Shell disorder analysis predicts greater resilience of the SARS-CoV-2 (COVID-19) outside the body and in body fluids.

Gerard Kian-Meng Goh, A Keith Dunker, James A Foster, Vladimir N Uversky
Author Information
  1. Gerard Kian-Meng Goh: Goh's BioComputing, Singapore. Electronic address: gohsbiocomputing@yahoo.com.
  2. A Keith Dunker: Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
  3. James A Foster: Department of Biological Sciences, University of Idaho, Moscow, ID, USA; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, ID, USA.
  4. Vladimir N Uversky: Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA; Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow region, Russia.

Abstract

The coronavirus (CoV) family consists of viruses that infects a variety of animals including humans with various levels of respiratory and fecal-oral transmission levels depending on the behavior of the viruses' natural hosts and optimal viral fitness. A model to classify and predict the levels of respective respiratory and fecal-oral transmission potentials of the various viruses was built before the outbreak of MERS-CoV using AI and empirically-based molecular tools to predict the disorder level of proteins. Using the percentages of intrinsic disorder (PID) of the nucleocapsid (N) and membrane (M) proteins of CoV, the model easily clustered the viruses into three groups with the SARS-CoV (M PID = 8%, N PID = 50%) falling into Category B, in which viruses have intermediate levels of both respiratory and fecal-oral transmission potentials. Later, MERS-CoV (M PID = 9%, N PID = 44%) was found to be in Category C, which consists of viruses with lower respiratory transmission potential but with higher fecal-oral transmission capabilities. Based on the peculiarities of disorder distribution, the SARS-CoV-2 (M PID = 6%, N PID = 48%) has to be placed in Category B. Our data show however, that the SARS-CoV-2 is very strange with one of the hardest protective outer shell, (M PID = 6%) among coronaviruses. This means that it might be expected to be highly resilient in saliva or other body fluids and outside the body. An infected body is likelier to shed greater numbers of viral particles since the latter is more resistant to antimicrobial enzymes in body fluids. These particles are also likelier to remain active longer. These factors could account for the greater contagiousness of the SARS-CoV-2 and have implications for efforts to prevent its spread.

Keywords

References

  1. Lancet. 2020 Feb 22;395(10224):565-574 [PMID: 32007145]
  2. J Med Virol. 2020 Jun;92(6):602-611 [PMID: 32104911]
  3. PLoS Pathog. 2017 Sep 21;13(9):e1006512 [PMID: 28934357]
  4. Oncotarget. 2017 Feb 21;8(8):12686-12694 [PMID: 27050368]
  5. Infect Immun. 1999 Jul;67(7):3267-75 [PMID: 10377100]
  6. Proteins. 2001 Jan 1;42(1):38-48 [PMID: 11093259]
  7. J Pathog. 2012;2012:738590 [PMID: 23097708]
  8. Mol Biosyst. 2015 Aug;11(8):2312-23 [PMID: 26080321]
  9. Genome Inform Ser Workshop Genome Inform. 1999;10:41-50 [PMID: 11072341]
  10. Biochemistry. 2005 Sep 20;44(37):12454-70 [PMID: 16156658]
  11. Adv Dent Res. 2011 Apr;23(1):34-7 [PMID: 21441478]
  12. Proteins. 2000 Nov 15;41(3):415-27 [PMID: 11025552]
  13. Biomolecules. 2019 Nov 06;9(11): [PMID: 31698857]
  14. Mol Biosyst. 2016 May 24;12(6):1881-91 [PMID: 27102744]
  15. Biomolecules. 2019 May 08;9(5): [PMID: 31072073]
  16. J Infect Dis. 2011 Nov;204 Suppl 3:S817-24 [PMID: 21987757]
  17. Nature. 2020 Mar;579(7798):270-273 [PMID: 32015507]
  18. Lancet Infect Dis. 2014 Feb;14(2):93-4 [PMID: 24355867]
  19. Clin Microbiol Newsl. 2014 Aug 1;36(15):115-122 [PMID: 32287683]
  20. Clin Chim Acta. 1974 Dec 17;57(3):205-9 [PMID: 4434640]
  21. Genome Inform Ser Workshop Genome Inform. 1999;10:30-40 [PMID: 11072340]
  22. Biochem Biophys Res Commun. 2009 Nov 6;389(1):63-9 [PMID: 19712667]
  23. Biomolecules. 2020 Feb 19;10(2): [PMID: 32092911]
  24. Viruses. 2014 Aug 07;6(8):2991-3018 [PMID: 25105276]
  25. Chin Med J (Engl). 2020 May 5;133(9):1051-1056 [PMID: 32149769]
  26. Virol J. 2008 Oct 23;5:126 [PMID: 18947403]
  27. J Med Virol. 2020 Apr;92(4):433-440 [PMID: 31967321]
  28. Biochemistry. 2007 Nov 27;46(47):13468-77 [PMID: 17973494]
  29. J Allergy Clin Immunol. 2008 Aug;122(2):261-6 [PMID: 18439663]
  30. FEBS Lett. 2004 Oct 8;576(1-2):174-8 [PMID: 15474033]
  31. Protein Pept Lett. 2010 Aug;17(8):932-51 [PMID: 20450483]
  32. J Mol Biol. 1999 Oct 22;293(2):321-31 [PMID: 10550212]
  33. Adv Virus Res. 2006;66:193-292 [PMID: 16877062]
  34. N Engl J Med. 2004 Apr 22;350(17):1731-9 [PMID: 15102999]
  35. J Virol. 2015 Mar;89(6):3332-42 [PMID: 25589635]
  36. PLoS Curr. 2013 Nov 13;5: [PMID: 24270586]
  37. Mol Biosyst. 2015 Aug;11(8):2337-44 [PMID: 26086270]
  38. Virol J. 2009 Jun 03;6:69 [PMID: 19493338]
  39. Microb Pathog. 2020 Apr;141:103976 [PMID: 31940461]
  40. Trends Biochem Sci. 2002 Oct;27(10):527-33 [PMID: 12368089]
  41. BMC Genomics. 2008 Sep 16;9 Suppl 2:S4 [PMID: 18831795]
  42. Emerg Microbes Infect. 2019;8(1):717-723 [PMID: 31119984]

MeSH Term

Betacoronavirus
Body Fluids
COVID-19
Coronavirus Infections
Feces
Humans
Middle East Respiratory Syndrome Coronavirus
Pandemics
Pneumonia, Viral
Severe acute respiratory syndrome-related coronavirus
SARS-CoV-2
Saliva
Severe Acute Respiratory Syndrome

Word Cloud

Created with Highcharts 10.0.0bodyvirusestransmissionMlevelsrespiratoryfecal-oraldisorderNSARS-CoV-2CoVCategoryfluidsgreaterconsistsvariousviralmodelpredictpotentialsMERS-CoVproteinsBPID = 6%outsidelikelierparticlescoronavirusfamilyinfectsvarietyanimalsincludinghumansdependingbehaviorviruses'naturalhostsoptimalfitnessclassifyrespectivebuiltoutbreakusingAIempirically-basedmoleculartoolslevelUsingpercentagesintrinsicPIDnucleocapsidmembraneeasilyclusteredthreegroupsSARS-CoVPID = 8%PID = 50%fallingintermediateLaterPID = 9%PID = 44%foundClowerpotentialhighercapabilitiesBasedpeculiaritiesdistributionPID = 48%placeddatashowhoweverstrangeonehardestprotectiveoutershellamongcoronavirusesmeansmightexpectedhighlyresilientsalivainfectedshednumberssincelatterresistantantimicrobialenzymesalsoremainactivelongerfactorsaccountcontagiousnessimplicationseffortspreventspreadShellanalysispredictsresilienceCOVID-19COVIDCoronavirusIntrinsicallydisorderedproteinMERSMembraneNucleocapsidSARSSpread

Similar Articles

Cited By (42)