Modeling SARS-CoV-2 and preventing COVID-19 pandemic

Backgrounds: Since December 2019, COVID-19 pandemic has globally killed more than 6.602 millions, infected more than 635.2 millions of people and lasted almost three years, as of 11/22/2022. The pandemic is still killing more than 7,261 and infecting more than 2.259 millions of people per week in the whole world today. We think the rates of the fatality, infection and the long term of the pandemic are related to proliferation characteristics and biological structures of SARS-CoV-2.

Methods and Objectives: We apply theories of biology, ligand field, biophysics, biochemistry, virology, classic electrodynamics, and published biological data, to model proliferation characteristics and biological structures of SARS-CoV-2.

Modeling Results and Outcomes: We coin a concept: quasi identical biological objects carry the quasi identical biological information (spatial, temporal, electromagnetic and mass properties), and they cannot occupy the same biological envelope if their repulsive forces between them are stronger than the resistances. We propose two models of exclusions. Exclusion of RNA (DNA) strands: No normally and naturally replicated quasi identical RNA (DNA) strands can occupy the same virus. Exclusion of viruses: No normally and naturally proliferated quasi identical viruses can occupy the same biological host cell. For a SARS-CoV-2, we model the charged ssRNA and N proteins as a negatively charged central body, the charged proteins in the biological membrane as dynamic ligands, the electric field between the center and ligands as a dynamic ligand field.

Conclusions: The biological models of exclusions of RNA strands in a virus and viruses in a host cell qualitatively respectively answer the questions why or how there is only one mature ssRNA strand inside a SARS-CoV-2 membrane envelope and the virus proliferate; it is suitable to extend or analogize the ligand field theory to illustrate the stability of SARS-CoV-2 in biophysical structures (topologic constructions). Our models could be applicable to other biological objects.