Tailoring potential antigenic regions on pandemic SARS spike protein

Author affiliations

Authors

  • Le Thanh Hoa \(^1\) School of Biotechnology, International University, Ho Chi Minh City, Vietnam.
    \(^3\) Vietnam National University, Ho Chi Minh City, Vietnam.
    https://orcid.org/0000-0003-1429-2414
  • Le Nhat Thong \(^2\) Research Center for Infectious Diseases, International University, Ho Chi Minh City, Vietnam.
    \(^3\) Vietnam National University, Ho Chi Minh City, Vietnam.
    https://orcid.org/0000-0001-9416-6068
  • Le Minh Thong \(^1\) School of Biotechnology, International University, Ho Chi Minh City, Vietnam.
    \(^3\) Vietnam National University, Ho Chi Minh City, Vietnam.

DOI:

https://doi.org/10.15625/vjbt-21493

Keywords:

ACE2, antibody, HLA, reverse vaccinology, SARS-CoV-2, spike protein

Abstract

Coronavirus-associated severe acute respiratory syndrome (SARS) pandemics have devastated lives, economies, and societies worldwide. Given the higher severity of the latter pandemic, the constant mutation, and vaccine escape, new and more dangerous pandemics could emerge. Therefore, it is imperative to identify conserved vaccine candidates for stable effectiveness in future pandemics. This study aimed to tailor potential, conserved peptide-based vaccine candidates for the upcoming Coronavirus pandemic based on the sequences of the spike protein of SARS-CoV-1 and SARS-CoV-2 viruses, using bioinformatic approaches. Peptide-based CD4+ T-cell epitopes derived from SARS proteomes were identified based on their predicted binding affinity to HLA-DRB1, one of the central molecules for the adaptive immune system. These epitopes were then assessed for conservation by sequence analysis of all pandemic-involved strains and variants. The epitopes were then evaluated and cross-checked for possible protection against the causative pathogens via potential uptake by B-cell receptors, the sustenance of sequence conservation for the future pandemic strain using data from population HLA-allele-typing studies, structural analysis of the spike-antibody complex and their contribution to the function of spike protein, respectively. As a result, selected vaccine candidates were projected to cover nearly 90% of the world's population with the combination of just four epitopes. The epitopes could be modified to adapt to future pandemic strains, improve antigenicity, or be used as booster immunization against the currently circulating SARS-CoV-2 variant. This study demonstrates that there is still room for improvement and promising discoveries in vaccine design to deter upcoming SARS pandemics.

Downloads

Download data is not yet available.

References

Abbas AK, Lichtman AH, Pillai S (2014) Cellular and Molecular Immunology, 8th Edition. Elsevier Health Sciences.

Andrzejczak-Grządko S, Czudy Z, Donderska M (2021) Side effects after COVID-19 vaccinations among residents of Poland. European review for medical and pharmacological sciences 25: 4418–4421. https://doi.org/10.26355/eurrev_202106_26153

Arrieta-Bolaños E, Hernández-Zaragoza DI, Barquera R (2023) An HLA map of the world: A comparison of HLA frequencies in 200 worldwide populations reveals diverse patterns for class I and class II. Front Genet 14: 866407. https://doi.org/10.3389/fgene.2023.866407 DOI: https://doi.org/10.3389/fgene.2023.866407

Åsjö B, Stavang H, Sørensen B, Baksaas I, Nyhus J, Langeland N (2002) Phase I Trial of a Therapeutic HIV Type 1 Vaccine, Vacc-4x, in HIV Type 1-Infected Individuals with or without Antiretroviral Therapy. AIDS Research and Human Retroviruses 18(18): 1357–1365. https://doi.org/10.1089/088922202320935438 DOI: https://doi.org/10.1089/088922202320935438

Astbury S, Reynolds CJ, Butler DK, Muñoz-Sandoval DC, Lin K-M, Pieper FP, Otter A, Kouraki A, Cusin L, Nightingale J, Vijay A, Craxford S, Aithal GP, Tighe PJ, Gibbons JM, Pade C, Joy G, Maini M, Chain B, Semper A, Brooks T, Ollivere BJ, McKnight Á, Noursadeghi M, Treibel TA, Manisty C, Moon JC, Investigators* Covid, Valdes AM, Boyton RJ, Altmann DM (2022) HLA-DR polymorphism in SARS-CoV-2 infection and susceptibility to symptomatic COVID-19. Immunology 166(1): 68–77. https://doi.org/10.1111/imm.13450 DOI: https://doi.org/10.1111/imm.13450

Bassani-Sternberg M, Gfeller D (2016) Unsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide–HLA Interactions. The Journal of Immunology 197(6): 2492–2499. https://doi.org/10.4049/jimmunol.1600808 DOI: https://doi.org/10.4049/jimmunol.1600808

Behloul N, Baha S, Shi R, Meng J (2020) Role of the GTNGTKR motif in the N-terminal receptor-binding domain of the SARS-CoV-2 spike protein. Virus Research 286: 198058. https://doi.org/10.1016/j.virusres.2020.198058 DOI: https://doi.org/10.1016/j.virusres.2020.198058

Bò L, Miotto M, Di Rienzo L, Milanetti E, Ruocco G (2021) Exploring the Association Between Sialic Acid and SARS-CoV-2 Spike Protein Through a Molecular Dynamics-Based Approach. Front Med Technol 2: 614652. https://doi.org/10.3389/fmedt.2020.614652 DOI: https://doi.org/10.3389/fmedt.2020.614652

Bui H-H, Sidney J, Dinh K, Southwood S, Newman MJ, Sette A (2006) Predicting population coverage of T-cell epitope-based diagnostics and vaccines. BMC Bioinformatics 7(1): 153. https://doi.org/10.1186/1471-2105-7-153 DOI: https://doi.org/10.1186/1471-2105-7-153

Chen J, Wang R, Wang M, Wei G-W (2020) Mutations Strengthened SARS-CoV-2 Infectivity. Journal of Molecular Biology 432(19): 5212–5226. https://doi.org/10.1016/j.jmb.2020.07.009 DOI: https://doi.org/10.1016/j.jmb.2020.07.009

Chen Z, Boon SS, Wang MH, Chan RWY, Chan PKS (2021) Genomic and evolutionary comparison between SARS-CoV-2 and other human coronaviruses. Journal of Virological Methods 289: 114032. https://doi.org/10.1016/j.jviromet.2020.114032 DOI: https://doi.org/10.1016/j.jviromet.2020.114032

Clausen TM, Sandoval DR, Spliid CB, Pihl J, Perrett HR, Painter CD, Narayanan A, Majowicz SA, Kwong EM, McVicar RN, Thacker BE, Glass CA, Yang Z, Torres JL, Golden GJ, Bartels PL, Porell RN, Garretson AF, Laubach L, Feldman J, Yin X, Pu Y, Hauser BM, Caradonna TM, Kellman BP, Martino C, Gordts PLSM, Chanda SK, Schmidt AG, Godula K, Leibel SL, Jose J, Corbett KD, Ward AB, Carlin AF, Esko JD (2020) SARS-CoV-2 Infection Depends on Cellular Heparan Sulfate and ACE2. Cell 183(4): 1043-1057.e15. https://doi.org/10.1016/j.cell.2020.09.033 DOI: https://doi.org/10.1016/j.cell.2020.09.033

Dar HA, Waheed Y, Najmi MH, Ismail S, Hetta HF, Ali A, Muhammad K (2020) Multiepitope Subunit Vaccine Design against COVID-19 Based on the Spike Protein of SARS-CoV-2: An In Silico Analysis. Journal of Immunology Research 2020(1): 8893483. https://doi.org/10.1155/2020/8893483 DOI: https://doi.org/10.1155/2020/8893483

Elliott SL, Suhrbier A, Miles JJ, Lawrence G, Pye SJ, Le TT, Rosenstengel A, Nguyen T, Allworth A, Burrows SR, Cox J, Pye D, Moss DJ, Bharadwaj M (2008) Phase I Trial of a CD8+ T-Cell Peptide Epitope-Based Vaccine for Infectious Mononucleosis. Journal of Virology 82(3): 1448–1457. https://doi.org/10.1128/jvi.01409-07 DOI: https://doi.org/10.1128/JVI.01409-07

Eyre-Walker A, Keightley PD (2007) The distribution of fitness effects of new mutations. Nat Rev Genet 8(8): 610–618. https://doi.org/10.1038/nrg2146 DOI: https://doi.org/10.1038/nrg2146

Gahery H, Daniel N, Charmeteau B, Ourth L, Jackson A, Andrieu M, Choppin J, Salmon D, Pialoux G, Guillet J-G (2006) New CD4+ and CD8+ T Cell Responses Induced in Chronically HIV Type-1-Infected Patients After Immunizations with an HIV Type 1 Lipopeptide Vaccine. AIDS Research and Human Retroviruses 22(7): 684–694. https://doi.org/10.1089/aid.2006.22.684 DOI: https://doi.org/10.1089/aid.2006.22.684

Gonzalez-Galarza FF, McCabe A, Santos EJM dos, Jones J, Takeshita L, Ortega-Rivera ND, Cid-Pavon GMD, Ramsbottom K, Ghattaoraya G, Alfirevic A, Middleton D, Jones AR (2020) Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools. Nucleic Acids Research 48(D1): D783–D788. https://doi.org/10.1093/nar/gkz1029 DOI: https://doi.org/10.1093/nar/gkz1029

Harvey WT, Carabelli AM, Jackson B, Gupta RK, Thomson EC, Harrison EM, Ludden C, Reeve R, Rambaut A, Peacock SJ, Robertson DL (2021) SARS-CoV-2 variants, spike mutations and immune escape. Nat Rev Microbiol 19(7): 409–424. https://doi.org/10.1038/s41579-021-00573-0 DOI: https://doi.org/10.1038/s41579-021-00573-0

Huang Y, Yang C, Xu X, Xu W, Liu S (2020) Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19. Acta Pharmacol Sin 41(9): 1141–1149. https://doi.org/10.1038/s41401-020-0485-4 DOI: https://doi.org/10.1038/s41401-020-0485-4

Hunter JD (2007) Matplotlib: A 2D Graphics Environment. Computing in Science & Engineering 9(03): 90–95. https://doi.org/10.1109/MCSE.2007.55 DOI: https://doi.org/10.1109/MCSE.2007.55

Hutchinson EG, Sessions RB, Thornton JM, Woolfson DN (1998) Determinants of strand register in antiparallel β-sheets of proteins. Protein Science 7(11): 2287–2300. https://doi.org/10.1002/pro.5560071106 DOI: https://doi.org/10.1002/pro.5560071106

Janeway CA Jr, Travers P, Walport M, Shlomchik MJ (2001) B-cell activation by armed helper T cells. In Immunobiology: The Immune System in Health and Disease. 5th Edition. Garland Science

Jones DT, Taylor WR, Thornton JM (1992) The rapid generation of mutation data matrices from protein sequences. Bioinformatics 8(3): 275–282. https://doi.org/10.1093/bioinformatics/8.3.275 DOI: https://doi.org/10.1093/bioinformatics/8.3.275

Jubb HC, Higueruelo AP, Ochoa-Montaño B, Pitt WR, Ascher DB, Blundell TL (2017) Arpeggio: A Web Server for Calculating and Visualising Interatomic Interactions in Protein Structures. Journal of Molecular Biology 429(3): 365–371. https://doi.org/10.1016/j.jmb.2016.12.004 DOI: https://doi.org/10.1016/j.jmb.2016.12.004

Khare S, Gurry C, Freitas L, Schultz MB, Bach G, Diallo A, Akite N, Ho J, Lee RT, Yeo W, Curation Team GC, Maurer-Stroh S (2021) GISAID’s Role in Pandemic Response. China CDC Wkly 3(49): 1049–1051. https://doi.org/10.46234/ccdcw2021.255 DOI: https://doi.org/10.46234/ccdcw2021.255

Kran A-MB, Sørensen B, Nyhus J, Sommerfelt MA, Baksaas I, Bruun JN, Kvale D (2004) HLA- and dose-dependent immunogenicity of a peptide-based HIV-1 immunotherapy candidate (Vacc-4x). AIDS 18(14): 1875–1883. https://doi.org/10.1097/00002030-200409240-00003 DOI: https://doi.org/10.1097/00002030-200409240-00003

Langton DJ, Bourke SC, Lie BA, Reiff G, Natu S, Darlay R, Burn J, Echevarria C (2021) The influence of HLA genotype on the severity of COVID-19 infection. HLA 98(1): 14–22. https://doi.org/10.1111/tan.14284 DOI: https://doi.org/10.1111/tan.14284

Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG (2007) Clustal W and Clustal X version 2.0. Bioinformatics 23(21): 2947–2948. https://doi.org/10.1093/bioinformatics/btm404 DOI: https://doi.org/10.1093/bioinformatics/btm404

Lazarevic I, Pravica V, Miljanovic D, Cupic M (2021) Immune Evasion of SARS-CoV-2 Emerging Variants: What Have We Learnt So Far? Viruses 13(7): 1192. https://doi.org/10.3390/v13071192 DOI: https://doi.org/10.3390/v13071192

Lehmann C, Loeffler-Wirth H, Balz V, Enczmann J, Landgraf R, Lakowa N, Gruenewald T, Fischer JC, Doxiadis I (2023) Immunogenetic Predisposition to SARS-CoV-2 Infection. Biology 12(1): 37. https://doi.org/10.3390/biology12010037 DOI: https://doi.org/10.3390/biology12010037

Li B, Wang L, Ge H, Zhang X, Ren P, Guo Y, Chen W, Li J, Zhu W, Chen W, Zhu L, Bai F (2021) Identification of Potential Binding Sites of Sialic Acids on the RBD Domain of SARS-CoV-2 Spike Protein. Front Chem 9: 659764. https://doi.org/10.3389/fchem.2021.659764 DOI: https://doi.org/10.3389/fchem.2021.659764

Li F (2016) Structure, Function, and Evolution of Coronavirus Spike Proteins. Annual Review of Virology 3(Volume 3, 2016): 237–261. https://doi.org/10.1146/annurev-virology-110615-042301 DOI: https://doi.org/10.1146/annurev-virology-110615-042301

Li H, Liu L, Zhang D, Xu J, Dai H, Tang N, Su X, Cao B (2020) SARS-CoV-2 and viral sepsis: observations and hypotheses. The Lancet 395(10235): 1517–1520. https://doi.org/10.1016/S0140-6736(20)30920-X DOI: https://doi.org/10.1016/S0140-6736(20)30920-X

Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22(13): 1658–1659. https://doi.org/10.1093/bioinformatics/btl158 DOI: https://doi.org/10.1093/bioinformatics/btl158

Littera R, Campagna M, Deidda S, Angioni G, Cipri S, Melis M, Firinu D, Santus S, Lai A, Porcella R, Lai S, Rassu S, Scioscia R, Meloni F, Schirru D, Cordeddu W, Kowalik MA, Serra M, Ragatzu P, Carta MG, Del Giacco S, Restivo A, Deidda S, Orrù S, Palimodde A, Perra R, Orrù G, Conti M, Balestrieri C, Serra G, Onali S, Marongiu F, Perra A, Chessa L (2020) Human Leukocyte Antigen Complex and Other Immunogenetic and Clinical Factors Influence Susceptibility or Protection to SARS-CoV-2 Infection and Severity of the Disease Course. The Sardinian Experience. Front. Immunol. 11 https://doi.org/10.3389/fimmu.2020.605688 DOI: https://doi.org/10.3389/fimmu.2020.605688

Meo SA, Bukhari IA, Akram J, Meo AS, Klonoff DC (2021) COVID-19 vaccines: comparison of biological, pharmacological characteristics and adverse effects of Pfizer/BioNTech and Moderna Vaccines. Eur Rev Med Pharmacol Sci 25(3): 1663–1669. https://doi.org/10.26355/eurrev_202102_24877

Merkel JS, Sturtevant JM, Regan L (1999) Sidechain interactions in parallel β sheets: the energetics of cross-strand pairings. Structure 7(11): 1333–1343. https://doi.org/10.1016/S0969-2126(00)80023-4 DOI: https://doi.org/10.1016/S0969-2126(00)80023-4

Mlcochova P, Kemp SA, Dhar MS, Papa G, Meng B, Ferreira IATM, Datir R, Collier DA, Albecka A, Singh S, Pandey R, Brown J, Zhou J, Goonawardane N, Mishra S, Whittaker C, Mellan T, Marwal R, Datta M, Sengupta S, Ponnusamy K, Radhakrishnan VS, Abdullahi A, Charles O, Chattopadhyay P, Devi P, Caputo D, Peacock T, Wattal C, Goel N, Satwik A, Vaishya R, Agarwal M, Mavousian A, Lee JH, Bassi J, Silacci-Fegni C, Saliba C, Pinto D, Irie T, Yoshida I, Hamilton WL, Sato K, Bhatt S, Flaxman S, James LC, Corti D, Piccoli L, Barclay WS, Rakshit P, Agrawal A, Gupta RK (2021) SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion. Nature 599(7883): 114–119. https://doi.org/10.1038/s41586-021-03944-y DOI: https://doi.org/10.1038/s41586-021-03944-y

Mueller AL, McNamara MS, Sinclair DA (2020) Why does COVID-19 disproportionately affect older people? Aging 12(10): 9959–9981. https://doi.org/10.18632/aging.103344 DOI: https://doi.org/10.18632/aging.103344

Ng PC, Henikoff S (2006) Predicting the Effects of Amino Acid Substitutions on Protein Function. Annual Review of Genomics and Human Genetics 7(Volume 7, 2006): 61–80. https://doi.org/10.1146/annurev.genom.7.080505.115630 DOI: https://doi.org/10.1146/annurev.genom.7.080505.115630

Ng WH, Tipih T, Makoah NA, Vermeulen J-G, Goedhals D, Sempa JB, Burt FJ, Taylor A, Mahalingam S (2021) Comorbidities in SARS-CoV-2 Patients: A Systematic Review and Meta-Analysis. mBio 12(1): 10.1128/mbio.03647-20. https://doi.org/10.1128/mbio.03647-20 DOI: https://doi.org/10.1128/mBio.03647-20

O’Donnell TJ, Rubinsteyn A, Bonsack M, Riemer AB, Laserson U, Hammerbacher J (2018) MHCflurry: Open-Source Class I MHC Binding Affinity Prediction. cels 7(1): 129-132.e4. https://doi.org/10.1016/j.cels.2018.05.014 DOI: https://doi.org/10.1016/j.cels.2018.05.014

Oronsky B, Larson C, Hammond TC, Oronsky A, Kesari S, Lybeck M, Reid TR (2023) A Review of Persistent Post-COVID Syndrome (PPCS). Clinic Rev Allerg Immunol 64(1): 66–74. https://doi.org/10.1007/s12016-021-08848-3 DOI: https://doi.org/10.1007/s12016-021-08848-3

Pearson WR (2018) Selecting the Right Similarity‐Scoring Matrix. Current Protocols in Bioinformatics https://doi.org/10.1002/0471250953.bi0305s43 DOI: https://doi.org/10.1002/0471250953.bi0305s43

Peters B, Sette A (2005) Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method. BMC Bioinformatics 6(1): 132. https://doi.org/10.1186/1471-2105-6-132 DOI: https://doi.org/10.1186/1471-2105-6-132

Rahman MS, Hoque MN, Islam MR, Akter S, Alam ASMRU, Siddique MA, Saha O, Rahaman MM, Sultana M, Crandall KA, Hossain MA (2020) Epitope-based chimeric peptide vaccine design against S, M and E proteins of SARS-CoV-2, the etiologic agent of COVID-19 pandemic: an in silico approach. PeerJ 8: e9572. https://doi.org/10.7717/peerj.9572 DOI: https://doi.org/10.7717/peerj.9572

Rammensee H-G, Bachmann J, Emmerich NPN, Bachor OA, Stevanović S (1999) SYFPEITHI: database for MHC ligands and peptide motifs. Immunogenetics 50(3): 213–219. https://doi.org/10.1007/s002510050595 DOI: https://doi.org/10.1007/s002510050595

Reynisson B, Alvarez B, Paul S, Peters B, Nielsen M (2020) NetMHCpan-4.1 and NetMHCIIpan-4.0: improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Research 48(W1): W449–W454. https://doi.org/10.1093/nar/gkaa379 DOI: https://doi.org/10.1093/nar/gkaa379

Rose PW, Prlić A, Altunkaya A, Bi C, Bradley AR, Christie CH, Costanzo LD, Duarte JM, Dutta S, Feng Z, Green RK, Goodsell DS, Hudson B, Kalro T, Lowe R, Peisach E, Randle C, Rose AS, Shao C, Tao Y-P, Valasatava Y, Voigt M, Westbrook JD, Woo J, Yang H, Young JY, Zardecki C, Berman HM, Burley SK (2017) The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucleic Acids Research 45(D1): D271–D281. https://doi.org/10.1093/nar/gkw1000 DOI: https://doi.org/10.1093/nar/gkw1000

Saeed BQ, Al-Shahrabi R, Alhaj SS, Alkokhardi ZM, Adrees AO (2021) Side effects and perceptions following Sinopharm COVID-19 vaccination. International Journal of Infectious Diseases 111: 219–226. https://doi.org/10.1016/j.ijid.2021.08.013 DOI: https://doi.org/10.1016/j.ijid.2021.08.013

Schrödinger, LLC (2015) The PyMOL Molecular Graphics System, Version 1.8.

Seyran M, Takayama K, Uversky VN, Lundstrom K, Palù G, Sherchan SP, Attrish D, Rezaei N, Aljabali AAA, Ghosh S, Pizzol D, Chauhan G, Adadi P, Mohamed Abd El-Aziz T, Soares AG, Kandimalla R, Tambuwala M, Hassan SkS, Azad GK, Pal Choudhury P, Baetas-da-Cruz W, Serrano-Aroca Á, Brufsky AM, Uhal BD (2021) The structural basis of accelerated host cell entry by SARS-CoV-2. The FEBS Journal 288(17): 5010–5020. https://doi.org/10.1111/febs.15651 DOI: https://doi.org/10.1111/febs.15651

Song P, Li W, Xie J, Hou Y, You C (2020) Cytokine storm induced by SARS-CoV-2. Clinica Chimica Acta 509: 280–287. https://doi.org/10.1016/j.cca.2020.06.017 DOI: https://doi.org/10.1016/j.cca.2020.06.017

Soskine M, Tawfik DS (2010) Mutational effects and the evolution of new protein functions. Nat Rev Genet 11(8): 572–582. https://doi.org/10.1038/nrg2808 DOI: https://doi.org/10.1038/nrg2808

Southwood S, Sidney J, Kondo A, del Guercio M-F, Appella E, Hoffman S, Kubo RT, Chesnut RW, Grey HM, Sette A (1998) Several Common HLA-DR Types Share Largely Overlapping Peptide Binding Repertoires1 2. The Journal of Immunology 160(7): 3363–3373. https://doi.org/10.4049/jimmunol.160.7.3363 DOI: https://doi.org/10.4049/jimmunol.160.7.3363

Tamura K, Stecher G, Kumar S (2021) MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Molecular Biology and Evolution 38(7): 3022–3027. https://doi.org/10.1093/molbev/msab120 DOI: https://doi.org/10.1093/molbev/msab120

Unione L, Moure MJ, Lenza MP, Oyenarte I, Ereño-Orbea J, Ardá A, Jiménez-Barbero J (2022) The SARS-CoV-2 Spike Glycoprotein Directly Binds Exogeneous Sialic Acids: A NMR View. Angewandte Chemie 134(18): e202201432. https://doi.org/10.1002/ange.202201432 DOI: https://doi.org/10.1002/ange.202201432

Valdar WSJ (2002) Scoring residue conservation. Proteins: Structure, Function, and Bioinformatics 48(2): 227–241. https://doi.org/10.1002/prot.10146 DOI: https://doi.org/10.1002/prot.10146

Vinayagam S, Sattu K (2020) SARS-CoV-2 and coagulation disorders in different organs. Life Sciences 260: 118431. https://doi.org/10.1016/j.lfs.2020.118431 DOI: https://doi.org/10.1016/j.lfs.2020.118431

Walls AC, Park Y-J, Tortorici MA, Wall A, McGuire AT, Veesler D (2020) Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein. Cell 181(2): 281-292.e6. https://doi.org/10.1016/j.cell.2020.02.058 DOI: https://doi.org/10.1016/j.cell.2020.02.058

Wheeler DL, Chappey C, Lash AE, Leipe DD, Madden TL, Schuler GD, Tatusova TA, Rapp BA (2000) Database resources of the National Center for Biotechnology Information. Nucleic Acids Research 28(1): 10–14. https://doi.org/10.1093/nar/28.1.10 DOI: https://doi.org/10.1093/nar/28.1.10

World Health Organization (2023) WHO Director-General’s opening remarks at the media briefing – 5 May 2023. (Accessed July 2024: https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing---5-may-2023)

World Health Organization forthcoming. COVID-19 cases. (Accessed June 2024: https://data.who.int/dashboards/covid19/cases)

Yang Y, Zhang Y, Qu Y, Zhang C, Liu X-W, Zhao M, Mu Y, Li W (2021) Key residues of the receptor binding domain in the spike protein of SARS-CoV-2 mediating the interactions with ACE2: a molecular dynamics study. Nanoscale 13(20): 9364–9370. https://doi.org/10.1039/D1NR01672E DOI: https://doi.org/10.1039/D1NR01672E

Yazdani Z, Rafiei A, Yazdani M, Valadan R (2020) Design an Efficient Multi-Epitope Peptide Vaccine Candidate Against SARS-CoV-2: An insilico Analysis. Infection and Drug Resistance 13: 3007–3022. https://doi.org/10.2147/IDR.S264573 DOI: https://doi.org/10.2147/IDR.S264573

Zhang Y, He X, Zhai J, Ji B, Man VH, Wang J (2021) In silico binding profile characterization of SARS-CoV-2 spike protein and its mutants bound to human ACE2 receptor. Briefings in Bioinformatics 22(6): bbab188. https://doi.org/10.1093/bib/bbab188 DOI: https://doi.org/10.1093/bib/bbab188

Zhang Z-B, Xia Y-L, Shen J-X, Du W-W, Fu Y-X, Liu S-Q (2022) Mechanistic Origin of Different Binding Affinities of SARS-CoV and SARS-CoV-2 Spike RBDs to Human ACE2. Cells 11(8): 1274. https://doi.org/10.3390/cells11081274 DOI: https://doi.org/10.3390/cells11081274

Zhong N, Zheng B, Li Y, Poon L, Xie Z, Chan K, Li P, Tan S, Chang Q, Xie J, Liu X, Xu J, Li D, Yuen K, Peiris J, Guan Y (2003) Epidemiology and cause of severe acute respiratory syndrome (SARS) in Guangdong, People’s Republic of China, in February, 2003. The Lancet 362(9393): 1353–1358. https://doi.org/10.1016/S0140-6736(03)14630-2 DOI: https://doi.org/10.1016/S0140-6736(03)14630-2

Zhou B, Thao TTN, Hoffmann D, Taddeo A, Ebert N, Labroussaa F, Pohlmann A, King J, Steiner S, Kelly JN, Portmann J, Halwe NJ, Ulrich L, Trüeb BS, Fan X, Hoffmann B, Wang L, Thomann L, Lin X, Stalder H, Pozzi B, de Brot S, Jiang N, Cui D, Hossain J, Wilson MM, Keller MW, Stark TJ, Barnes JR, Dijkman R, Jores J, Benarafa C, Wentworth DE, Thiel V, Beer M (2021) SARS-CoV-2 spike D614G change enhances replication and transmission. Nature 592(7852): 122–127. https://doi.org/10.1038/s41586-021-03361-1 DOI: https://doi.org/10.1038/s41586-021-03361-1

Zimmermann K, Gibrat J-F (2010) Amino acid ‘little Big Bang’: Representing amino acid substitution matrices as dot products of Euclidian vectors. BMC Bioinformatics 11(1): 4. https://doi.org/10.1186/1471-2105-11-4 DOI: https://doi.org/10.1186/1471-2105-11-4

Downloads

Published

30-09-2024

How to Cite

Hoa, L. T., Thong, L. N., & Thong, L. M. (2024). Tailoring potential antigenic regions on pandemic SARS spike protein. Vietnam Journal of Biotechnology, 22(3), 482–506. https://doi.org/10.15625/vjbt-21493

Issue

Section

Articles

Most read articles by the same author(s)

1 2 > >>