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American Society for Microbiology, Antimicrobial Agents and Chemotherapy, 2(59), p. 838-848, 2015

DOI: 10.1128/aac.04163-14

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A Cell-Based Strategy To Assess Intrinsic Inhibition Efficiencies of HIV-1 Reverse Transcriptase Inhibitors

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

ABSTRACTDuring HIV-1 reverse transcription, there are increasing opportunities for nucleos(t)ide (NRTI) or nonnucleoside (NNRTI) reverse transcriptase (RT) inhibitors to stop elongation of the nascent viral DNA (vDNA). In addition, RT inhibitors appear to influence the kinetics of vDNA synthesis differently. While cell-free kinetic inhibition constants have provided detailed mechanistic insight, these assays are dependent on experimental conditions that may not mimic the cellular milieu. Here we describe a novel cell-based strategy to provide a measure of the intrinsic inhibition efficiencies of clinically relevant RT inhibitors on a per-stop-site basis. To better compare inhibition efficiencies among HIV-1 RT inhibitors that can stop reverse transcription at any number of different stop sites, their basic probability,p, of getting stopped at any potential stop site was determined. A relationship between qPCR-derived 50% effective inhibitory concentrations (EC50s) and this basic probability enabled determination ofpby successive approximation. On a per-stop-site basis, tenofovir (TFV) exhibited 1.4-fold-greater inhibition efficiency than emtricitabine (FTC), and as a class, both NRTIs exhibited an 8- to 11-fold greater efficiency than efavirenz (EFV). However, as more potential stops sites were considered, the probability of reverse transcription failing to reach the end of the template approached equivalence between both classes of RT inhibitors. Overall, this novel strategy provides a quantitative measure of the intrinsic inhibition efficiencies of RT inhibitors in the natural cellular milieu and thus may further understanding of drug efficacy. This approach also has applicability for understanding the impact of viral polymerase-based inhibitors (alone or in combination) in other virus systems.