Background:  Previous studies have shown that inhibitory potential of antiviral drugs is strongly dependent on the dose-response curve slope (m) or Hill coefficient. Strikingly, slope values are class-specific for antiviral drugs. Nucleoside reverse transcriptase inhibitors (NRTI) and integrase inhibitors (II) have m ~1, while non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) unexpectedly exhibit m >1 even though their enzyme targets are univalent for the inhibitors. To understand this unique form of intermolecular cooperativity, we developed a multiple equilibrium model which is based on the mass action law, but envisions independent binding of multiple molecules of drug to a set of identical targets within each virus or virus-infected cell. We hypothesized that an m >1 results from participation of multiple copies of the drug target (n_T) in a relevant step of virus life cycle and that infection cannot proceed unless some critical number (c) of these n_T target molecules are unoccupied by drug.

Methods:  Using a single round infectivity assay in primary CD4⁺ T lymphoblasts, we tested this model by modulating the number of active enzyme molecules per virus and measuring the shift of dose-response curves for the relevant drugs against these modulated viruses. Dose-response curves were fitted into the multiple equilibrium model with least squares regression analysis.

Results:  We show that the estimated n_T and c values for the relevant enzymes predict m ~1.7 for NNRTI and m >1.8 for PI based on the model. We further show that compared to wild-type viruses, viruses with less reverse transcriptase (RT) show similar or slightly increased susceptibility to NNRTI, whereas viruses with less protease show dramatically increased susceptibility to PI. This phenomenon is consistent with the fractional occupancy of RT or protease required for inhibiting virus replication. In contrast, the IC₅₀ and m for NRTI and II remain unchanged against modulated viruses, since they target a reaction in which n_T = c = 1.

Conclusions:  The multiple equilibrium model predicts m >1 without postulating direct interaction between binding sites. Instead, the critical requirement is the participation of multiple copies of a drug target in the relevant step in the life cycle, and that the fractional occupancy of the drug target determines whether that step is completed. These results have profound implications for antiviral drug and vaccine development.