Accessory Mutations Maintain Stability in Drug-Resistant HIV-1 Protease

The underlying mechanisms driving the evolution of drug resistance in human immunodeficiency virus (HIV) are only partially understood. We investigated the evolutionary cost of the major resistance mutations in HIV-1 protease in terms of protein stability. The accumulation of resistance mutations destabilizes the protease, limiting further adaptation. From an analysis of clinical isolates, we identified specific accessory mutations that were able to restore the stability of the protease or even increase it beyond the wild-type baseline. Resistance mutations were also found to decrease the activity of HIV protease near neutral pH values, while incorporating stabilizing mutations improved the enzyme's pH tolerance. These findings help us to explain the prevalence of mutations located far from the active site and underscore the importance of protein stability during the evolution of drug resistance in HIV.     

Identification of HCV protease inhibitor resistance mutations by selection pressure-based method

A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (K_a/K_s) to predict drug resistance mutations. Similar resistance analysis programs for HCV inhibitors are not currently available. Taking advantage of the recently available sequence data of patient HCV samples from a Phase II clinical study of protease inhibitor boceprevir, we calculated the selection pressure for all codons in the HCV protease region (amino acid 1–181) to identify potential resistance mutations. The correlation between mutations was also calculated to evaluate linkage between any two mutations. Using this approach, we identified previously known major resistant mutations, including a recently reported mutation V55A. In addition, a novel mutation V158I was identified, and we further confirmed its resistance to boceprevir in protease enzyme and replicon assay. We also extended the approach to analyze potential interactions between individual mutations and identified three pairs of correlated changes. Our data suggests that selection pressure-based analysis and correlation mapping could provide useful tools to analyze large amount of sequencing data from clinical samples and to identify new drug resistance mutations as well as their linkage and correlations.     

HIV protease as a target for retrovirus vector-mediated gene therapy

The dimeric aspartyl protease of HIV has been the subject of intense research for almost a decade. Knowledge of the substrate specificity and catalytic mechanism of this enzyme initially guided the development of several potent peptidomimetic small molecule inhibitors. More recently, the solution of the HIV protease structure led to the structure-based design of improved peptidomimetic and non-peptidomimetic antiviral compounds. Despite the qualified success of these inhibitors, the high mutation rate associated with RNA viruses continues to hamper the long-term clinical efficacy of HIV protease inhibitors. The dimeric nature of the viral protease has been conducive to the investigation of dominant-negative inhibitors of the enzyme. Some of these inhibitors are defective protease monomers that interact with functional monomers to form inactive protease heterodimers. An advantage of macromolecular inhibitors as compared to small-molecule inhibitors is the increased surface area of interaction between the inhibitor and the target gene product. Point mutations that preserve enzyme activity but confer resistance to small-molecule inhibitors are less likely to have an adverse effect on macromolecular interactions. The use of efficient retrovirus vectors has facilitated the delivery of these macromolecular inhibitors to primary human lymphocytes. The vector-transduced cells were less susceptible to HIV infection in vitro, and showed similar levels of protection compared to other macromolecular inhibitors of HIV replication, such as RevM10. These preliminary results encourage the further development of dominant-negative HIV protease inhibitors as a gene therapy-based antiviral strategy.     

Accessory mutations balance the marginal stability of the HIV-1 protease in drug resistance

The HIV-1 protease is a major target of inhibitor drugs in AIDS therapies. The therapies are impaired by mutations of the HIV-1 protease that can lead to resistance to protease inhibitors. These mutations are classified into major mutations, which usually occur first and clearly reduce the susceptibility to protease inhibitors, and minor, accessory mutations that occur later and individually do not substantially affect the susceptibility to inhibitors. Major mutations are predominantly located in the active site of the HIV-1 protease and can directly interfere with inhibitor binding. Minor mutations, in contrast, are typically located distal to the active site. A central question is how these distal mutations contribute to resistance development. In this article, we present a systematic computational investigation of stability changes caused by major and minor mutations of the HIV-1 protease. As most small single-domain proteins, the HIV-1 protease is only marginally stable. Mutations that destabilize the folded, active state of the protease therefore can shift the conformational equilibrium towards the unfolded, inactive state. We find that the most frequent major mutations destabilize the HIV-1 protease, whereas roughly half of the frequent minor mutations are stabilizing. An analysis of protease sequences from patients in treatment indicates that the stabilizing minor mutations are frequently correlated with destabilizing major mutations, and that highly resistant HIV-1 proteases exhibit significant fractions of stabilizing mutations. Our results thus indicate a central role of minor mutations in balancing the marginal stability of the protease against the destabilization induced by the most frequent major mutations.     

The linear interaction energy method for the prediction of protein stability changes upon mutation

The coupling of protein energetics and sequence changes is a critical aspect of computational protein design, as well as for the understanding of protein evolution, human disease, and drug resistance. To study the molecular basis for this coupling, computational tools must be sufficiently accurate and computationally inexpensive enough to handle large amounts of sequence data. We have developed a computational approach based on the linear interaction energy (LIE) approximation to predict the changes in the free-energy of the native state induced by a single mutation. This approach was applied to a set of 822 mutations in 10 proteins which resulted in an average unsigned error of 0.82 kcal/mol and a correlation coefficient of 0.72 between the calculated and experimental ΔΔG values. The method is able to accurately identify destabilizing hot spot mutations; however, it has difficulty in distinguishing between stabilizing and destabilizing mutations because of the distribution of stability changes for the set of mutations used to parameterize the model. In addition, the model also performs quite well in initial tests on a small set of double mutations. On the basis of these promising results, we can begin to examine the relationship between protein stability and fitness, correlated mutations, and drug resistance.     

Evaluating the potency of HIV-1 protease drugs to combat resistance

HIV-1 protease has been an important drug target for the antiretroviral treatment of HIV infection. The efficacy of protease drugs is impaired by the rapid emergence of resistant virus strains. Understanding the molecular basis and evaluating the potency of an inhibitor to combat resistance are no doubt important in AIDS therapy. In this study, we first identified residues that have significant contributions to binding with six substrates using molecular dynamics simulations and Molecular Mechanics Generalized Born Surface Area calculations. Among the critical residues, Asp25, Gly27, Ala28, Asp29, and Gly49 are well conserved, with which the potent drugs should form strong interactions. We then calculated the contribution of each residue to binding with eight FDA approved drugs. We analyzed the conservation of each protease residue and also compared the interaction between the HIV protease and individual residues of the drugs and substrates. Our analyses showed that resistant mutations usually occur at less conserved residues forming more favorable interactions with drugs than with substrates. To quantitatively integrate the binding free energy and conservation information, we defined an empirical parameter called free energy/variability (FV) value, which is the product of the contribution of a single residue to the binding free energy and the sequence variability at that position. As a validation, the FV value was shown to identify single resistant mutations with an accuracy of 88%. Finally, we evaluated the potency of a newly approved drug, darunavir, to combat resistance and predicted that darunavir is more potent than amprenavir but may be susceptible to mutations on Val32 and Ile84.     

Evolution of phenotypic drug susceptibility and viral replication capacity during long-term virologic failure of protease inhibitor therapy in human immunodeficiency virus-infected adults

Continued use of antiretroviral therapy despite the emergence of drug-resistant human immunodeficiency virus (HIV) has been associated with the durable maintenance of plasma HIV RNA levels below pretherapy levels. The factors that may account for this partial control of viral replication were assessed in a longitudinal observational study of 20 HIV-infected adults who remained on a stable protease inhibitor-based regimen despite ongoing viral replication (plasma HIV RNA levels consistently >500 copies/ml). Longitudinal plasma samples (n = 248) were assayed for drug susceptibility and viral replication capacity (measured by using a single-cycle recombinant-virus assay). The initial treatment-mediated decrease in plasma viremia was directly proportional to the reduction in replicative capacity (P = 0.01). Early virologic rebound was associated the emergence of a virus population exhibiting increased protease inhibitor phenotypic resistance, while replicative capacity remained low. During long-term virologic failure, plasma HIV RNA levels often remained stable or increased slowly, while phenotypic resistance continued to increase and replicative capacity decreased slowly. The emergence of primary genotypic mutations within protease (particularly V82A, I84V, and L90M) was temporally associated with increasing phenotypic resistance and decreasing replicative capacity, while the emergence of secondary mutations within protease was associated with more-gradual changes in both phenotypic resistance and replicative capacity. We conclude that HIV may be constrained in its ability to become both highly resistant and highly fit and that this may contribute to the continued partial suppression of plasma HIV RNA levels that is observed in some patients with drug-resistant viremia.     

Molecular dynamics study on drug resistance mechanism of HCV NS3/4A protease inhibitor: BI201335

Hepatitis C virus (HCV) infection is a serious threat to global health. NS3 serine protease is one of the most advanced HCV drug targets. However, the high mutation rate makes many protease inhibitors ineffective and allows viral replication to continue. To investigate the structural basis of the molecular mechanism of HCV resistance to inhibitors, molecular dynamics and molecular mechanics Poisson–Boltzmann/surface area calculations were carried out on HCV NS3 serine protease–BI201335 complexes. The drug resistance to BI201335 is explained by the fact that seven single mutations weaken the biological activity by lessening the sum of electrostatic interactions in the gas phase and polar solvation. The computational results demonstrate that the mutations affect the BI201335 binding through direct and indirect mechanisms. Seven single mutations lead to significant changes in the conformation, such as the shifts of the side chain of His57 and Lys136 and the movement of the P2 group of BI201335 towards the solvent. Furthermore, the contributions of Lys136 significantly decrease, which is the most major binding attraction. The shifts of the side chain of His57 induce the lack of hydrogen bond between His57 with Asp81 expert for D168G mutation. Detailing the molecular mechanisms of BI201335 drug resistance provides some helpful insights into the nature of mutational effect and aid the rational design of potent inhibitors combating HCV.     

Rapid enzymatic test for phenotypic HIV protease drug resistance

A phenotypic resistance test based on recombinant expression of the active HIV protease in E. coli from patient blood samples was developed. The protease is purified in a rapid one-step procedure as active enzyme and tested for inhibition by five selected synthetic inhibitors (amprenavir, indinavir, nelfinavir, ritonavir, and saquinavir) used presently for chemotherapy of HIV-infected patients. The HPLC system used in a previous approach was replaced by a continuous fluorogenic assay suitable for high-throughput screening on microtiter plates. This reduces significantly the total assay time and allows the determination of inhibition constants (Ki). The Michaelis constant (Km) and the inhibition constant (Ki) of recombinant wild-type protease agree well with published data for cloned HIV protease. The enzymatic test was evaluated with recombinant HIV protease derived from eight HIV-positive patients scored from 'sensitive' to 'highly resistant' according to mutations detected by genotypic analysis. The measured Ki values correlate well with the genotypic resistance scores, but allow a higher degree of differentiation. The non-infectious assay enables a more rapid yet sensitive detection of HIV protease resistance than other phenotypic assays.     

Characterization of a human immunodeficiency virus type 1 variant with reduced sensitivity to an aminodiol protease inhibitor.

Development of viral resistance to the aminodiol human immunodeficiency virus (HIV) protease inhibitor BMS 186,318 was studied by serial passage of HIV type 1 RF in MT-2 cells in the presence of increasing concentrations of compound. After 11 passages, an HIV variant that showed a 15-fold increase in 50% effective dose emerged. This HIV variant displays low-level cross-resistance to the C2 symmetric inhibitor A-77003 but remains sensitive to the protease inhibitors Ro 31-8959 and SC52151. Genetic analysis of the protease gene from a drug-resistant variant revealed an Ala-to-Thr change at amino acid residue 71 (A71T) and a Val-to-Ala change at residue 82 (V82A). To determine the effects of these mutations on protease and virus drug susceptibility, recombinant protease and proviral HIV type 1 clones containing the single mutations A71T and V82A or double mutation A71T/V82A were constructed. Subsequent drug sensitivity assays on the mutant proteases and viruses indicated that the V82A substitution was responsible for most of the resistance observed. Further genotypic analysis of the protease genes from earlier passages of virus indicated that the A71T mutation emerged prior to the V82A change. Finally, the level of resistance did not increase following continued passage in increasing concentrations of drug, and the resistant virus retained its drug susceptibility phenotype 34 days after drug withdrawal.     

Viability of a drug-resistant human immunodeficiency virus type 1 protease variant: structural insights for better antiviral therapy

Under the selective pressure of protease inhibitor therapy, patients infected with human immunodeficiency virus (HIV) often develop drug-resistant HIV strains. One of the first drug-resistant mutations to arise in the protease, particularly in patients receiving indinavir or ritonavir treatment, is V82A, which compromises the binding of these and other inhibitors but allows the virus to remain viable. To probe this drug resistance, we solved the crystal structures of three natural substrates and two commercial drugs in complex with an inactive drug-resistant mutant (D25N/V82A) HIV-1 protease. Through structural analysis and comparison of the protein-ligand interactions, we found that Val82 interacts more closely with the drugs than with the natural substrate peptides. The V82A mutation compromises these interactions with the drugs while not greatly affecting the substrate interactions, which is consistent with previously published kinetic data. Coupled with our earlier observations, these findings suggest that future inhibitor design may reduce the probability of the appearance of drug-resistant mutations by targeting residues that are essential for substrate recognition.     

Timing the Emergence of Resistance to Anti-HIV Drugs with Large Genetic Barriers

New antiretroviral drugs that offer large genetic barriers to resistance, such as the recently approved inhibitors of HIV-1 protease, tipranavir and darunavir, present promising weapons to avert the failure of current therapies for HIV infection. Optimal treatment strategies with the new drugs, however, are yet to be established. A key limitation is the poor understanding of the process by which HIV surmounts large genetic barriers to resistance. Extant models of HIV dynamics are predicated on the predominance of deterministic forces underlying the emergence of resistant genomes. In contrast, stochastic forces may dominate, especially when the genetic barrier is large, and delay the emergence of resistant genomes. We develop a mathematical model of HIV dynamics under the influence of an antiretroviral drug to predict the waiting time for the emergence of genomes that carry the requisite mutations to overcome the genetic barrier of the drug. We apply our model to describe the development of resistance to tipranavir in in vitro serial passage experiments. Model predictions of the times of emergence of different mutant genomes with increasing resistance to tipranavir are in quantitative agreement with experiments, indicating that our model captures the dynamics of the development of resistance to antiretroviral drugs accurately. Further, model predictions provide insights into the influence of underlying evolutionary processes such as recombination on the development of resistance, and suggest guidelines for drug design: drugs that offer large genetic barriers to resistance with resistance sites tightly localized on the viral genome and exhibiting positive epistatic interactions maximally inhibit the emergence of resistant genomes.     

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C

Although combination antiretroviral therapies seem to be effective at controlling HIV-1 infections regardless of the viral subtype, there is increasing evidence for subtype-specific drug resistance mutations. The order and rates at which resistance mutations accumulate in different subtypes also remain poorly understood. Most of this knowledge is derived from studies of subtype B genotypes, despite not being the most abundant subtype worldwide. Here, we present a methodology for the comparison of mutational networks in different HIV-1 subtypes, based on Hidden Conjunctive Bayesian Networks (H-CBN), a probabilistic model for inferring mutational networks from cross-sectional genotype data. We introduce a Monte Carlo sampling scheme for learning H-CBN models for a larger number of resistance mutations and develop a statistical test to assess differences in the inferred mutational networks between two groups. We apply this method to infer the temporal progression of mutations conferring resistance to the protease inhibitor lopinavir in a large cross-sectional cohort of HIV-1 subtype C genotypes from South Africa, as well as to a data set of subtype B genotypes obtained from the Stanford HIV Drug Resistance Database and the Swiss HIV Cohort Study. We find strong support for different initial mutational events in the protease, namely at residue 46 in subtype B and at residue 82 in subtype C. The inferred mutational networks for subtype B versus C are significantly different sharing only five constraints on the order of accumulating mutations with mutation at residue 54 as the parental event. The results also suggest that mutations can accumulate along various alternative paths within subtypes, as opposed to a unique total temporal ordering. Beyond HIV drug resistance, the statistical methodology is applicable more generally for the comparison of inferred mutational networks between any two groups.     

Resistance outside the substrate envelope: hepatitis C NS3/4A protease inhibitors

Direct acting antivirals have dramatically increased the efficacy and tolerability of hepatitis C treatment, but drug resistance has emerged with some of these inhibitors, including nonstructural protein 3/4?A protease inhibitors (PIs). Although many co-crystal structures of PIs with the NS3/4A protease have been reported, a systematic review of these crystal structures in the context of the rapidly emerging drug resistance especially for early PIs has not been performed. To provide a framework for designing better inhibitors with higher barriers to resistance, we performed a quantitative structural analysis using co-crystal structures and models of HCV NS3/4A protease in complex with natural substrates and inhibitors. By comparing substrate structural motifs and active site interactions with inhibitor recognition, we observed that the selection of drug resistance mutations correlates with how inhibitors deviate from viral substrates in molecular recognition. Based on this observation, we conclude that guiding the design process with native substrate recognition features is likely to lead to more robust small molecule inhibitors with decreased susceptibility to resistance.     

Sequencing-based detection of low-frequency human immunodeficiency virus type 1 drug-resistant mutants by an RNA/DNA heteroduplex generator-tracking assay

Drug-resistant viruses may be present as minority variants during early treatment failures or following discontinuation of failed antiretroviral regimens. A limitation of the traditional direct PCR population sequencing method is its inability to detect human immunodeficiency virus type 1 (HIV-1) variants present at frequencies lower than 20%. A drug resistance genotyping assay based on the isolation and DNA sequencing of minority HIV protease variants is presented here. A multiple-codon-specific heteroduplex generator probe was constructed to improve the separation of HIV protease genes varying in sequence at 12 codons associated with resistance to protease inhibitors. Using an RNA molecule as probe allowed the simple sequencing of protease variants isolated as RNA/DNA heteroduplexes with different electrophoretic mobilities. The protease gene RNA heteroduplex generator-tracking assay (RNA-HTA) was tested on plasma quasispecies from 21 HIV-1-infected persons in whom one or more protease resistance mutations emerged during therapy or following initiation of salvage regimens. In 11 of 21 cases, RNA-HTA testing of virus from the first episode of virologic failure identified protease resistance mutations not seen by population-based PCR sequencing. In 8 of these 11 cases, all of the low-frequency drug resistance mutations detected exclusively by RNA-HTA during the first episode became detectable by population-based PCR sequencing at the later time point. Distinct sets of protease mutations could be linked on different genomes in patients with high-frequency protease gene lineages. The enhanced detection of minority drug resistance variants using a sequencing-based assay may improve the efficacy of genotype-assisted salvage therapies.