Journal article 623 views 109 downloads
Intracellular Life Cycle Kinetics of SARS-CoV-2 Predicted Using Mathematical Modelling
,
Antonina Karsonova,
Andreas Meyerhans,
Gennady Bocharov
Viruses, Volume: 13, Issue: 9, Start page: 1735
Swansea University Author:
Igor Sazonov
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DOI (Published version): 10.3390/v13091735
Abstract
SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contr...
| Published in: | Viruses |
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| ISSN: | 1999-4915 |
| Published: |
MDPI AG
2021
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa58314 |
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| Abstract: |
SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contributing to the observed disease phenotypes. In our study here, we formulate and calibrate a deterministic model of the SARS-CoV-2 life cycle. It provides a kinetic description of the major replication stages of SARS-CoV-2. Sensitivity analysis of the net viral progeny with respect to model parameters enables the identification of the life cycle stages that have the strongest impact on viral replication. These three most influential parameters are (i) degradation rate of positive sense vRNAs in cytoplasm (negative effect), (ii) threshold number of non-structural proteins enhancing vRNA transcription (negative effect), and (iii) translation rate of non-structural proteins (positive effect). The results of our analysis could be used for guiding the search for antiviral drug targets to combat SARS-CoV-2 infection. |
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| Keywords: |
intracellular replication, mathematical model, sensitivity analysis, targets for drugs, SARS-CoV-2 |
| College: |
Faculty of Science and Engineering |
| Funders: |
Russian Foundation for Basic Research Grant: 20-04-60157 Grant: 20-01-00352 Ministry of Education and Science of the Russian Federation Grant: 075-15-2019-1624 |
| Issue: |
9 |
| Start Page: |
1735 |