Acta Scientific Microbiology (ASMI) (ISSN: 2581-3226)

Research Article Volume 4 Issue 1

On SARS-CoV-2, Tropical Medicine and Bioinformatics: Analysis of the SARS-Cov-2 Molecular Features and Epitope Prediction for Antibody or Vaccine Development

Joshua Angelo Hermida Mandanas*

Tropical Medicine Scientist and Immunobiologist, Philippine Medical Technology Professional/ National Lecturer, University of the Philippines Manila, Philippines

*Corresponding Author: Joshua Angelo Hermida Mandanas, Tropical Medicine Scientist and Immunobiologist, Philippine Medical Technology Professional/ National Lecturer, University of the Philippines Manila, Philippines.

Received: November 24, 2020; Published: December 08, 2020



Introduction: SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is the cause of COVID-19 which is the pandemic as of the current time. It is a global public health emergency and is still on the loose of spreading more infections and deaths. Bioinformatics offer extensive visualization and analysis of combined molecular, cellular, biochemical and immunobiologic aspects of SARS-CoV-2 which is indeed vital for antibody and vaccine development.

Objectives: This paper presents the SARS-CoV-2 molecular virologic, biochemical, cellular and immunobiologic features and gives a basic B cell linear epitope prediction of the SARS-CoV-2 spike (S) glycoprotein using bioinformatics which both can serve as a guide for development of vaccines or antibody-based treatments.

Methods: Several bioinformatic methods were used, from sequence analysis (Uniprot), structural correlation (PDB), molecular modelling (UCSF Chimera) and illustration (Biorender), B cell linear epitope prediction tools, conservancy analysis and search of related epitopes (IEDB) together with determination of disordered regions (GlobPlot and DisEMBL).

Results: Host enzymes such as furin, cathepsin L and TMPRSS2 enable pre-processing of SARS-CoV-2 prior to infecting cells such as monocytes, macrophages and alveolar cells. Sialylated cells can potentially be infected with SARS-CoV-2. A 29 and an 11-residues long B cell linear epitope candidates were predicted from the SARS-CoV-2 spike (S) glycoprotein to be the potential target of antibodies or vaccines.

Conclusion: SARS-CoV-2 binds to many host receptors and is enzymatically processed leading to infection of many human cells. Prediction of B cell linear epitopes using bioinformatics can be vital for antibody or vaccine development. Integration of Tropical Medicine and Bioinformatics can offer new horizons and can turn the battle against SARS-CoV-2.

Keywords: SARS-Cov-2; COVID-19; Tropical Medicine; Bioinformatics; Epitope; Vaccine



  1. Huang C., et al. “Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China”. Lancet 395 (2020): 497-506.
  2. Jin Y., et al. “Virology, Epidemiology, Pathogenesis, and Control of COVID-19”. Viruses 12 (2020): 372.
  3. Wang L., et al. “Review of the 2019 novel coronavirus (SARS-CoV-2) based on current evidence”. International Journal of Antimicrobial Agents6 (2020): 105948.
  4. Chan JF., et al. “Interspecies transmission and emergence of novel viruses: lessons from bats and birds”. Trends in Microbiology 21 (2013): 544-555.
  5. Corman VM., et al. “Hosts and Sources of Endemic Human Coronaviruses”. Advances in Virus Research 100 (2018): 163-188.
  6. Mackay IM and Arden KE. “MERS coronavirus: diagnostics, epidemiology and transmission”. Virology Journal 12 (2015): 222.
  7. Ji W., et al. “Homologous recombination within the spike glycoprotein of the newly identified coronavirus may boost cross-species transmission from snake to human”. Journal of Medical Virology (2020): 92.
  8. Ji W., et al. “Cross-species transmission of the newly identified coronavirus 2019-nCoV”. Medical Virology 4 (2020): 433-440.
  9. King AMQ., et al. “Virus Taxonomy: Ninth Report of the International Committee on Taxonomy of Viruses”. Amsterdam: Elsevier (2011): 806-828.
  12. “Generation and behaviour of airborne particles” (2020).
  13. Adam D., et al. “Clustering and superspreading potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Hong Kong (pre-print)”. Research Square (2020).
  14. Vivanti AJ., et al. Transplacental transmission of SARS-CoV-2 infection”. Nature Communication 11 (2020): 3572.
  19. Bayat A. “Science, medicine, and the future: Bioinformatics”. BMJ (Clinical research ed.), 324.7344 (2002): 1018-1022.
  20. Kumar S., et al. “Morphology, Genome Organization, Replication, and Pathogenesis of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Coronavirus Disease 2019 (COVID-19): Epidemiology, Pathogenesis, Diagnosis, and Therapeutics” (2020): 23-31.
  21. Woo PC., et al. “Coronavirus diversity, phylogeny and interspecies jumping”. Experimental Biology and Medicine (Maywood) 10 (2009): 1117-1127.
  22. Park WB., et al. “Virus Isolation from the First Patient with SARS-CoV-2 in Korea”. Journal of Korean Medical Science 7 (2020): e84.
  23. Kalathiya U., et al. “Highly Conserved Homotrimer Cavity Formed by the SARS-CoV-2 Spike Glycoprotein: A Novel Binding Site”. Journal of Clinical Medicine5 (2020): 1473.
  24. Lau S Y., et al. “Attenuated SARS-CoV-2 variants with deletions at the S1/S2 junction”. Emerging Microbes and Infections1 (2020): 837-842.
  25. Jaimes J A., et al. “Proteolytic Cleavage of the SARS-CoV-2 Spike Protein and the Role of the Novel S1/S2 Site”. iScience6 (2020): 101212.
  26. Ou X., et al. “Characterization of spike glycoprotein of SARS-CoV-2 on virus entry and its immune cross-reactivity with SARS-CoV”. Nature Communication 11 (2020): 1620.
  27. Trigueiro-Louro J., et al. “Unlocking COVID therapeutic targets: A structure-based rationale against SARS-CoV-2, SARS-CoV and MERS-CoV Spike” (2020).
  28. Wu A., et al. “Genome composition and divergence of the novel coronavirus (2019-nCoV) originating in China”. Cell Host Microbe3 (2020): 325-328.
  29. Khailany R A., et al. “Genomic characterization of a novel SARS-CoV-2”. Gene Reports 19 (2020): 100682.
  30. Xu J., et al. “Systematic Comparison of Two Animal-to-Human Transmitted Human Coronaviruses: SARS-CoV-2 and SARS-CoV”. Viruses 2 (2020): 244.
  31. Lu R., et al. “Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding”. Lancet (London, England)10224 (2020): 565-574.
  32. Wang H., et al. “The genetic sequence, origin, and diagnosis of SARS-CoV-2”. European journal of clinical Microbiology and Infectious Diseases: official publication of the European Society of Clinical Microbiology 39.9 (2020): 1629-1635.
  33. “The software that powers scientific illustration”. Nature 582 (2020): 137-138.
  34. , et al. “UCSF Chimera--a visualization system for exploratory research and analysis". Journal of Computational Chemistry 25.13 (2019): 1605-1612.
  35. Hoffmanm M., et al. “A Multibasic Cleavage Site in the Spike Protein of SARS-CoV-2 Is Essential for Infection of Human Lung Cells”. Molecular Cell4 (2020): 779-784.e5.
  36. Shang J., et al. “Cell entry mechanisms of SARS-CoV-2”. Proceedings of the National Academy of Sciences of the United States of America21 (2020): 11727-11734.
  37. Johnson B A., et al. “Furin Cleavage Site Is Key to SARS-CoV-2 Pathogenesis”. bioRxiv (2020).
  38. Tang T., et al. “Coronavirus membrane fusion mechanism offers a potential target for antiviral development”. Antiviral Research 178 (2020): 104792.
  39. Tong Meng., et al. “The insert sequence in SARS-CoV-2 enhances spike protein cleavage by TMPRSS”. bioRxiv (2020).
  40. Heurich A., et al. “TMPRSS2 and ADAM17 cleave ACE2 differentially and only proteolysis by TMPRSS2 augments entry driven by the severe acute respiratory syndrome coronavirus spike protein”. Journal of Virology 88 (2014): 1293-1307.
  41. Sungnak W., et al. “SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes”. Nature Medicine 26 (2020): 681-687.
  42. Abassi Z., et al. “The Lung Macrophage in SARS-CoV-2 Infection: A Friend or a Foe?”. Frontiers in Immunology 11 (2020): 1312.
  43. Rensi S., et al. “Homology Modeling of TMPRSS2 Yields Candidate Drugs That May Inhibit Entry of SARS-CoV-2 into Human Cells”. ChemRxiv (2020).
  44. Morniroli D., et al. “Human Sialome and Coronavirus Disease-2019 (COVID-19) Pandemic: An Understated Correlation?”. Frontiers in Immunology (2020).
  45. Wei Hao., et al. “Binding of the SARS-CoV-2 Spike Protein to Glycans”. bioRxiv (2020).
  46. Ward S., et al. “von Willebrand factor sialylation-A critical regulator of biological function”. Journal of Thrombosis and Haemostasis 7 (2019): 1018-1029.
  47. Estus S., et al. “Evaluation of CD33 as a genetic risk factor for Alzheimer's disease”. Acta Neuropathology2 (2019): 187-199.
  48. Schwartz-Albiez R., et al. “Cell surface sialylation and ecto-sialyltransferase activity of human CD34 progenitors from peripheral blood and bone marrow”. Glycoconj Journal 21 (2004): 451-459.
  49. Kawasaki N., et al. “Targeted delivery of lipid antigen to macrophages via the CD169/sialoadhesin endocytic pathway induces robust invariant natural killer T cell activation”. Proceedings of the National Academy of Sciences of the United States of America19 (2020): 7826-7831.
  50. Merah-Mourah F., et al. “Identification of Novel Human Monocyte Subsets and Evidence for Phenotypic Groups Defined by Interindividual Variations of Expression of Adhesion Molecules”. Scientific Report 10 (2020): 4397.
  51. Venosa A., et al. “Characterization of Distinct Macrophage Subpopulations during Nitrogen Mustard-Induced Lung Injury and Fibrosis”. American Journal of Respiratory Cell and Molecular Biology3 (2016): 436-446.
  52. Grabowska J., et al. “CD169+ Macrophages Capture and Dendritic Cells Instruct: The Interplay of the Gatekeeper and the General of the Immune System”. Frontiers in Immunology 9 (2018): 2472.
  53. Kessel K U., et al. “Emergence of CD43-Expressing Hematopoietic Progenitors from Human Induced Pluripotent Stem Cells”. Transfusion medicine and hemotherapy: offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie3 (2017): 143-150.
  54. Pedraza-Alva G., et al. “T cell activation through the CD43 molecule leads to Vav tyrosine phosphorylation and mitogen-activated protein kinase pathway activation”. The Journal of Biological Chemistry23 (1998): 14218-14224.
  55. Wang Q., et al. “Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2”. Cell4 (2020): 894-904.e9.
  56. Nguyen H L., et al. “Does SARS-CoV-2 Bind to Human ACE2 More Strongly Than Does SARS-CoV?”. The Journal of Physical Chemistry. B 34 (2020): 7336-7347.
  57. Koyama T., et al. “Variant analysis of SARS-CoV-2 genomes”. Bulletin of the World Health Organization 98 (2020): 495-504.
  58. Ma Y., et al. “Structural basis and functional analysis of the SARS coronavirus nsp14-nsp10 complex”. Proceedings of the National Academy of Sciences of the United States of America 30 (2015): 9436-9441.
  59. Pachetti M., et al. “Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant”. Journal of Translational Medicine1 (2020): 179.
  60. Huang Y., et al. “Structural and functional properties of SARS-CoV-2 spike protein: potential antivirus drug development for COVID-19”. Acta Pharmaceutica Sinica 41 (2020): 1141-1149.
  61. The UniProt Consortium. “UniProt: a worldwide hub of protein knowledge”. Nucleic Acids Research 47 (2019): D506-515.
  63. Apweiler R., et al. “Protein sequence databases". Current Opinion in Chemical Biology1 (2004): 76-80.
  64. Leinonen R Diez., et al. “UniProt archive". Bioinformatics17 (2004): 3236-3237.
  65. Suzek B., et al. “UniRef: Comprehensive and non-redundant UniProt reference clusters". Bioinformatics 10 (2007): 1282-1288.
  66. Uniprot C. "The Universal Protein Resource (UniProt) in 2010". Nucleic Acids Research 38 (2009): D142-D148.
  67. wwPDB Consortium. "Protein Data Bank: the single global archive for 3D macromolecular structure data". Nucleic Acids Research 47 (2019): 520-528.
  69. NCBI Resource Coordinators. “Database resources of the National Center for Biotechnology Information”. Nucleic Acids Research 46 (2018): D8-D13.
  71. Bui HH., et al. “Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines”. BMC Bioinformatics 8 (2007): 361.
  72. Li F., et al. “Structure of SARS coronavirus spike receptor-binding domain complexed with receptor”. Science (New York, N.Y.), 309.574 (2005): 1864-1868.
  73., (similarity)%20between%20two%20sequences
  74. Song H C., et al. “Synthesis and characterization of a native, oligomeric form of recombinant severe acute respiratory syndrome coronavirus spike glycoprotein”. Journal of Virology19 (2004): 10328-10335.
  75. Sette A., et al. “Definition of epitopes and antigens recognized by vaccinia specific immune responses: their conservation in variola virus sequences, and use as a model system to study complex pathogens”. Vaccine 27 (2009): G21-G26.
  76. Forthal D N. “Functions of Antibodies”. Microbiology Spectrum4 (2014): 1-17.
  77. Noviski M., et al. “IgM and IgD B cell receptors differentially respond to endogenous antigens and control B cell fate”. eLife 7 (2018): e35074.
  78. Frank SA.” Immunology and Evolution of Infectious Disease”. Princeton (NJ): Princeton University Press. Chapter 4, Specificity and Cross-Reactivity (2002).
  79. Forsström B., et al. “Dissecting antibodies with regards to linear and conformational epitopes”. PloS One 3 (2015): e0121673.
  80. Oscherwitz J. “The promise and challenge of epitope-focused vaccines”. Human Vaccines and Immunotherapeutics8 (2016): 2113-2116.
  81. Poh CM., et al. “Two linear epitopes on the SARS-CoV-2 spike protein that elicit neutralising antibodies in COVID-19 patients”. Nature Communication 11 (2020): 2806.
  82. Lin L., et al. “Epitope-based peptide vaccines predicted against novel coronavirus disease caused by SARS-CoV-2”. Virus Research 288 (2020): 198082.
  83. Trolle T., et al. “The Length Distribution of Class I-Restricted T Cell Epitopes Is Determined by Both Peptide Supply and MHC Allele-Specific Binding Preference”. Journal of Immunology (Baltimore, Md.: 1950), 196.4 (2016): 1480-1487.
  84. Hewitt E W. “The MHC class I antigen presentation pathway: strategies for viral immune evasion”. Immunology2 (2003): 163-169.
  86. Ponomarenko J., et al. “ElliPro: a new structure-based tool for the prediction of antibody epitopes”. BMC Bioinformatics 9 (2008): 514.
  88. Emini EA. “Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide”. Journal of Virology1985 (1990): 836-839.
  89. Larsen JE., et al. “Improved method for predicting linear B-cell epitopes”. Immunome Research 2 (2006): 2.
  90. Kolaskar AS and Tongaonkar PC. “A semi-empirical method for prediction of antigenic determinants on protein antigens”. FEBS Letter 276 (1990): 172-174.
  91. Deng X., et al. “A comprehensive overview of computational protein disorder prediction methods”. Molecular bioSystems1 (20121): 114-121.
  92. MacRaild C A., et al. “Antibody Recognition of Disordered Antigens”. Structure (London, England: 1993), 24.1 (2016): 148-157.
  93. Guy A J., et al. “Insights into the Immunological Properties of Intrinsically Disordered Malaria Proteins Using Proteome Scale Predictions”. PloS One10 (2015): e0141729.
  94. Linding R., et al. “GlobPlot: Exploring protein sequences for globularity and disorder”. Nucleic Acids Research 13 (2003): 3701-3708.
  95. Vincent M and Schnell S. “Disorder Atlas: Web-based software for the proteome-based interpretation of intrinsic disorder predictions”. Computational Biology and Chemistry 83 (2019): 107090.
  96. Pillay TS. “Gene of the month: the 2019-nCoV/SARS-CoV-2 novel coronavirus spike protein”. Journal of Clinical Pathology7 (2020): 366-369.
  97. Chan J F., et al. “Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan”. Emerging Microbes and Infections1 (2020): 221-236.
  98. Neil S., et al. “Monoclonal Versus Polyclonal Antibodies: Distinguishing Characteristics, Applications, and Information Resources”. ILAR Journal3 (2005): 258-268.
  99. Denisova G F., et al. “Applying bioinformatics for antibody epitope prediction using affinity-selected mimotopes - relevance for vaccine design”. Immunome Research 6 (2010): S6.
  100. Oli A N., et al. “Immunoinformatics and Vaccine Development: An Overview”. ImmunoTargets and Therapy 9 (2020): 13-30.
  101. Cornick JE., et al. “The global distribution and diversity of protein vaccine candidate antigens in the highly virulent Streptococcus pneumoniae serotype 1”. Vaccine6 (2017): 972-980.
  102. Mandanas, J. “Molecular Characterization of Tefimazumab Binding to the Streptococcus pyogenes Serotype M18 Superantigen SpeC as Basis for Vaccine Development”. Acta Scientific Microbiology5 (2019): 114-118.
  103. Alam A., et al. “From ZikV genome to vaccine: In silico approach for the epitope‐based peptide vaccine against Zika virus envelope glycoprotein”. Immunology4 (2016): 386-399.
  104. Chen H., et al. “Bioinformatics analysis of epitope-based vaccine design against the novel SARS-CoV-2”. Infectious Diseases of Poverty 9 (2020): 88.
  105. Poran A., et al. “Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes”. Genome Medicine 12 (2020): 70.
  106. Kim J W., et al. “Application of antihelix antibodies in protein structure determination”. Proceedings of the National Academy of Sciences of the United States of America36 (2019): 17786-17791.
  107. Vita R., et al. “The Immune Epitope Database (IEDB): 2018 update”. Nucleic Acids Research 24 (2018).
  108. Walls A C., et al. “Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein”. Cell 2 (2020): 281-292.e6.
  109. Xiong X., et al. “A thermostable, closed SARS-CoV-2 spike protein trimer”. Nature Structural and Molecular Biology 27 (2020): 934-941.
  110. Dahms S O., et al. “Structural Studies Revealed Active Site Distortions of Human Furin by a Small Molecule Inhibitor”. ACS Chemical Biology5 (2017): 1211-1216.
  111. Asaad N., et al. “Dipeptidyl nitrile inhibitors of Cathepsin L”. Bioorganic and Medicinal Chemistry Letters15 (2009): 4280-4283.
  112. Rao K., et al. “Crystal Structure of Serine protease Hepsin in complex with Inhibitor”.
  113. Takai Y., et al. “Structural basis of the cytoplasmic tail of adhesion molecule CD43 and its binding to ERM proteins”. Journal of Molecular Biology3 (2008): 634-644.
  114. Benton D J., et al. “Receptor binding and priming of the spike protein of SARS-CoV-2 for membrane fusion”. Nature (2020).
  115. Gui M., et al. “Cryo-electron microscopy structures of the SARS-CoV spike glycoprotein reveal a prerequisite conformational state for receptor binding”. Cell Research1 (2017): 119-129.


Citation: Joshua Angelo Hermida Mandanas. “On SARS-CoV-2, Tropical Medicine and Bioinformatics: Analysis of the SARS-Cov-2 Molecular Features and Epitope Prediction for Antibody or Vaccine Development". Acta Scientific Microbiology 4.1 (2021): 03-20.


Acceptance rate30%
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