SARS-CoV-2 Nsp5 Protein Causes Acute Lung Inflammation: A Dynamical Mathematical Model

In the present work we propose a dynamical mathematical model of the lung cells inflammation process in response to SARS-CoV-2 infection. In this scenario the main protease Nsp5 enhances the inflammatory process, increasing the levels of NF kB, IL-6, Cox2, and PGE2 with respect to a reference state without the virus. In presence of the virus the translation rates of NF kB and IkB arise to a high constant value, and when the translation rate of IL-6 also increases above the threshold value of 7 pg mL-1 s-1 the model predicts a persistent over stimulated immune state with high levels of the cytokine IL-6. Our model shows how such over stimulated immune state becomes autonomous of the signals from other immune cells such as macrophages and lymphocytes, and does not shut down by itself. We also show that in the context of the dynamical model presented here, Dexamethasone or Nimesulide have little effect on such inflammation state of the infected lung cell, and the only form to suppress it is with the inhibition of the activity of the viral protein Nsp5.To that end, our model suggest that drugs like Saquinavir may be useful. In this form, our model suggests that Nsp5 is effectively a central node underlying the severe acute lung inflammation during SARS-CoV-2 infection. The persistent production of IL-6 by lung cells can be one of the causes of the cytokine storm observed in critical patients with COVID19. Nsp5 seems to be the switch to start inflammation, the consequent overproduction of the ACE2 receptor, and an important underlying cause of the most severe cases of COVID19..

Medienart:

Preprint

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Preprints.org - (2021) vom: 16. März Zur Gesamtaufnahme - year:2021

Sprache:

Englisch

Beteiligte Personen:

Díaz, José [VerfasserIn]
Álvarez-Buylla, Elena R. [VerfasserIn]
Bensussen, Antonio [VerfasserIn]

Links:

Volltext [kostenfrei]

doi:

10.20944/preprints202012.0749.v2

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

preprintsorg019661193