• Logo
  • HamaraJournals

Vaccine Design, Adaptation, and Cloning Design for Multiple Epitope-Based Vaccine Derived From SARS-CoV-2 Surface Glycoprotein (S), Membrane Protein (M) and Envelope Protein (E): In silico approach

Peter T. Habib
36

Views


Abstract

Introduction: The SARS Coronavirus-2 (SARS-CoV-2) pandemic has become a global epidemic that has increased the scientific community's concern about developing and finding a counteraction against this lethal virus. So far, hundreds of thousands of people have been infected by the pandemic due to contamination and spread. This research was therefore carried out to develop potential epitope-based vaccines against the SARS-CoV-2 virus using reverse vaccinology and immunoinformatics approaches.

Material and Methods: The material of SARS-COV2 Surface Glycoprotein (S), Membrane Protein (M), and Envelope Protein (E) were downloaded from the NCBI protein database. Each protein has undergone epitopes prediction for MHC class I epitopes, MHC class II epitopes, and Antibody of B-cell epitopes. Selected epitopes according to their antigenicity score was tested for allergenicity and toxicity. Finally, filtered epitopes were used in vaccine construction. Vaccines were constructed, docked against Toll-like receptor 3, and undergone Molecular Dynamic simulation. The vaccine with the best scores, subjected to immune stimulation and cloning design.

Results: Three vaccines were constructed, COVac-1, COVac-2, and COVac-3. Each vaccine was submitted into a deep investigation. The molecular dynamic simulation determines the stability and physical movement of protein atoms and molecules. After Molecular dynamics simulation, COVac-1 was having the best scores. COVac-1 was then subjected to immune simulation analysis to insure the stimulation of innate and adaptive immunity. After passing the immune simulation, COVac-1 was integrated into E.coli pET-30b plasmid using in silico cloning design.

Conclusion:Viral pandemics are threatened to face humanity today. The best scenario to fight against any pandemic is utilizing the full power of computational biology, especially immune-informatics, to design and discover in silico new vaccines or molecules that may stimulate the immune system against the invader pathogens or inhibit the pathogen life cycle.


References

Su S, Wong G, Shi W, Liu J, Lai ACK, Zhou J, et al. Epidemiology, genetic recombination, and pathogenesis of coronaviruses. Trends Microbiol. 2016; 24(6): 490-502. PMID: 27012512 DOI: 10.1016/j.tim.2016.03.003

Weiss SR, Navas-Martin S. Coronavirus pathogenesis and the emerging pathogen severe acute respiratory syndrome coronavirus. Microbiol Mol Biol Rev. 2005; 69(4): 635-64. PMID: 16339739 DOI: 10.1128/MMBR.69.4.635-664.2005

Masters PS, Perlman S. Coronaviridae. In: Fields B, Knipe DM, Howley PM. Fields virology. 6th ed. Lippincott Williams & Wilkins; 2013.

van der Hoek L, Pyrc K, Jebbink MF, Vermeulen-Oost W, Berkhout RJM, Wolthers KC, et al. Identification of a new human coronavirus. Nat Med. 2004; 10(4): 368-73. PMID: 15034574 DOI: 10.1038/nm1024

Hamre D, Procknow JJ. A new virus isolated from the human respiratory tract. Proc Soc Exp Biol Med. 1966; 121(1): 190-3. PMID: 4285768 DOI: 10.3181/00379727-121-30734

Drosten C, Günther S, Preiser W, van der Werf S, Brodt H-R, Becker S, et al. Identification of a novel coronavirus in patients with severe acute respiratory syndrome. N Engl J Med. 2003; 348(20): 1967-76. PMID: 12690091 DOI: 10.1056/NEJMoa030747

Zaki AM, van Boheemen S, Bestebroer TM, Osterhaus ADME, Fouchier RAM. Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. N Engl J Med. 2012; 367(19): 1814-20. PMID: 23075143 DOI: 10.1056/NEJMoa1211721

Peeri NC, Shrestha N, Rahman MS, Zaki R, Tan Z, Bibi S, et al. The SARS, MERS and novel coronavirus (COVID-19) epidemics, the newest and biggest global health threats: What lessons have we learned? Int J Epidemiol. 2020; 49(3): 717-26. PMID: 32086938 DOI: 10.1093/ije/dyaa033

Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet. 2020; 395(10223): 470-3. PMID: 31986257 DOI: 10.1016/S0140-6736(20)30185-9

Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395(10223): 497-506. PMID: 31986264 DOI: 10.1016/S0140-6736(20)30183-5

Habib PT, Saber-Ayad M, Hassanein SE. In silico analysis of 716 natural bioactive molecules form atlantic ocean reveals candidate molecule to inhibit spike protein. Research Square. 2021; Preprint.

Randhawa GS, Soltysiak MPM, el Roz H, de Souza CPE, Hill KA, Kari L. Machine learning using intrinsic genomic signatures for rapid classification of novel pathogens: COVID-19 case study. PLoS One. 2020; 15(4): e0232391. PMID: 32330208 DOI: 10.1371/journal.pone.0232391

Habib PT. COVATOR: A software for chimeric coronavirus identification. bioRxiv. 2020; Preprint.

Fehr AR, Perlman S. Coronaviruses: An overview of their replication and pathogenesis. Methods Mol Biol. 2015; 1282: 1-23. PMID: 25720466 DOI: 10.1007/978-1-4939-2438-7_1

Petit CM, Melancon JM, Chouljenko VN, Colgrove R, Farzan M, Knipe DM, et al. Genetic analysis of the SARS-coronavirus spike glycoprotein functional domains involved in cell-surface expression and cell-to-cell fusion. Virology. 2005; 341(2): 215-30. PMID: 16099010 DOI: 10.1016/j.virol.2005.06.046

Cavanagh D. The coronavirus surface glycoprotein. In: Siddell SG (eds). The coronaviridae. Springer; 1995.

Schoeman D, Fielding BC. Coronavirus envelope protein: Current knowledge. Virol J. 2019; 16(1): 1-22. PMID: 31133031 DOI: 10.1186/s12985-019-1182-0

Rottier PJM. The coronavirus membrane glycoprotein. In: Siddell SG (eds). The coronaviridae. Springer; 1995.

Chong LC, Khan AM. Vaccine target discovery. In: Ranganathan S, Nakai K, Schonbach C (eds). Encyclopedia of bioinformatics and computational biology. Elsevier; 2019.

Mar’ia RR, Arturo CJ, Alicia J-A, Paulina MG, Gerardo A-O. The impact of bioinformatics on vaccine design and development. In: Afrin F (eds). Vaccine. INTECH; 2017.

Ullah MA, Sarkar B, Islam SS. Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus. Immunobiology. 2020; 225(3): 151949. PMID: 32444135 DOI: 10.1016/j.imbio.2020.151949

Vita R, Mahajan S, Overton JA, Dhanda SK, Martini S, Cantrell JR, et al. The immune epitope database (IEDB): 2018 update. Nucleic Acids Res. 2019; 47(D1): D339-43. PMID: 30357391 DOI: 10.1093/nar/gky1006

Wu C-Y, Monie A, Pang X, Hung C-F, Wu TC. Improving therapeutic HPV peptide-based vaccine potency by enhancing CD4+ T help and dendritic cell activation. J Biomed Sci. 2010; 17(1): 1-10. PMID: 21092195 DOI: 10.1186/1423-0127-17-88

Källberg M, Wang H, Wang S, Peng J, Wang Z, Lu H, et al. Template-based protein structure modeling using the RaptorX web server. Nat Protoc. 2012; 7(8): 1511-22. PMID: 22814390 DOI: 10.1038/nprot.2012.085

Sateesh P, Rao A, Sangeeta SK, Babu MN, Grandhi RS. Homology modeling and sequence analysis of anxC3. International Journal of Engineering Science and Technology. 2010; 2(5): 1125-30.

Laskowski RA, MacArthur MW, Moss DS, Thornton JM. PROCHECK: A program to check the stereochemical quality of protein structures. Journal of Appllied Crystallography. 1993; 26(2): 283-91.

Zobayer M, Aowald Hossain ABM. In silico characterization and homology modeling of histamine receptors. Journal of Biological Sciences. 2018; 18(4): 178-91.

Craig DB, Dombkowski AA. Disulfide by design 2.0: A web-based tool for disulfide engineering in proteins. BMC Bioinformatics. 2013; 14: 1-7. PMID: 24289175 DOI: 10.1186/1471-2105-14-346

Chauhan V, Rungta T, Goyal K, Singh MP. Designing a multi-epitope based vaccine to combat Kaposi Sarcoma utilizing immunoinformatics approach. Sci Rep. 2019; 9(1): 2517. PMID: 30792446 DOI: 10.1038/s41598-019-39299-8

López-Blanco JR, Aliaga JI, Quintana-Ort’i ES, Chacón P. iMODS: Internal coordinates normal mode analysis server. Nucleic Acids Res. 2014; 42(Web Server issue): W271-6. PMID: 24771341 DOI: 10.1093/nar/gku339

Solanki V, Tiwari V. Subtractive proteomics to identify novel drug targets and reverse vaccinology for the development of chimeric vaccine against Acinetobacter baumannii. Sci Rep. 2018; 8(1): 9044. PMID: 29899345 DOI: 10.1038/s41598-018-26689-7

Demkowicz WE, Maa JS, Esteban M. Identification and characterization of vaccinia virus genes encoding proteins that are highly antigenic in animals and are immunodominant in vaccinated humans. J Virol. 1992; 66(1): 386-98. PMID: 1727494 DOI: 10.1128/JVI.66.1.386-398.1992




DOI: http://dx.doi.org/10.30699/fhi.v10i1.279

Refbacks

  • There are currently no refbacks.