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

Olga Shcherbatova, Dmitry Grebennikov, Igor Sazonov Orcid Logo, Andreas Meyerhans, Gennady Bocharov

Pathogens, Volume: 9, Issue: 4, Start page: 255

Swansea University Author: Igor Sazonov Orcid Logo

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DOI (Published version): 10.3390/pathogens9040255

Abstract

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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Published in: Pathogens
ISSN: 2076-0817
Published: MDPI AG 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa54020
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first_indexed 2020-04-23T13:23:06Z
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spelling 2020-05-15T19:01:28.1792722 v2 54020 2020-04-23 Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets 05a507952e26462561085fb6f62c8897 0000-0001-6685-2351 Igor Sazonov Igor Sazonov true false 2020-04-23 AERO 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. Journal Article Pathogens 9 4 255 MDPI AG 2076-0817 HIV-1; intracellular replication; mathematical model; sensitivity analysis; antiviral targets 31 3 2020 2020-03-31 10.3390/pathogens9040255 COLLEGE NANME Aerospace Engineering COLLEGE CODE AERO Swansea University 2020-05-15T19:01:28.1792722 2020-04-23T08:51:17.9694370 Olga Shcherbatova 1 Dmitry Grebennikov 2 Igor Sazonov 0000-0001-6685-2351 3 Andreas Meyerhans 4 Gennady Bocharov 5 54020__17116__2fee1581094b47379cdca3481c4cfb10.pdf 54020.pdf 2020-04-23T08:53:17.5862360 Output 2274863 application/pdf Version of Record true Released under the terms of a Creative Commons Attribution License (CC-BY). true eng http://creativecommons.org/licenses/by/4.0/
title Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
spellingShingle Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
Igor Sazonov
title_short 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_sort Modeling of the HIV-1 Life Cycle in Productively Infected Cells to Predict Novel Therapeutic Targets
author_id_str_mv 05a507952e26462561085fb6f62c8897
author_id_fullname_str_mv 05a507952e26462561085fb6f62c8897_***_Igor Sazonov
author Igor Sazonov
author2 Olga Shcherbatova
Dmitry Grebennikov
Igor Sazonov
Andreas Meyerhans
Gennady Bocharov
format Journal article
container_title Pathogens
container_volume 9
container_issue 4
container_start_page 255
publishDate 2020
institution Swansea University
issn 2076-0817
doi_str_mv 10.3390/pathogens9040255
publisher MDPI AG
document_store_str 1
active_str 0
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.
published_date 2020-03-31T04:07:19Z
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score 11.016235

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