al., OPTIMIZER: a web server for optimizing the codon usage of DNA sequences. Nucleic acids research, 2007. 35(suppl 2): p. W126-W131.
In article      View Article  PubMed
 
[20]  Zuker, M., Mfold web server for nucleic acid folding and hybridization prediction. Nucleic acids research, 2003. 31(13): p. 3406-3415.
In article      View Article  PubMed
 
[21]  Cheng J, A. Z. Randall, M. J. Sweredoski and P. Baldi, SCRATCH: a protein structure and structural feature prediction server. Nucleic acids research, 2005. 33 (suppl 2): p.W72-W76.
In article      View Article  PubMed
 
[22]  Roy, A., A. Kucukural, and Y. Zhang, I-TASSER: a unified platform for automated protein structure and function prediction. Nature protocols, 2010. 5(4): p. 725-738.
In article      View Article  PubMed
 
[23]  Wiederstein, M. and M. J. Sippl, ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic acids research, 2007. 35 (suppl 2): p. W407-W410.
In article      View Article  PubMed
 
[24]  Yuzhen Ye and A. Godzik. Flexible structure alignment by chaining aligned fragment pairs allowing twists. Bioinformatics, 2003. 19 (suppl 2): p. ii246-ii255.
In article      View Article  PubMed
 
[25]  Ponomarenko J.V., et al., ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 2008. 9: p. 514.
In article      View Article  PubMed
 
[26]  Li, J., et al., GC-content of synonymous codons profoundly influences amino acid usage. G3: Genes| Genomes| Genetics, 2015. 5(10): p. 2027-2036.
In article      View Article  PubMed
 
[27]  Seo, S.W., J. Yang, and G.Y. Jung, Quantitative correlation between mRNA secondary structure around the region downstream of the initiation codon and translational efficiency in Escherichia coli. Biotechnology and bioengineering, 2009. 104(3): p. 611-616.
In article      View Article  PubMed
 
[28]  Singh, S.M. and A.K. Panda, Solubilization and refolding of bacterial inclusion body proteins. Journal of bioscience and bioengineering, 2005. 99(4): p. 303-310.
In article      View Article  PubMed
 
[29]  Yin, J., et al., Select what you need: a comparative evaluation of the advantages and limitations of frequently used expression systems for foreign genes. Journal of Biotechnology, 2007. 127(3): p. 335-347.
In article      View Article  PubMed
 

Published with license by Science and Education Publishing, Copyright © 2017 Shirin Tarahomjoo and Soheila Ghaderi

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Cite this article:

Normal Style
Shirin Tarahomjoo, Soheila Ghaderi. Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin. American Journal of Microbiological Research. Vol. 5, No. 6, 2017, pp 118-123. http://pubs.sciepub.com/ajmr/5/6/1
MLA Style
Tarahomjoo, Shirin, and Soheila Ghaderi. "Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin." American Journal of Microbiological Research 5.6 (2017): 118-123.
APA Style
Tarahomjoo, S. , & Ghaderi, S. (2017). Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin. American Journal of Microbiological Research, 5(6), 118-123.
Chicago Style
Tarahomjoo, Shirin, and Soheila Ghaderi. "Novel Vaccines against Streptococcus pneumoniae Based on the Immunoprotective B-cell Epitope Region of Pneumococcal Choline Binding Protein D and Salmonella Enteritidis Flagellin." American Journal of Microbiological Research 5, no. 6 (2017): 118-123.
Share
  • Figure 1. The mRNA secondary structures and free energy details at 5' ends of chimeric vaccines predicted by Mfold. A, CFH; B, FCH; C, D3Gly202; D3Thr75
  • Figure 2. 3D models of chimeric vaccines. A, CFH; B, FCH; C, D3Gly202; D, D3Thr275; E, Flagellin. MIBR of CBPD was shown in pink color in A and B. This region was shown in Gray color in C and D
[1]  Mook-Kanamori, B.B., et al., Pathogenesis and pathophysiology of pneumococcal meningitis. Clinical microbiology reviews, 2011. 24(3): p. 557-591.
In article      View Article  PubMed
 
[2]  Johnson, H.L., et al., Systematic evaluation of serotypes causing invasive pneumococcal disease among children under five: the pneumococcal global serotype project. PLoS Med, 2010. 7(10): p. e1000348.
In article      View Article  PubMed
 
[3]  Publication, W., Pneumococcal vaccines WHO position paper-2012–recommendations. Vaccine, 2012. 30(32): p. 4717-4718.
In article      View Article  PubMed
 
[4]  Ginsburg, A.S., et al., Issues and challenges in the development of pneumococcal protein vaccines. Expert review of vaccines, 2012. 11(3): p. 279-285.
In article      View Article  PubMed
 
[5]  Foster, T.J., et al., Adhesion, invasion and evasion: the many functions of the surface proteins of Staphylococcus aureus. Nature Reviews Microbiology, 2014. 12(1): p. 49-62.
In article      View Article  PubMed
 
[6]  Bergmann, S. and S. Hammerschmidt, Versatility of pneumococcal surface proteins. Microbiology, 2006. 152(2): p. 295-303.
In article      View Article  PubMed
 
[7]  Tarahomjoo, S., Recent approaches in vaccine development against Streptococcus pneumoniae. Journal of molecular microbiology and biotechnology, 2014. 24(4): p. 215-227.
In article      View Article  PubMed
 
[8]  Tarahomjoo, S., Bioinformatic analysis of surface proteins of Streptococcus pneumoniae serotype 19F for identification of vaccine candidates. American Journal of Microbiological Research, 2014. 2(6): p. 174-177.
In article      View Article
 
[9]  Novotný, J.í., et al., Antigenic determinants in proteins coincide with surface regions accessible to large probes (antibody domains). Proceedings of the National Academy of Sciences, 1986. 83(2): p. 226-230.
In article      View Article
 
[10]  Quijada, L., et al., Mapping of the linear antigenic determinants of the Leishmania infantum hsp70 recognized by leishmaniasis sera. Immunology letters, 1996. 52(2): p. 73-79.
In article      View Article
 
[11]  Faria, A.R., et al., High-throughput analysis of synthetic peptides for the immunodiagnosis of canine visceral leishmaniasis. PLoS Negl Trop Dis, 2011. 5(9): p. e1310.
In article      View Article  PubMed
 
[12]  Zhao, Z., et al., Multiple B-cell epitope vaccine induces a Staphylococcus enterotoxin B-specific IgG1 protective response against MRSA infection. Scientific reports, 2015. 5.
In article      View Article
 
[13]  Lu, Y., et al., A candidate vaccine against influenza virus intensively improved the immunogenicity of a neutralizing epitope. International archives of allergy and immunology, 2002. 127(3): p. 245-250.
In article      View Article  PubMed
 
[14]  Kelly, D.F. and R. Rappuoli, Reverse vaccinology and vaccines for serogroup B Neisseria meningitidis, in Hot Topics in Infection and Immunity in Children II. 2005, Springer. p. 217-223.
In article      View Article  PubMed
 
[15]  Assis, L., et al., Bcell epitopes of antigenic proteins in Leishmania infantum: an in silico analysis. Parasite immunology, 2014. 36(7): p. 313-323.
In article      View Article  PubMed
 
[16]  Tarahomjoo, S, In silico Analysis of Surface Proteins of Streptococcus pneumoniae Serotype 19F for Identification of Immunoprotective Epitopes. American Journal of Microbiological Research, 2015. 3 (6): p. 190-196.
In article      View Article
 
[17]  Andersen – Nissen, E., K. D. Smith, K. L. Strobe, et al. Evasion of toll like receptor 5 by flagellated bacteria. Proceeding of National Academy of Science USA 2005. 102 (26): p. 9247-9252.
In article      View Article  PubMed
 
[18]  Doytchinova, I.A. and D.R. Flower, Bioinformatic approach for identifying parasite and fungal candidate subunit vaccines. Open Vaccine J, 2008. 1(1): p. 4.
In article      View Article
 
[19]  Puigbo, P., et al., OPTIMIZER: a web server for optimizing the codon usage of DNA sequences. Nucleic acids research, 2007. 35(suppl 2): p. W126-W131.
In article      View Article  PubMed
 
[20]  Zuker, M., Mfold web server for nucleic acid folding and hybridization prediction. Nucleic acids research, 2003. 31(13): p. 3406-3415.
In article      View Article  PubMed
 
[21]  Cheng J, A. Z. Randall, M. J. Sweredoski and P. Baldi, SCRATCH: a protein structure and structural feature prediction server. Nucleic acids research, 2005. 33 (suppl 2): p.W72-W76.
In article      View Article  PubMed
 
[22]  Roy, A., A. Kucukural, and Y. Zhang, I-TASSER: a unified platform for automated protein structure and function prediction. Nature protocols, 2010. 5(4): p. 725-738.
In article      View Article  PubMed
 
[23]  Wiederstein, M. and M. J. Sippl, ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic acids research, 2007. 35 (suppl 2): p. W407-W410.
In article      View Article  PubMed
 
[24]  Yuzhen Ye and A. Godzik. Flexible structure alignment by chaining aligned fragment pairs allowing twists. Bioinformatics, 2003. 19 (suppl 2): p. ii246-ii255.
In article      View Article  PubMed
 
[25]  Ponomarenko J.V., et al., ElliPro: a new structure-based tool for the prediction of antibody epitopes. BMC Bioinformatics, 2008. 9: p. 514.
In article      View Article  PubMed
 
[26]  Li, J., et al., GC-content of synonymous codons profoundly influences amino acid usage. G3: Genes| Genomes| Genetics, 2015. 5(10): p. 2027-2036.
In article      View Article  PubMed
 
[27]  Seo, S.W., J. Yang, and G.Y. Jung, Quantitative correlation between mRNA secondary structure around the region downstream of the initiation codon and translational efficiency in Escherichia coli. Biotechnology and bioengineering, 2009. 104(3): p. 611-616.
In article      View Article  PubMed
 
[28]  Singh, S.M. and A.K. Panda, Solubilization and refolding of bacterial inclusion body proteins. Journal of bioscience and bioengineering, 2005. 99(4): p. 303-310.
In article      View Article  PubMed
 
[29]  Yin, J., et al., Select what you need: a comparative evaluation of the advantages and limitations of frequently used expression systems for foreign genes. Journal of Biotechnology, 2007. 127(3): p. 335-347.
In article      View Article  PubMed