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

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...

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Detalles Bibliográficos
Autores principales: Shcherbatova, Olga, Grebennikov, Dmitry, Sazonov, Igor, Meyerhans, Andreas, Bocharov, Gennady
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238236/
https://www.ncbi.nlm.nih.gov/pubmed/32244421
http://dx.doi.org/10.3390/pathogens9040255
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author Shcherbatova, Olga
Grebennikov, Dmitry
Sazonov, Igor
Meyerhans, Andreas
Bocharov, Gennady
author_facet Shcherbatova, Olga
Grebennikov, Dmitry
Sazonov, Igor
Meyerhans, Andreas
Bocharov, Gennady
author_sort Shcherbatova, Olga
collection PubMed
description 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.
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spelling pubmed-72382362020-06-02 Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets Shcherbatova, Olga Grebennikov, Dmitry Sazonov, Igor Meyerhans, Andreas Bocharov, Gennady Pathogens Article 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. MDPI 2020-03-31 /pmc/articles/PMC7238236/ /pubmed/32244421 http://dx.doi.org/10.3390/pathogens9040255 Text en © 2020 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/).
spellingShingle Article
Shcherbatova, Olga
Grebennikov, Dmitry
Sazonov, Igor
Meyerhans, Andreas
Bocharov, Gennady
Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
title Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
title_full Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
title_fullStr Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
title_full_unstemmed Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
title_short Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
title_sort modeling of the hiv-1 life cycle in productively infected cells to predict novel therapeutic targets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7238236/
https://www.ncbi.nlm.nih.gov/pubmed/32244421
http://dx.doi.org/10.3390/pathogens9040255
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