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Open AccessArticle

Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets

Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia
Moscow Center for Fundamental and Applied Mathematics at INM RAS, 119333 Moscow, Russia
Institute for Personalized Medicine, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
College of Engineering, Swansea University, Bay Campus, Fabian Way, Swansea SA1 8EN, UK
Infection Biology Laboratory, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain
Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Pathogens 2020, 9(4), 255;
Received: 28 February 2020 / Revised: 24 March 2020 / Accepted: 25 March 2020 / Published: 31 March 2020
(This article belongs to the Special Issue Modeling Virus Dynamics and Evolution)
There are many studies that model the within-host population dynamics of Human Immunodeficiency Virus Type 1 (HIV-1) infection. However, the within-infected-cell replication of HIV-1 remains to be not comprehensively addressed. There exist rather few quantitative models describing the regulation of the HIV-1 life cycle at the intracellular level. In treatment of HIV-1 infection, there remain issues related to side-effects and drug-resistance that require further search “...for new and better drugs, ideally targeting multiple independent steps in the HIV-1 replication cycle” (as highlighted recently by Tedbury & Freed, The Future of HIV-1 Therapeutics, 2015). High-resolution mathematical models of HIV-1 growth in infected cells provide an additional analytical tool in identifying novel drug targets. We formulate a high-dimensional model describing the biochemical reactions underlying the replication of HIV-1 in target cells. The model considers a nonlinear regulation of the transcription of HIV-1 mediated by Tat and the Rev-dependent transport of fully spliced and singly spliced transcripts from the nucleus to the cytoplasm. The model is calibrated using available information on the kinetics of various stages of HIV-1 replication. The sensitivity analysis of the model is performed to rank the biochemical processes of HIV-1 replication with respect to their impact on the net production of virions by one actively infected cell. The ranking of the sensitivity factors provides a quantitative basis for identifying novel targets for antiviral therapy. Our analysis suggests that HIV-1 assembly depending on Gag and Tat-Rev regulation of transcription and mRNA distribution present two most critical stages in HIV-1 replication that can be targeted to effectively control virus production. These processes are not covered by current antiretroviral treatments. View Full-Text
Keywords: HIV-1; intracellular replication; mathematical model; sensitivity analysis; antiviral targets HIV-1; intracellular replication; mathematical model; sensitivity analysis; antiviral targets
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Shcherbatova, O.; Grebennikov, D.; Sazonov, I.; Meyerhans, A.; Bocharov, G. Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets. Pathogens 2020, 9, 255.

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