Intracellular life cycle kinetics of SARS-CoV-2 predicted using mathematical modelling

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• dc.contributor.author Grebennikov, Dmitry
• dc.contributor.author Kholodareva, Ekaterina
• dc.contributor.author Sazonov, Igor
• dc.contributor.author Karsonova, Antonina
• dc.contributor.author Meyerhans, Andreas
• dc.contributor.author Bocharov, Gennady A.
• dc.date.accessioned 2021-10-20T06:29:34Z
• dc.date.available 2021-10-20T06:29:34Z
• dc.date.issued 2021
• dc.description.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.
• dc.description.sponsorship The reported study was funded by RFBR according to the research project numbers 20-04-60157 and 20-01-00352. AM is also supported by the Spanish Ministry of Science and Innovation grant no. PID2019-106323RB-I00(AEI/MINEICO/FEDER, UE), and “Unidad de Excelencia María de Maeztu”, funded by the AEI (CEX2018-000792-M). G.B. and D.G. were partly supported by Moscow Center for Fundamental and Applied Mathematics (agreement with the Ministry of Education and Science of the Russian Federation No. 075-15-2019-1624).
• dc.format.mimetype application/pdf
• dc.identifier.citation Grebennikov D, Kholodareva E, Sazonov I, Karsonova A, Meyerhans A, Bocharov G. Intracellular life cycle kinetics of SARS-CoV-2 predicted using mathematical modelling. Viruses. 2021;13(9):1735. DOI: 10.3390/v13091735
• dc.identifier.doi http://dx.doi.org/10.3390/v13091735
• dc.identifier.issn 1999-4915
• dc.identifier.uri http://hdl.handle.net/10230/48715
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Viruses. 2021;13(9):1735
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-106323RB-I00
• dc.rights © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword SARS-CoV-2
• dc.subject.keyword Intracellular replication
• dc.subject.keyword Mathematical model
• dc.subject.keyword Sensitivity analysis
• dc.subject.keyword Targets for drugs
• dc.title Intracellular life cycle kinetics of SARS-CoV-2 predicted using mathematical modelling
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion