The Impact of Individual Human Immunodeficiency Virus Type 1 Protease Mutations on Drug Susceptibility Is Highly Influenced by Complex Interactions with the Background Protease Sequence

The requirement for multiple mutations for protease inhibitor (PI) resistance necessitates a better understanding of the molecular basis of resistance development. The novel bioinformatics resistance determination approach presented here elaborates on genetic profiles observed in clinical human immunodeficiency virus type 1 (HIV-1) isolates. Synthetic protease sequences were cloned in a wild-type HIV-1 background to generate a large number of close variants, covering 69 mutation clusters between multi-PI-resistant viruses and their corresponding genetically closely related, but PI-susceptible, counterparts. The vast number of mutants generated facilitates a profound and broad analysis of the influence of the background on the effect of individual PI resistance-associated mutations (PI-RAMs) on PI susceptibility. Within a set of viruses, all PI-RAMs that differed between susceptible and resistant viruses were varied while maintaining the background sequence from the resistant virus. The PI darunavir was used to evaluate PI susceptibility. Single sets allowed delineation of the impact of individual mutations on PI susceptibility, as well as the influence of PI-RAMs on one another. Comparing across sets, it could be inferred how the background influenced the interaction between two mutations, in some cases even changing antagonistic relationships into synergistic ones or vice versa. The approach elaborates on patient data and demonstrates how the specific mutational background greatly influences the impact of individual mutations on PI susceptibility in clinical patterns.The clinical use of protease inhibitors (PIs) for the treatment of human immunodeficiency virus (HIV) infection has led to a remarkable decline in HIV-1-related morbidity and mortality, and PIs are now a cornerstone of highly active antiretroviral therapy (14). However, the clinical benefit of PIs is limited by several factors, including long-term safety and tolerability, resistance development, and drug-drug interactions.The combination of extremely high levels of virus production and a high mutation rate is resulting in a growing resistance to anti-HIV drugs, making these less effective over time (1). In addition, an increasing proportion of primary infections involve the transmission of resistant viruses, including strains with reduced susceptibility to approved PIs (17). Therefore, patients need to be monitored for development of drug resistance, and treatment regimens have to be adapted accordingly. Most currently approved PIs are based on similar chemical structures, and therefore extensive cross-resistance can occur (7).In order to investigate the molecular basis of resistance development, we used the PI darunavir (DRV) as a model. DRV, previously known as TMC114, was approved in 2006 for the treatment of highly experienced patients and in 2008 for treatment of naïve patients. DRV has a high in vitro and in vivo potency against wild-type (WT) HIV, and this activity is maintained against HIV variants that are highly cross-resistant to other licensed PIs (2, 15). Moreover, there appears to be a very high genetic barrier to the development of resistance to DRV (3). A diminished virological response to DRV was only observed at week 24 (POWER studies [4]), when at least three specific baseline protease mutations (of V11I, V32I, L33F, I47V, I50V, I54L/M, G73S, L76V, I84V, and L89V) occurred in a background containing multiple protease mutations (median of at least 10 International AIDS Society-USA [IAS-USA] PI resistance-associated mutations [PI-RAMs] [11]).Mutations can interact as part of higher-order networks in complex and frequently overlapping patterns (7, 16, 18). In such patterns, the effect of an individual protease mutation on drug susceptibility depends on the presence of other mutations, PI-RAMs as well as background mutations. Many of the background mutations act synergistically with PI-RAMs and increase resistance to specific drugs. In addition, some of these mutations favor the development of other drug resistance mutations, thus lowering the genetic barrier to the development of PI resistance. In contrast, some mutations in the mutational background antagonize the effects of an individual PI-RAM. As resistance mutations are usually associated with reduced viral fitness, it may be that certain background mutations could (partly) compensate for this (12).In order to design drugs with high genetic barriers to resistance, a full understanding of the molecular basis of resistance development is needed. This includes the complex interplay between resistance mutations that can be studied only by exploring genetically close variants. Because of the high variability of HIV, it is difficult to find the genetically related variants required for such a study in patient databases, even if they contain sequences from thousands of virus isolates. Traditional approaches utilizing site-directed mutagenesis to create close variants by modifying the protease amino acids in existing viruses are feasible only on a small scale. The advent of mature gene assembly technologies makes the large-scale generation of closely related variants practicable. Here we describe a novel approach, bioinformatics resistance determination (BIRD), in which we created PI resistance sets between viral genotypes observed in patient samples. By varying a specific set of mutations in an invariable genetic background, the complex interactions between these mutations could be carefully dissected. Our studies illustrate how some mutations do not influence other mutations, while other changes act synergistically or antagonistically toward a specific RAM. Moreover, by comparing sets, we show how a specific background can alter the interplay between mutations.