Gag-protease coevolution shapes the outcome of lopinavir-inclusive treatment regimens in chronically infected HIV-1 subtype C patients

HIV-1 envelope facilitates the development of protease inhibitor resistance through acquiring mutations associated with viral entry and immune escape

Introduction

There is increasing evidence supporting a role for HIV-1 envelope in the development of Protease Inhibitor drug resistance, and a recent report from our group suggested that Env mutations co-evolve with Gag-Protease mutations in the pathway to Lopinavir resistance. In this study, we investigated the effect of co-evolving Env mutations on virus function and structure.

Methods

Co-receptor usage and n-linked glycosylation were investigated using Geno2Pheno as well as tools available at the Los Alamos sequence database. Molecular dynamics simulations were performed using Amber 18 and analyzed using Cpptraj, and molecular interactions were calculated using the Ring server.

Results

The results showed that under Protease Inhibitor drug selection pressure, the envelope gene modulates viral entry by protecting the virus from antibody recognition through the increased length and number of N-glycosylation sites observed in V1/V2 and to some extent V5. Furthermore, gp120 mutations appear to modulate viral entry through a switch to the CXCR4 coreceptor, induced by higher charge in the V3 region and specific mutations at the coreceptor binding sites. In gp41, S534A formed a hydrogen bond with L602 found in the disulfide loop region between the Heptad Repeat 1 and Heptad Repeat 2 domains and could negatively affect the association of gp120-gp41 during viral entry. Lastly, P724Q/S formed both intermolecular and intramolecular interactions with residues within the Kennedy loop, a known epitope.

Discussion

In conclusion, the results suggest that mutations in envelope during Protease Inhibitor treatment failure are related to immune escape and that S534A mutants could preferentially use the cell-to-cell route of infection.

Understanding the co-evolutionary molecular mechanisms of resistance in the HIV-1 Gag and protease

Due to high human immunodeficiency virus type 1 (HIV-1) subtype C infections coupled with increasing antiretroviral treatment failure, the elucidation of complex drug resistance mutational patterns arising through protein co-evolution is required. Despite the inclusion of potent protease inhibitors Lopinavir (LPV) and Darunavir (DRV) in second- and third-line therapies, many patients still fail treatment due to the accumulation of mutations in protease (PR) and recently, Gag. To understand the co-evolutionary molecular mechanisms of resistance in the HIV-1 PR and Gag, we performed 100 ns molecular dynamic simulations on multidrug resistant PR's when bound to LPV, DRV or a mutated A431V NC|p1 Gag cleavage site (CS). Here we showed that distinct changes in PR's active site, flap and elbow regions due to several PR resistance mutations (L10F, M46I, I54V, L76V, V82A) were found to alter LPV and DRV drug binding. However, binding was significantly exacerbated when the mutant PRs were bound to the NC|p1 Gag CS. Although A431V was shown to coordinate several residues in PR, the L76V PR mutation was found to have a significant role in substrate recognition. Consequently, a greater binding affinity was observed when the mutated substrate was bound to an L76V-inclusive PR mutant (G_bind: -62.46 ± 5.75 kcal/mol) than without (Gbind: -50.34 ± 6.28 kcal/mol). These data showed that the co-selection of resistance mutations in the enzyme and substrate can simultaneously constrict regions in PR's active site whilst flexing the flaps to allow flexible movement of the substrate and multiple, complex mechanisms of resistance to occur. Communicated by Ramaswamy H. Sarma.

HIV-1 protease with 10 lopinavir and darunavir resistance mutations exhibits altered inhibition, structural rearrangements and extreme dynamics

Antiretroviral drug resistance is a therapeutic obstacle for people with HIV. HIV protease inhibitors darunavir and lopinavir are recommended for resistant infections. We characterized a protease mutant (PR10x) derived from a highly resistant clinical isolate including 10 mutations associated with resistance to lopinavir and darunavir. Compared to the wild-type protease, PR10x exhibits ∼3-fold decrease in catalytic efficiency and Ki values of 2-3 orders of magnitude worse for darunavir, lopinavir, and potent investigational inhibitor GRL-519. Crystal structures of the mutant were solved in a ligand-free form and in complex with GRL-519. The structures show altered interactions in the active site, flap-core interface, hydrophobic core, hinge region, and 80s loop compared to the corresponding wild-type protease structures. The ligand-free crystal structure exhibits a highly curled flap conformation which may amplify drug resistance. Molecular dynamics simulations performed for 1 μs on ligand-free dimers showed extremely large fluctuations in the flaps for PR10x compared to equivalent simulations on PR with a single L76V mutation or wild-type protease. This analysis offers insight about the synergistic effects of mutations in highly resistant variants.

The HIV-1 Gag Protein Displays Extensive Functional and Structural Roles in Virus Replication and Infectivity

Once merely thought of as the protein responsible for the overall physical nature of the human immunodeficiency virus type 1 (HIV-1), the Gag polyprotein has since been elucidated to have several roles in viral replication and functionality. Over the years, extensive research into the polyproteins' structure has revealed that Gag can mediate its own trafficking to the plasma membrane, it can interact with several host factors and can even aid in viral genome packaging. Not surprisingly, Gag has also been associated with HIV-1 drug resistance and even treatment failure. Therefore, this review provides an extensive overview of the structural and functional roles of the HIV-1 Gag domains in virion integrity, functionality and infectivity.

Potential Associations of Mutations within the HIV-1 Env and Gag Genes Conferring Protease Inhibitor (PI) Drug Resistance

An increasing number of patients in Africa are experiencing virological failure on a second-line antiretroviral protease inhibitor (PI)-containing regimen, even without resistance-associated mutations in the protease region, suggesting a potential role of other genes in PI resistance. Here, we investigated the prevalence of mutations associated with Lopinavir/Ritonavir (LPV/r) failure in the Envelope gene and the possible coevolution with mutations within the Gag-protease (gag-PR) region. Env and Gag-PR sequences generated from 24 HIV-1 subtype C infected patients failing an LPV/r inclusive treatment regimen and 344 subtype C drug-naïve isolates downloaded from the Los Alamos Database were analyzed. Fisher’s exact test was used to determine the differences in mutation frequency. Bayesian network probability was applied to determine the relationship between mutations occurring within the env and gag-PR regions and LPV/r treatment. Thirty-five mutations in the env region had significantly higher frequencies in LPV/r-treated patients. A combination of Env and Gag-PR mutations was associated with a potential pathway to LPV/r resistance. While Env mutations were not directly associated with LPV/r resistance, they may exert pressure through the Gag and minor PR mutation pathways. Further investigations using site-directed mutagenesis are needed to determine the impact of Env mutations alone and in combination with Gag-PR mutations on viral fitness and LPV/r efficacy.

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.

There is a disparity in the distribution of infections by HIV-1 subtype in the world. Subtype B is predominant in America, Australia and western and central Europe, and most therapeutic strategies are based on research and clinical studies on this subtype. However, non-B subtypes represent the majority of global HIV-1 infections; e.g., subtype C alone accounts for nearly half of all HIV-1 infections. We present a statistical framework enabling the comparison of patterns of accumulating mutations in different HIV-1 subtypes. Specifically, we compare the temporal ordering of lopinavir resistance mutations in HIV-1 subtypes B versus C. To this end, we combine the Hidden Conjunctive Bayesian Network (H-CBN) model with an approximate inference scheme enabling comparisons of larger networks. We show that the development of resistance to lopinavir differs significantly between subtypes B and C, such that findings based on subtype B sequences can not always be applied to sybtype C. The described methodology is suitable for comparing different subgroups in the context of other evolutionary processes.