Dose-response curve slope is a missing dimension in the analysis of HIV-1 drug resistance

Abstract

HIV-1 drug resistance is a major clinical problem. Resistance is evaluated using in vitro assays measuring the fold change in IC(50) caused by resistance mutations. Antiretroviral drugs are used at concentrations above IC(50), however, and inhibition at clinical concentrations can only be predicted from IC(50) if the shape of the dose-response curve is also known. Curve shape is influenced by cooperative interactions and is described mathematically by the slope parameter or Hill coefficient (m). Implicit in current analysis of resistance is the assumption that mutations shift dose-response curves to the right without affecting the slope. We show here that m is altered by resistance mutations. For reverse transcriptase and fusion inhibitors, single resistance mutations affect both slope and IC(50). For protease inhibitors, single mutations primarily affect slope. For integrase inhibitors, only IC(50) is affected. Thus, there are fundamental pharmacodynamic differences in resistance to different drug classes. Instantaneous inhibitory potential (IIP), the log inhibition of single-round infectivity at clinical concentrations, takes into account both slope and IC(50), and thus provides a direct measure of the reduction in susceptibility produced by mutations and the residual activity of drugs against resistant viruses. The standard measure, fold change in IC(50), does not correlate well with changes in IIP when mutations alter slope. These results challenge a fundamental assumption underlying current analysis of HIV-1 drug resistance and suggest that a more complete understanding of how resistance mutations reduce antiviral activity requires consideration of a previously ignored parameter, the dose-response curve slope.

Fig. 1.

Analysis of HIV-1 drug resistance mutations requires a consideration of dose–response curve slope. (A) Standard semilog dose–response curves for representative drugs from five different classes of antiretrovirals. Drugs were tested for inhibition of WT (blue curves) and mutant viruses bearing the indicated drug resistance mutations in a single-round infectivity assay. The fraction of infection events that remain unaffected (f_u) by the indicated D is shown. Error bars represent SE. The peach-shaded region indicates the clinical concentration range of the relevant drug. f_u = 0.5 (dotted line) indicates IC₅₀ for each drug. Note that the D axis for 3TC and RAL is shifted by 1 log relative to the other drugs. (B) Log-log plots of the dose–response curves from A. IC₅₀ for each drug can be determined from the points where the curves intersect log f_u = −0.3 (dotted line). Error bars represent SE. (C) Median effect plots of the dose–response curves from A. IC₅₀ for each drug can be determined from the points where the curves intersect log (fa/fu) = 0 (dotted line). The m value is the actual slope of the median effect plot. Error bars represent SE. (D) IIP for WT and mutant viruses at the indicated D. IIP was computed using Eq. 3 and the measured IC₅₀ and m. (E) Selective advantage (written as 1 + s, where s is the selection coefficient) is the ratio of the infectivity of a preexisting mutant virus to the infectivity of WT at the indicated D. The blue shading indicates regions where mutant viruses have selective advantage. ENF, enfuvirtide.

Fig. 2.

Effect of single drug resistance mutations on IC₅₀ (A), m (B), and IIP (C). IC₅₀ and m were determined for each mutant using median effect plots (Eq. 2) as previously described (33). The fractional change in IIP was computed as: 1 − (IIP_mutant /IIP_WT). IIP values for WT and mutant viruses were computed using Eq. 3 and the reported D at C_max (33). Drugs are grouped by class: NRTIs (blue shades), NNRTIs (red shades), PIs (green shades), fusion inhibitor (orange), and InSTIs (black and gray). Within each class, mutations are indicated by the shape of the symbol. ABC, abacavir; APV, amprenavir; AZT, zidovudine; d4T, stavudine; DRV, darunavir; ENF, enfuvirtide; ETV, etravirine; EVG, elvitegravir; FI, fusion inhibitor; FTC, emtricitabine; LPV, lopinavir; NFV, nelfinavir; NVP, nevirapine; SQV, saquinavir; TPV, tipranavir.

Fig. 3.

Correlation of fractional change in IIP with fold change in IC₅₀. (A) Relationship between fractional change in IIP C_max and fold change in IC₅₀ for integrase mutants with respect to RAL and elvitegravir (EVG). (B) Relationship between fractional change in IIP C_max and fold change in IC₅₀ for protease mutants with respect to LPV and IDV. LPV, lopinavir.

Fig. 4.

Residual IIP against resistant viruses. Bars indicate the IIP against WT and viruses carrying the indicated single drug resistance mutations at C_max. ABC, abacavir; APV, amprenavir; AZT, zidovudine; d4T, stavudine; DRV, darunavir; ENF, enfuvirtide; ETV, etravirine; EVG, elvitegravir; FI, fusion inhibitor; FTC, emtricitabine; LPV, lopinavir; NFV, nelfinavir; NVP, nevirapine; SQV, saquinavir; TPV, tipranavir.

Fig. 5.

Effect of mutations on replication capacity and selective advantage. (A) Replication capacity was determined as the ratio of the infectivity of resistant virus to the infectivity of WT. (B) Selective advantage of viruses bearing single resistance mutations in the presence of the indicated drugs at C_max. ABC, abacavir; APV, amprenavir; d4T, stavudine; DRV, darunavir; EFV, efavirenz; ENF, enfuvirtide; ETV, etravirine; EVG, elvitegravir; FTC, emtricitabine; LPV, lopinavir; NFV, nelfinavir; NVP, nevirapine; SQV, saquinavir; TPV, tipranavir.