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Immunoinformatics design of a novel epitope-based vaccine candidate against dengue virus

  • 1.

    Hotez, P. J., Aksoy, S., Brindley, P. J. & Kamhawi, S. What Constitutes a Neglected Tropical Disease? (Public Library of Science, 2020).

    Book 

    Google Scholar 

  • 2.

    Fitzpatrick, C., Nwankwo, U., Lenk, E., de Vlas, S. J. & Bundy, D. A. An Investment Case for Ending Neglected Tropical Diseases (The World Bank, 2017).

    Book 

    Google Scholar 

  • 3.

    Rees, C. A., Hotez, P. J., Monuteaux, M. C., Niescierenko, M. & Bourgeois, F. T. Neglected tropical diseases in children: An assessment of gaps in research prioritization. PLoS Negl. Trop. Dis. 13, e0007111 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 4.

    Adekiya, T. A., Aruleba, R. T., Klein, A. & Fadaka, A. O. In silico inhibition of SGTP4 as a therapeutic target for the treatment of schistosomiasis. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2020.1850363 (2020).

    Article 
    PubMed 

    Google Scholar 

  • 5.

    Hotez, P. J. Ten global “hotspots” for the neglected tropical diseases. PLoS Negl. Trop. Dis. 8, e2496 (2014).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 6.

    Relman, D. A. & Choffnes, E. R. The Causes and Impacts of Neglected Tropical and Zoonotic Diseases: Opportunities for Integrated Intervention Strategies (National Academies Press, 2011).

    Google Scholar 

  • 7.

    Waggoner, J. J. et al. Viremia and clinical presentation in Nicaraguan patients infected with Zika virus, chikungunya virus, and dengue virus. Clin. Infect. Dis. 63, 1584–1590 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 8.

    Organization WH, UNICEF. Global vector control response 2017–2030 (UNICEF, 2017).

    Google Scholar 

  • 9.

    Organization, W. H. A Global Brief on Vector-Borne Diseases (World Health Organization, 2014).

    Google Scholar 

  • 10.

    Gurugama, P., Garg, P., Perera, J., Wijewickrama, A. & Seneviratne, S. L. Dengue viral infections. Indian J. Dermatol. 55, 68 (2010).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 11.

    Malavige, G., Fernando, S., Fernando, D. & Seneviratne, S. Dengue viral infections. Postgrad. Med. J. 80, 588–601 (2004).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 12.

    da Silveira, L. T. C., Tura, B. & Santos, M. Systematic review of dengue vaccine efficacy. BMC Infect. Dis. 19, 750 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 13.

    Crill, W. D. & Roehrig, J. T. Monoclonal antibodies that bind to domain III of dengue virus E glycoprotein are the most efficient blockers of virus adsorption to Vero cells. J. Virol. 75, 7769–7773 (2001).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 14.

    Lai, C. Y. et al. Antibodies to envelope glycoprotein of dengue virus during the natural course of infection are predominantly cross-reactive and recognize epitopes containing highly conserved residues at the fusion loop of domain II. J. Virol. 82, 6631–6643 (2008).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 15.

    Beltramello, M. et al. The human immune response to Dengue virus is dominated by highly cross-reactive antibodies endowed with neutralizing and enhancing activity. Cell Host Microbe. 8, 271–283 (2010).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 16.

    Oliphant, T. et al. Antibody recognition and neutralization determinants on domains I and II of West Nile Virus envelope protein. J. Virol. 80, 12149–12159 (2006).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 17.

    Guy, B. et al. A recombinant live attenuated tetravalent vaccine for the prevention of dengue. Expert Rev. Vaccines 16, 671–684 (2017).

    CAS 
    Article 

    Google Scholar 

  • 18.

    Dayan, G. H. et al. Immunogenicity and safety of a recombinant tetravalent dengue vaccine in children and adolescents ages 9–16 years in Brazil. Am. J. Trop. Med. Hyg. 89, 1058 (2013).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 19.

    Sridhar, S. et al. Effect of dengue serostatus on dengue vaccine safety and efficacy. N. Engl. J. Med. 379, 327–340 (2018).

    PubMed 
    Article 

    Google Scholar 

  • 20.

    Lanata, C. F. et al. Immunogenicity and safety of tetravalent dengue vaccine in 2–11 year-olds previously vaccinated against yellow fever: Randomized, controlled, phase II study in Piura, Peru. Vaccines 30, 5935–5941 (2012).

    CAS 
    Article 

    Google Scholar 

  • 21.

    Amar-Singh, H. et al. Safety and immunogenicity of a tetravalent dengue vaccine in healthy children aged 2–11 years in Malaysia: A randomized, placebo-controlled, Phase III study. Vaccine 31, 5814–5821 (2013).

    Article 
    CAS 

    Google Scholar 

  • 22.

    Halstead, S. B. Safety issues from a Phase 3 clinical trial of a live-attenuated chimeric yellow fever tetravalent dengue vaccine. Hum. Vaccine Immunother. 14, 2158–2162 (2018).

    Article 

    Google Scholar 

  • 23.

    Halstead, S. B. Neutralization and antibody-dependent enhancement of dengue viruses. Adv. Virus Res. 60, 421–467 (2003).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 24.

    Pinheiro-Michelsen, J. R. et al. Anti-dengue Vaccines: From development to clinical trials. Front. Immunol. 11, 1252 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 25.

    Men, R., Bray, M., Clark, D., Chanock, R. M. & Lai, C. J. Dengue type 4 virus mutants containing deletions in the 3’ noncoding region of the RNA genome: Analysis of growth restriction in cell culture and altered viremia pattern and immunogenicity in rhesus monkeys. J. Virol. 70, 3930–3937 (1996).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 26.

    Durbin, A. P. et al. Attenuation and immunogenicity in humans of a live dengue virus type-4 vaccine candidate with a 30 nucleotide deletion in its 3’-untranslated region. Am. J. Trop. Med. Hyg. 65, 405–413 (2001).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 27.

    Durbin, A. P. et al. rDEN4delta30, a live attenuated dengue virus type 4 vaccine candidate, is safe, immunogenic, and highly infectious in healthy adult volunteers. J. Infect. Dis. 191, 710–718 (2005).

    PubMed 
    Article 

    Google Scholar 

  • 28.

    Kirkpatrick, B. D. et al. The live attenuated dengue vaccine TV003 elicits complete protection against dengue in a human challenge model. Sci. Transl. Med. 8, 33036 (2016).

    Article 
    CAS 

    Google Scholar 

  • 29.

    Osorio, J. E. et al. Safety and immunogenicity of a recombinant live attenuated tetravalent dengue vaccine (DENVax) in flavivirus-naive healthy adults in Colombia: A randomised, placebo-controlled, phase 1 study. Lancet. Infect. Dis. 14, 830–838 (2014).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 30.

    Sáez-Llorens, X. et al. Immunogenicity and safety of one versus two doses of tetravalent dengue vaccine in healthy children aged 2–17 years in Asia and Latin America: 18-month interim data from a phase 2, randomised, placebo-controlled study. Lancet. Infect. Dis 18, 162–170 (2018).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 31.

    Sáez-Llorens, X. et al. Safety and immunogenicity of one versus two doses of Takeda’s tetravalent dengue vaccine in children in Asia and Latin America: Interim results from a phase 2, randomised, placebo-controlled study. Lancet Infect. Dis. 17, 615–625 (2017).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 32.

    Jackson, L. A. et al. A phase 1 study of safety and immunogenicity following intradermal administration of a tetravalent dengue vaccine candidate. Vaccine 36, 3976–3983 (2018).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 33.

    Manoff, S. B. et al. Preclinical and clinical development of a dengue recombinant subunit vaccine. Vaccine 33, 7126–7134 (2015).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 34.

    Clements, D. E. et al. Development of a recombinant tetravalent dengue virus vaccine: Immunogenicity and efficacy studies in mice and monkeys. Vaccine 28, 2705–2715 (2018).

    Article 
    CAS 

    Google Scholar 

  • 35.

    Manoff, S. B. et al. Immunogenicity and safety of an investigational tetravalent recombinant subunit vaccine for dengue: Results of a Phase I randomized clinical trial in flavivirus-naive adults. Hum. Vaccines Immunother. 15, 2195–2204 (2019).

    Article 

    Google Scholar 

  • 36.

    Danko, J. R. et al. Safety and immunogenicity of a tetravalent dengue DNA vaccine administered with a cationic lipid-based adjuvant in a phase 1 clinical trial. Am. J. Trop. Med. Hyg. 98, 849 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 37.

    Schmidt, A. C. et al. Phase 1 randomized study of a tetravalent dengue purified inactivated vaccine in healthy adults in the United States. Am. J. Trop. Med. Hyg. 96, 1325 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 38.

    Thomas, S. J. et al. A phase II, randomized, safety and immunogenicity study of a re-derived, live-attenuated dengue virus vaccine in healthy adults. Am. J. Trop. Med. Hyg. 88, 73 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 39.

    Porter, K. R. et al. Immunogenicity and protective efficacy of a vaxfectin-adjuvanted tetravalent dengue DNA vaccine. Vaccine 30, 336–341 (2012).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 40.

    Osatomi, K. & Sumiyoshi, H. Complete nucleotide sequence of dengue type 3 virus genome RNA. Virology 176, 643–647 (1990).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 41.

    Wang, B. et al. Phylogenetic analysis of dengue virus reveals the high relatedness between imported and local strains during the 2013 dengue outbreak in Yunnan, China: A retrospective analysis. BMC Infect. Dis. 15, 1–7 (2015).

    Article 

    Google Scholar 

  • 42.

    Bäck, A. & Lundkvist, A. Dengue viruses: An overview. Infect. Ecol. Epidemiol. 3, 19839 (2013).

    Google Scholar 

  • 43.

    Cao, J. et al. Epidemiological and clinical characteristics of Dengue virus outbreaks in two regions of China, 2014–2015. PLoS ONE 14, e0213353 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 44.

    Fajardo-Sánchez, E., Galiano, V. & Villalaín, J. Molecular dynamics study of the membrane interaction of a membranotropic dengue virus C protein-derived peptide. J. Biomol. Struct. Dyn. 35, 1283–1294 (2017).

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 45.

    Tuiskunen Bäck, A. & Lundkvist, Å. Dengue viruses: An overview. Infect. Ecol. Epidemiol. 3, 19839 (2013).

    Google Scholar 

  • 46.

    Naz, A. et al. Identification of putative vaccine candidates against Helicobacter pylori exploiting exoproteome and secretome: A reverse vaccinology based approach. Infect. Genet. Evol. 32, 280–291 (2015).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 47.

    Ka, T. et al. A Candidate multi-epitope vaccine against SARS-CoV-2. Sci. Rep. 10, 10895 (2020).

    ADS 
    Article 
    CAS 

    Google Scholar 

  • 48.

    Ullah, A., Sarkar, B. & Islam, S. S. Exploiting the reverse vaccinology approach to design novel subunit vaccine against ebola virus. Immunobiology 8, 151949 (2020).

    Article 
    CAS 

    Google Scholar 

  • 49.

    Alam, A., Ali, S., Ahamad, S., Malik, M. Z. & Ishrat, R. From ZikV genome to vaccine: In silico approach for the epitope-based peptide vaccine against Zika virus envelope glycoprotein. Immunology 149, 386–399 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 50.

    Anwar, S., Mourosi, J. T., Khan, M. F. & Hosen, M. J. Prediction of epitope-based peptide vaccine against the chikungunya virus by immuno-informatics approach. Curr. Pharm. Biotechnol. 21, 325–340 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 51.

    Chong, L. C. & Khan, A. M. Vaccine Target Discovery. Encyclopedia of Bioinformatics and Computational Biology (Elsevier, 2019).

    Google Scholar 

  • 52.

    María, R., Arturo, C., Alicia, J. A., Paulina, M. & Gerardo, A. O. The Impact of Bioinformatics on Vaccine Design and Development (InTech, 2017).

    Book 

    Google Scholar 

  • 53.

    Ali, M. et al. Exploring dengue genome to construct a multi-epitope based subunit vaccine by utilizing immunoinformatics approach to battle against dengue infection. Sci. Rep. 7, 1–13 (2017).

    Article 
    CAS 

    Google Scholar 

  • 54.

    Chaplin, D. D. Overview of the immune response. J. Allergy Clin. Immunol. 125, S3–S23 (2010).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 55.

    Fadaka, A. O. et al. Inhibitory potential of repurposed drugs against the SARS-CoV-2 main protease: A computational-aided approach. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2020.1847197 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 56.

    Fadaka, A. O., Pretorius, A. & Klein, A. MicroRNA assisted gene regulation in colorectal cancer. Int. J. Mol. Sci. 20, 4899 (2019).

    CAS 
    PubMed Central 
    Article 
    PubMed 

    Google Scholar 

  • 57.

    Abedi Karjiban, R. et al. Molecular dynamics study of the structure, flexibility and dynamics of thermostable L1 lipase at high temperatures. Protein. J. 28, 14–23 (2009).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 58.

    Fadaka, A. O., Sibuyi, N. R. S., Madiehe, A. M. & Meyer, M. Computational insight of dexamethasone against potential targets of SARS-CoV-2. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2020.1819880 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 59.

    Jyotisha, S. S. & Qureshi, I. A. Multi-epitope vaccine against SARS-CoV-2 applying immunoinformatics and molecular dynamics simulation approaches. J. Biomol. Struct. Dyn. 1, 17. https://doi.org/10.1080/07391102.2020.1844060 (2020).

    CAS 
    Article 

    Google Scholar 

  • 60.

    Sarkar, B., Ullah, M. A., Johora, F. T., Taniya, M. A. & Araf, Y. Immunoinformatics-guided designing of epitope-based subunit vaccines against the SARS Coronavirus-2 (SARS-CoV-2). Immunobiology 225, 151955 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 61.

    Ghaebi, M., Osali, A., Valizadeh, H., Roshangar, L. & Ahmadi, M. Vaccine development and therapeutic design for 2019-nCoV/SARS-CoV-2: Challenges and chances. J. Cell. Physiol. 235, 9098–9109 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 62.

    Dong, R., Chu, Z., Yu, F. & Zha, Y. Contriving Multi-Epitope Subunit of Vaccine for COVID-19: Immunoinformatics Approaches. Front. Immunol. 11, 1784 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 63.

    Lim, H. X., Lim, J., Jazayeri, S. D., Poppema, S. & Poh, C. L. Development of multi-epitope peptide-based vaccines against SARS-CoV-2. Biomed. J. 44, 18–30 (2020).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 64.

    Rahman, N. et al. Vaccine design from the ensemble of surface glycoprotein epitopes of SARS-CoV-2: An immunoinformatics approach. Vaccines. 8, 423 (2020).

    CAS 
    PubMed Central 
    Article 
    PubMed 

    Google Scholar 

  • 65.

    Kar, P. P. & Srivastava, A. Immuno-informatics analysis to identify novel vaccine candidates and design of a multi-epitope based vaccine candidate against theileria parasites. Front. Immunol. 9, 2213 (2018).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 66.

    Zawawi, A. et al. In silico design of a T-cell epitope vaccine candidate for parasitic helminth infection. PLoS Pathog. 16, e1008243 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 67.

    Tripathi, N. K. & Shrivastava, A. Recent developments in recombinant protein–based dengue vaccines. Front. Immunol. 2018, 1919 (2018).

    Article 
    CAS 

    Google Scholar 

  • 68.

    Thomas, S. J. & Rothman, A. L. Trials and tribulations on the path to developing a dengue vaccine. Vaccine 33, D24–D31 (2015).

    PubMed 
    Article 

    Google Scholar 

  • 69.

    Halstead, S. B. Antibody, macrophages, dengue virus infection, shock, and hemorrhage: A pathogenetic cascade. Rev. Infect. Dis. 11, S830–S839 (1989).

    PubMed 
    Article 

    Google Scholar 

  • 70.

    Thomas, S. J. Preventing dengue: Is the possibility now a reality?. N. Engl. J. Med. 372, 172–173 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 71.

    Naz, K. et al. PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome. BMC Bioinform. 20, 123 (2019).

    Article 

    Google Scholar 

  • 72.

    Kumar Jaiswal, A. et al. An in silico identification of common putative vaccine candidates against Treponema pallidum: A reverse vaccinology and subtractive genomics based approach. Int. J. Mol. Sci. 18, 402 (2017).

    PubMed Central 
    Article 
    CAS 
    PubMed 

    Google Scholar 

  • 73.

    Kar, T. et al. A candidate multi-epitope vaccine against SARS-CoV-2. Sci. Rep. 10, 10895 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 74.

    Sauer, K. & Harris, T. An effective COVID-19 vaccine needs to engage T cells. Front. Immunol. 11, 581807 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 75.

    Yadav, S. et al. In silico and in vitro studies on the protein-protein interactions between Brugia malayi immunomodulatory protein calreticulin and human C1q. PLoS ONE 9, e106413 (2014).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 76.

    Aathmanathan, V. S., Jothi, N., Prajapati, V. K. & Krishnan, M. Investigation of immunogenic properties of Hemolin from silkworm, Bombyx mori as carrier protein: an immunoinformatic approach. Sci. Rep. 8, 1–10 (2018).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 77.

    Droppa-Almeida, D., Franceschi, E. & Padilha, F. F. Immune-informatic analysis and design of peptide vaccine from multi-epitopes against Corynebacterium pseudotuberculosis. Bioinform. Biol. Insights 12, 1177932218755337 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 78.

    Rekik, I. et al. In silico characterization and Molecular modeling of double-strand break repair protein MRE11 from Phoenix dactylifera v deglet nour. Theor. Biol. Med. Model. 12, 1–14 (2015).

    Article 
    CAS 

    Google Scholar 

  • 79.

    Hashemzadeh, P., Ghorbanzadeh, V., Lashgarian, H. E., Kheirandish, F. & Dariushnejad, H. Harnessing bioinformatic approaches to design novel multi-epitope subunit vaccine against Leishmania infantum. Int. J. Pept. Res. Ther. 26, 1417–1428 (2020).

    CAS 
    Article 

    Google Scholar 

  • 80.

    Vijay, K. Toll-like receptors in immunity and inflammatory diseases: Past, present, and future. Int. Immunopharmacol. 59, 391–412 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 81.

    Ahmad, S. et al. Design of a novel multi epitope-based vaccine for pandemic coronavirus disease (COVID-19) by vaccinomics and probable prevention strategy against avenging zoonotics. Eur. J. Pharm. Sci. 151, 105387 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 82.

    Pfarr, K. M., Fischer, K. & Hoerauf, A. Involvement of Toll-like receptor 4 in the embryogenesis of the rodent filaria Litomosoides sigmodontis. Med. Microbiol. Immunol. 192, 53–56 (2003).

    PubMed 
    Article 

    Google Scholar 

  • 83.

    Kerepesi, L. A., Leon, O., Lustigman, S. & Abraham, D. Protective immunity to the larval stages of Onchocerca volvulus is dependent on Toll-like receptor 4. Infect. Immun. 73, 8291–8297 (2005).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 84.

    Compton, T. et al. Human cytomegalovirus activates inflammatory cytokine responses via CD14 and Toll-like receptor 2. J. Virol. 77, 4588–4596 (2003).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 85.

    Marín, A. et al. Relationship between G+ C content, ORF-length and mRNA concentration in Saccharomyces cerevisiae. Yeast 20, 703–711 (2003).

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • 86.

    Rapin, N., Lund, O., Bernaschi, M. & Castiglione, F. Computational immunology meets bioinformatics: The use of prediction tools for molecular binding in the simulation of the immune system. PLoS ONE 5, e9862 (2010).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 87.

    Devi, A. & Chaitanya, N. S. In silico designing of multi-epitope vaccine construct against human coronavirus infections. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2020.1804460 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 88.

    Ismail, S., Ahmad, S. & Azam, S. S. Vaccinomics to design a novel single chimeric subunit vaccine for broad-spectrum immunological applications targeting nosocomial Enterobacteriaceae pathogens. Eur. J. Pharm. Sci. 146, 105258 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 89.

    Tahir ul Qamar, M. et al. Multiepitope-based subunit vaccine design and evaluation against respiratory syncytial virus using reverse vaccinology approach. Vaccines 8, 288 (2020).

    PubMed Central 
    Article 
    CAS 
    PubMed 

    Google Scholar 

  • 90.

    Khan, A. et al. Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches. PLoS ONE 13, e0196484 (2018).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 91.

    Banisharif-Dehkordi, F., Mobini-Dehkordi, M., Shakhsi-Niaei, M. & Mahnam, K. Design and molecular dynamic simulation of a new double-epitope tolerogenic protein as a potential vaccine for multiple sclerosis disease. Res. Pharm. Sci. 14, 20–26 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 92.

    Nielsen, H. Predicting Secretory Proteins with SignalP 59–73 (Springer, 2017).

    Google Scholar 

  • 93.

    Petersen, T. N., Brunak, S., Von Heijne, G. & Nielsen, H. SignalP 4.0: Discriminating signal peptides from transmembrane regions. Nat. Methods 8, 785–786 (2011).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 94.

    Almagro Armenteros, J. J., Sønderby, C. K., Sønderby, S. K., Nielsen, H. & Winther, O. DeepLoc: Prediction of protein subcellular localization using deep learning. Bioinformatics 33, 3387–3395 (2017).

    PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 

  • 95.

    Doytchinova, I. A. & Flower, D. R. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines. BMC Bioinform. 8, 4 (2007).

    Article 
    CAS 

    Google Scholar 

  • 96.

    Westerhout, J. et al. Allergenicity prediction of novel and modified proteins: Not a mission impossible! Development of a random forest allergenicity prediction model. Regul. Toxicol. Pharmacol. 107, 104422 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 97.

    Dimitrov, I., Flower, D. R. & Doytchinova, I. AllerTOP: A server for in silico prediction of allergens. BMC Bioinform. 14, 1–9 (2013).

    Article 

    Google Scholar 

  • 98.

    Venkatarajan, M. S. & Braun, W. New quantitative descriptors of amino acids based on multidimensional scaling of a large number of physical–chemical properties. Mol. Model. Annu. 7, 445–453 (2001).

    CAS 
    Article 

    Google Scholar 

  • 99.

    Faria, A. R. et al. High-throughput analysis of synthetic peptides for the immunodiagnosis of canine visceral leishmaniasis. PLoS Negl. Trop. Dis. 5, e1310 (2011).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 100.

    Beaver, J. E., Bourne, P. E. & Ponomarenko, J. V. EpitopeViewer: a Java application for the visualization and analysis of immune epitopes in the Immune Epitope Database and Analysis Resource (IEDB). Immunome Res. 3, 3 (2007).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 101.

    Shey, R. A. et al. In-silico design of a multi-epitope vaccine candidate against onchocerciasis and related filarial diseases. Sci. Rep. 9, 1–18 (2019).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 102.

    Möller, S., Croning, M. D. & Apweiler, R. Evaluation of methods for the prediction of membrane spanning regions. Bioinformatics 17, 646–653 (2001).

    PubMed 
    Article 

    Google Scholar 

  • 103.

    Walker, J. M. The Proteomics Protocols Handbook (Springer, 2005).

    Book 

    Google Scholar 

  • 104.

    Gasteiger, E. et al. Protein Identification and Analysis Tools on the ExPASy Server 571–607 (Springer, 2005).

    Google Scholar 

  • 105.

    Hebditch, M., Carballo-Amador, M. A., Charonis, S., Curtis, R. & Warwicker, J. Protein–Sol: A web tool for predicting protein solubility from sequence. Bioinformatics 33, 3098–3100 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 106.

    Buchan, D. W., Minneci, F., Nugent, T. C., Bryson, K. & Jones, D. T. Scalable web services for the PSIPRED Protein Analysis Workbench. Nucleic Acids Res. 41, W349–W357 (2013).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 107.

    Saha, R. & Prasad, B. V. In silico approach for designing of a multi-epitope based vaccine against novel Coronavirus (SARS-COV-2). bioRxiv https://doi.org/10.1101/2020.03.31.017459 (2020).

    Article 

    Google Scholar 

  • 108.

    Wiederstein, M. & Sippl, M. J. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 35, W407–W410 (2007).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 109.

    Lovell, S. C. et al. Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins 50, 437–450 (2003).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 110.

    Ullah, M. A., Sarkar, B. & Islam, S. S. Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus. Immunobiology 225, 151949 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 111.

    Fadaka, A. O., Sibuyi, N. R. S., Madiehe, A. M. & Meyer, M. MicroRNA-based regulation of Aurora a kinase in breast cancer. Oncotarget 11, 4306 (2020).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 112.

    Ojo, O. A. et al. Deciphering the interaction of puerarin with cancer macromolecules: An in silico investigation. J. Biomol. Struct. Dyn. https://doi.org/10.1080/07391102.2020.1819425 (2020).

    Article 
    PubMed 

    Google Scholar 

  • 113.

    Grote, A. et al. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic Acids Res. 33, W526–W531 (2005).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 114.

    Morla, S., Makhija, A. & Kumar, S. Synonymous codon usage pattern in glycoprotein gene of rabies virus. Gene 584, 1–6 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 115.

    Castiglione, F., Mantile, F., De Berardinis, P. & Prisco, A. How the interval between prime and boost injection affects the immune response in a computational model of the immune system. Comput. Math. Methods Med. 2012, 1–9 (2012).

    Article 

    Google Scholar 

  • 116.

    Kroger, A. General Recommendations on Immunization; US Department of Health and Human Services (Public Health Servic, Centers for Disease Control, 2013).

    Google Scholar 

  • 117.

    Nain, Z., Karim, M. M., Sen, M. K. & Adhikari, U. K. Structural basis and designing of peptide vaccine using PE-PGRS family protein of Mycobacterium ulcerans: An integrated vaccinomics approach. Mol. Immunol. 120, 146–163 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 118.

    Chauhan, V. & Singh, M. P. Immuno-informatics approach to design a multi-epitope vaccine to combat cytomegalovirus infection. Eur. J. Pharm. Sci. 147, 105279 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 119.

    Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 120.

    Blessy, J. J. & Sharmila, D. J. S. Molecular simulation of N-acetylneuraminic acid analogs and molecular dynamics studies of cholera toxin-Neu5Gc complex. J. Biomol. Struct. Dyn. 33, 1126–1139 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 121.

    Hoover, W. G. Canonical dynamics: Equilibrium phase-space distributions. Phys. Rev. A 31, 1695 (1985).

    ADS 
    CAS 
    Article 

    Google Scholar 

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