Repository: Freie Universität Berlin, Math Department

Polymerase Inhibition by Nucleoside Analogs: Cellular- and Kinetic Parameters of Efficacy, Susceptibility and Resistance Selection

von Kleist, M. and Metzner, Ph. and Marquet, R. and Schütte, Ch. (2012) Polymerase Inhibition by Nucleoside Analogs: Cellular- and Kinetic Parameters of Efficacy, Susceptibility and Resistance Selection. Plos Computational Biology, 8 (1). e1002359.

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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 that resistance can be conferred by decreasing the NA incorporation rate, increasing its excision rate, or decreasing its affinity for the polymerase. We exemplify our approach for nucleoside inhibitors of HIV reverse transcriptase (NRTIs). For all analyzed NRTIs and their combinations, model-predicted macroscopic parameters (efficacy, fitness and toxicity) were consistent with observations. NA efficacy was found to greatly vary between distinct target cells. Surprisingly, target cells with low dNTP/NTP levels do not confer hyper-susceptibility to NA inhibition, whereas cells with high dNTP/NTP contents 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 found 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 and selection forces 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.

Item Type:Article
Subjects:Medicine and Dentistry > Pre-clinical Medicine
Mathematical and Computer Sciences > Mathematics > Mathematical Modelling
Biological Sciences > Microbiology > Virology
Subjects allied to Medicine > Pharmacology
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group
ID Code:1087
Deposited By: Dr Max von Kleist
Deposited On:02 Nov 2011 13:28
Last Modified:03 Mar 2017 14:41

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