ArticlePLoS computational biology2012
HIV-1 polymerase inhibition by nucleoside analogs: cellular- and kinetic parameters of efficacy, susceptibility and resistance selection.
Article in PLoS computational biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- Pharmacological markers of HIV prevention for oral pre-exposure prophylaxis in men who have sex with men.Nature communications · 2026Article
- Modeling of HIV-1 prophylactic efficacy and toxicity with islatravir shows non-superiority for oral dosing, but promise as a subcutaneous implant.CPT: pharmacometrics & systems pharmacology · 2024Article
- Mathematical Modelling of the Molecular Mechanisms of Interaction of Tenofovir with Emtricitabine against HIV.Viruses · 2021Article
- The Restrictome of Flaviviruses.Virologica Sinica · 2020Review
- Modeling HIV Pre-Exposure Prophylaxis.Frontiers in pharmacology · 2019Review
- Mechanistic framework predicts drug-class specific utility of antiretrovirals for HIV prophylaxis.PLoS computational biology · 2019Article
- Molecular evolution of HIV-1 integrase during the 20 years prior to the first approval of integrase inhibitors.Virology journal · 2017Article
- Structural Insights into HIV Reverse Transcriptase Mutations Q151M and Q151M Complex That Confer Multinucleoside Drug Resistance.Antimicrobial agents and chemotherapy · 2017Article
- Multiscale Systems-Pharmacology Pipeline to Assess the Prophylactic Efficacy of NRTIs Against HIV-1.CPT: pharmacometrics & systems pharmacology · 2016Article
- Optimal Treatment Strategies in the Context of 'Treatment for Prevention' against HIV-1 in Resource-Poor Settings.PLoS computational biology · 2015Article
- Linking the population pharmacokinetics of tenofovir and its metabolites with its cellular uptake and metabolism.CPT: pharmacometrics & systems pharmacology · 2014Article
- Estimating HIV-1 fitness characteristics from cross-sectional genotype data.PLoS computational biology · 2014Article
- In vitro HIV-1 evolution in response to triple reverse transcriptase inhibitors & in silico phenotypic analysis.PloS one · 2013Article
- Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nucleoside analogs (NAs) are used to treat numerous viral infections and cancer. They compete with endogenous nucleotides (dNTP/NTP) for incorporation into nascent DNA/RNA and inhibit replication by preventing subsequent primer extension. To date, an integrated mathematical model that could allow the analysis of their mechanism of action, of the various resistance mechanisms, and their effect on viral fitness is still lacking. We present the first mechanistic mathematical model of polymerase inhibition by NAs that takes into account the reversibility of polymerase inhibition. Analytical solutions for the model point out the cellular- and kinetic aspects of inhibition. Our model correctly predicts for HIV-1 that resistance against nucleoside analog reverse transcriptase inhibitors (NRTIs) can be conferred by decreasing their incorporation rate, increasing their excision rate, or decreasing their affinity for the polymerase enzyme. For all analyzed NRTIs and their combinations, model-predicted macroscopic parameters (efficacy, fitness and toxicity) were consistent with observations. NRTI efficacy was found to greatly vary between distinct target cells. Surprisingly, target cells with low dNTP/NTP levels may not confer hyper-susceptibility to inhibition, whereas cells with high dNTP/NTP contents are likely to confer natural resistance. Our model also allows quantification of the selective advantage of mutations by integrating their effects on viral fitness and drug susceptibility. For zidovudine triphosphate (AZT-TP), we predict that this selective advantage, as well as the minimal concentration required to select thymidine-associated mutations (TAMs) are highly cell-dependent. The developed model allows studying various resistance mechanisms, inherent fitness effects, selection forces and epistasis based on microscopic kinetic data. It can readily be embedded in extended models of the complete HIV-1 reverse transcription process, or analogous processes in other viruses and help to guide drug development and improve our understanding of the mechanisms of resistance development during treatment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.