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J Quant Spectrosc Radiat Transf. Photopolarimetrical properties of coronavirus model particles: spike proteins number influence

tetano

Editor, Senior Moderator
J Quant Spectrosc Radiat Transf. 2020 Apr 13:107005. doi: 10.1016/j.jqsrt.2020.107005. [Epub ahead of print]
Photopolarimetrical properties of coronavirus model particles: spike proteins number influence.


Petrov D[SUP]1[/SUP].

Author information




Abstract

Coronavirus virions have spherical shape surrounded by spike proteins. The coronavirus spike proteins are very effective molecular mechanisms, which provide the coronavirus entrance to the host cell. The number of these spikes is different; it dramatically depends on external conditions and determines the degree of danger of the virus. A larger number of spike proteins makes the virus infectivity stronger. This paper describes a mathematical model of the shape of coronavirus virions. Based on this model, the characteristics of light scattered by the coronavirus virions were calculated. It was found two main features of coronavirus model particles in the spectral region near 200nm: a minimum of intensity and a sharp leap of the linear polarization degree. The effect of the spike protein number on the intensity and polarization properties of the scattered light was studied. It was determined that when the number of spike proteins decreases, both the intensity minimum and the position of the linear polarization leap shift to shorter wavelengths. This allows us to better evaluate the shape of the coronavirus virion, and, therefore, the infectious danger of the virus. It was shown that the shorter the wavelength of scattered light, the more reliably one can distinguish viruses from non-viruses. The developed model and the light scattering simulations based on it can be applied not only to coronaviruses, but also to other objects of a similar structure, for example, pollen.
? 2020 Elsevier Ltd. All rights reserved.



KEYWORDS:

Computer simulation; Coronavirus; Intensity; Light scattering; Polarization; Shape matrices


PMID:32292212PMCID:PMC7152864DOI:10.1016/j.jqsrt.2020.107005
 
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