Mutational patterns and correlated amino acid substitutions in the HIV-1 protease after virological failure to nelfinavir- and lopinavir/ritonavir-based treatments

Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations

Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy Δ G, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease.

Mechanism of Darunavir (DRV)'s High Genetic Barrier to HIV-1 Resistance: A Key V32I Substitution in Protease Rarely Occurs, but Once It Occurs, It Predisposes HIV-1 To Develop DRV Resistance

Darunavir (DRV) has bimodal activity against HIV-1 protease, enzymatic inhibition and protease dimerization inhibition, and has an extremely high genetic barrier against development of drug resistance. We previously generated a highly DRV-resistant HIV-1 variant (HIVDRVRP51). We also reported that four amino acid substitutions (V32I, L33F, I54M, and I84V) identified in the protease of HIVDRVRP51 are largely responsible for its high-level resistance to DRV. Here, we attempted to elucidate the role of each of the four amino acid substitutions in the development of DRV resistance. We found that V32I is a key substitution, which rarely occurs, but once it occurs, it predisposes HIV-1 to develop high-level DRV resistance. When two infectious recombinant HIV-1 clones carrying I54M and I84V (rHIVI54M and rHIVI84V, respectively) were selected in the presence of DRV, V32I emerged, and the virus rapidly developed high-level DRV resistance. rHIVV32I also developed high-level DRV resistance. However, wild-type HIVNL4-3 (rHIVWT) failed to acquire V32I and did not develop DRV resistance. Compared to rHIVWT, rHIVV32I was highly susceptible to DRV and had significantly reduced fitness, explaining why V32I did not emerge upon selection of rHIVWT with DRV. When the only substitution is at residue 32, structural analysis revealed much stronger van der Waals interactions between DRV and I-32 than between DRV and V-32. These results suggest that V32I is a critical amino acid substitution in multiple pathways toward HIV-1's DRV resistance development and elucidate, at least in part, a mechanism of DRV's high genetic barrier to development of drug resistance. The results also show that attention should be paid to the initiation or continuation of DRV-containing regimens in people with HIV-1 containing the V32I substitution.IMPORTANCE Darunavir (DRV) is the only protease inhibitor (PI) recommended as a first-line therapeutic and represents the most widely used PI for treating HIV-1-infected individuals. DRV possesses a high genetic barrier to development of HIV-1's drug resistance. However, the mechanism(s) of the DRV's high genetic barrier remains unclear. Here, we show that the preexistence of certain single amino acid substitutions such as V32I, I54M, A71V, and I84V in HIV-1 protease facilitates the development of high-level DRV resistance. Interestingly, all in vitro-selected highly DRV-resistant HIV-1 variants acquired V32I but never emerged in wild-type HIV (HIVWT), and V32I itself rendered HIV-1 more sensitive to DRV and reduced viral fitness compared to HIVWT, strongly suggesting that the emergence of V32I plays a critical role in the development of HIV-1's resistance to DRV. Our results would be of benefit in the treatment of HIV-1-infected patients receiving DRV-containing regimens.

Defective hydrophobic sliding mechanism and active site expansion in HIV-1 protease drug resistant variant Gly48Thr/Leu89Met: mechanisms for the loss of saquinavir binding potency

HIV drug resistance continues to emerge; consequently, there is an urgent need to develop next generation antiretroviral therapeutics.1 Here we report on the structural and kinetic effects of an HIV protease drug resistant variant with the double mutations Gly48Thr and Leu89Met (PR_G48T/L89M), without the stabilizing mutations Gln7Lys, Leu33Ile, and Leu63Ile. Kinetic analyses reveal that PR_G48T/L89M and PR_WT share nearly identical Michaelis–Menten parameters; however, PR_G48T/L89M exhibits weaker binding for IDV (41-fold), SQV (18-fold), APV (15-fold), and NFV (9-fold) relative to PR_WT. A 1.9 Å resolution crystal structure was solved for PR_G48T/L89M bound with saquinavir (PR_{G48T/L89M-SQV}) and compared to the crystal structure of PR_WT bound with saquinavir (PR_WT-SQV). PR_{G48T/L89M-SQV} has an enlarged active site resulting in the loss of a hydrogen bond in the S3 subsite from Gly48 to P3 of SQV, as well as less favorable hydrophobic packing interactions between P1 Phe of SQV and the S1 subsite. PR_{G48T/L89M-SQV} assumes a more open conformation relative to PR_WT-SQV, as illustrated by the downward displacement of the fulcrum and elbows and weaker interatomic flap interactions. We also show that the Leu89Met mutation disrupts the hydrophobic sliding mechanism by causing a redistribution of van der Waals interactions in the hydrophobic core in PR_{G48T/L89M-SQV}. Our mechanism for PR_{G48T/L89M-SQV} drug resistance proposes that a defective hydrophobic sliding mechanism results in modified conformational dynamics of the protease. As a consequence, the protease is unable to achieve a fully closed conformation that results in an expanded active site and weaker inhibitor binding.

Capacity building and predictors of success for HIV-1 drug resistance testing in the Asia-Pacific region and Africa

BACKGROUND

The TREAT Asia Quality Assessment Scheme (TAQAS) was developed as a quality assessment programme through expert education and training, for laboratories in the Asia-Pacific and Africa that perform HIV drug-resistance (HIVDR) genotyping. We evaluated the programme performance and factors associated with high-quality HIVDR genotyping.

METHODS

Laboratories used their standard protocols to test panels of human immunodeficiency virus (HIV)-positive plasma samples or electropherograms. Protocols were documented and performance was evaluated according to a newly developed scoring system, agreement with panel-specific consensus sequence, and detection of drug-resistance mutations (DRMs) and mixtures of wild-type and resistant virus (mixtures). High-quality performance was defined as detection of ≥95% DRMs.

RESULTS

Over 4.5 years, 23 participating laboratories in 13 countries tested 45 samples (30 HIV-1 subtype B; 15 non-B subtypes) in nine panels. Median detection of DRMs was 88-98% in plasma panels and 90-97% in electropherogram panels. Laboratories were supported to amend and improve their test outcomes as appropriate. Three laboratories that detected <80% DRMs in early panels demonstrated subsequent improvement. Sample complexity factors - number of DRMs (p<0.001) and number of DRMs as mixtures (p<0.001); and laboratory performance factors - detection of mixtures (p<0.001) and agreement with consensus sequence (p<0.001), were associated with high performance; sample format (plasma or electropherogram), subtype and genotyping protocol were not.

CONCLUSION

High-quality HIVDR genotyping was achieved in the TAQAS collaborative laboratory network. Sample complexity and detection of mixtures were associated with performance quality. Laboratories conducting HIVDR genotyping are encouraged to participate in quality assessment programmes.

Amino acid sequence coevolution in the insect bursicon ligand-receptor system

The pattern of amino acid residue replacement in the components of the bursicon signaling system (involving the BURSα/BURSβ heterodimer and its receptor BURSrec) was reconstructed across a phylogeny of 17 insect species, in order to test for the co-occurrence of replacements at sets of individual sites. Sets of three or more branches with perfectly concordant changes occurred to a greater extent than expected by chance, given the observed level of amino acid change. The latter sites (SPC sites) were found to have distinctive characteristics: (1) the mean number of changes was significantly lower at SPC sites than that at other sites with multiple changes; (2) SPC sites had a significantly greater tendency toward parallel amino acid changes than other sites with multiple changes, but no greater tendency toward convergent changes; and (3) parallel changes tended to involve relatively similar amino acids, as indicated by relatively low mean chemical distances. The results implicated functional constraint, permitting only a limited subset of amino acids in a given site, as a major factor in causing both parallel amino acid replacement and coordinated amino acid changes in different sites of the same protein and of interacting proteins in this system.

A multifaceted analysis of HIV-1 protease multidrug resistance phenotypes

Background

Great strides have been made in the effective treatment of HIV-1 with the development of second-generation protease inhibitors (PIs) that are effective against historically multi-PI-resistant HIV-1 variants. Nevertheless, mutation patterns that confer decreasing susceptibility to available PIs continue to arise within the population. Understanding the phenotypic and genotypic patterns responsible for multi-PI resistance is necessary for developing PIs that are active against clinically-relevant PI-resistant HIV-1 variants.

Results

In this work, we use globally optimal integer programming-based clustering techniques to elucidate multi-PI phenotypic resistance patterns using a data set of 398 HIV-1 protease sequences that have each been phenotyped for susceptibility toward the nine clinically-approved HIV-1 PIs. We validate the information content of the clusters by evaluating their ability to predict the level of decreased susceptibility to each of the available PIs using a cross validation procedure. We demonstrate the finding that as a result of phenotypic cross resistance, the considered clinical HIV-1 protease isolates are confined to ~6% or less of the clinically-relevant phenotypic space. Clustering and feature selection methods are used to find representative sequences and mutations for major resistance phenotypes to elucidate their genotypic signatures. We show that phenotypic similarity does not imply genotypic similarity, that different PI-resistance mutation patterns can give rise to HIV-1 isolates with similar phenotypic profiles.

Conclusion

Rather than characterizing HIV-1 susceptibility toward each PI individually, our study offers a unique perspective on the phenomenon of PI class resistance by uncovering major multidrug-resistant phenotypic patterns and their often diverse genotypic determinants, providing a methodology that can be applied to understand clinically-relevant phenotypic patterns to aid in the design of novel inhibitors that target other rapidly evolving molecular targets as well.

The impact of the nelfinavir resistance-conferring mutation D30N on the susceptibility of HIV-1 subtype B to other protease inhibitors

The human immunodeficiency virus type 1 (HIV-1) protease mutation D30N is exclusively selected by the protease inhibitor (PI) nelfinavir and confers resistance to this drug. We demonstrate that D30N increases the susceptibility to saquinavir (SQV) and amprenavir in HIV-1 subtype B isolates and that the N88D mutation in a D30N background neutralizes this effect. D30N also suppresses indinavir (IDV) resistance caused by the M46I mutation. Interestingly, in patients with viruses originally containing the D30N mutation who were treated with IDV or SQV, the virus either reversed this mutation or acquired N88D, suggesting an antagonistic effect of D30N upon exposure to these PIs. These findings can improve direct salvage drug treatment in resource limited countries where subtype B is epidemiologically important and extend the value of first and second line PIs in these populations.

Resolution of discordant HIV-1 protease resistance rankings using molecular dynamics simulations

The emergence of drug resistance is a major challenge for the effective treatment of HIV. In this article, we explore the application of atomistic molecular dynamics simulations to quantify the level of resistance of a patient-derived HIV-1 protease sequence to the inhibitor lopinavir. A comparative drug ranking methodology was developed to compare drug resistance rankings produced by the Stanford HIVdb, ANRS, and RegaDB clinical decision support systems. The methodology was used to identify a patient sequence for which the three rival online tools produced differing resistance rankings. Mutations at only three positions ( L10I , A71IV, and L90M ) influenced the resistance level assigned to the sequence. We use ensemble molecular dynamics simulations to elucidate the origin of these discrepancies and the mechanism of resistance. By simulating not only the full patient sequences but also systems containing the constituent mutations, we gain insight into why resistance estimates vary and the interactions between the various mutations. In the same way, we also gain valuable knowledge of the mechanistic causes of resistance. In particular, we identify changes in the relative conformation of the two beta sheets that form the protease dimer interface which suggest an explanation of the relative frequency of different amino acids observed in patients at residue 71.

Lopinavir/Ritonavir: a review of its use in the management of HIV-1 infection

Lopinavir/ritonavir (Kaletra®) is an orally administered coformulated ritonavir-boosted protease inhibitor (PI) comprising lopinavir and low-dose ritonavir. It is indicated, in combination with other antiretroviral agents, for the treatment of HIV-1 infection in adults, adolescents and children. Lopinavir/ritonavir is available as a tablet, soft-gel capsule and an oral solution for patients with difficulty swallowing. In well designed, randomized clinical trials, lopinavir/ritonavir, in combination with other antiretroviral therapies (ART), provided durable virological suppression and improved immunological outcomes in both ART-naive and -experienced adult patients with virological failure. Furthermore, lopinavir/ritonavir demonstrated a high barrier to the development of resistance in ART-naive patients. More limited data indicate that it is effective in reducing plasma HIV-1 RNA levels in paediatric patients. Lopinavir/ritonavir has served as a well established benchmark comparator for the noninferiority of other ritonavir-boosted PI regimens. Although generally well tolerated, lopinavir/ritonavir is associated with generally manageable adverse gastrointestinal side effects and hypertriglyceridaemia and hypercholesterolaemia, which may require coadministration of lipid-lowering agents to reduce the risk of coronary heart disease. Lopinavir/ritonavir, in combination with other ART agents, is a well established and cost-effective treatment for both ART-naive and -experienced patients with HIV-1 infection and, with successful management of adverse events, continues to have a role as an effective component of ART regimens for the control of HIV-1 infection.

Alternative methods to analyse the impact of HIV mutations on virological response to antiviral therapy

Background

Principal component analysis (PCA) and partial least square (PLS) regression may be useful to summarize the HIV genotypic information. Without pre-selection each mutation presented in at least one patient is considered with a different weight. We compared these two strategies with the construction of a usual genotypic score.

Methods

We used data from the ANRS-CO3 Aquitaine Cohort Zephir sub-study. We used a subset of 87 patients with a complete baseline genotype and plasma HIV-1 RNA available at baseline and at week 12. PCA and PLS components were determined with all mutations that had prevalences >0. For the genotypic score, mutations were selected in two steps: 1) p-value < 0.01 in univariable analysis and prevalences between 10% and 90% and 2) backwards selection procedure based on the Cochran-Armitage Test. The predictive performances were compared by means of the cross-validated area under the receiver operating curve (AUC).

Results

Virological failure was observed in 46 (53%) patients at week 12. Principal components and PLS components showed a good performance for the prediction of virological response in HIV infected patients. The cross-validated AUCs for the PCA, PLS and genotypic score were 0.880, 0.868 and 0.863, respectively. The strength of the effect of each mutation could be considered through PCA and PLS components. In contrast, each selected mutation contributes with the same weight for the calculation of the genotypic score. Furthermore, PCA and PLS regression helped to describe mutation clusters (e.g. 10, 46, 90).

Conclusion

In this dataset, PCA and PLS showed a good performance but their predictive ability was not clinically superior to that of the genotypic score.

Coordinated evolution of the hepatitis C virus

Hepatitis C virus is a genetically heterogeneous RNA virus that is a major cause of liver disease worldwide. Here, we show that, despite its extensive heterogeneity, the evolution of hepatitis C virus is primarily shaped by negative selection and that numerous coordinated substitutions in the polyprotein can be organized into a scale-free network whose degree of connections between sites follows a power-law distribution. This network shares all major properties with many complex biological and technological networks. The topological structure and hierarchical organization of this network suggest that a small number of amino acid sites exert extensive impact on hepatitis C virus evolution. Nonstructural proteins are enriched for negatively selected sites of high centrality, whereas structural proteins are enriched for positively selected sites located in the periphery of the network. The complex network of coordinated substitutions is an emergent property of genetic systems with implications for evolution, vaccine research, and drug development. In addition to such properties as polymorphism or strength of selection, the epistatic connectivity mapped in the network is important for typing individual sites, proteins, or entire genetic systems. The network topology may help devise molecular intervention strategies for disrupting viral functions or impeding compensatory changes for vaccine escape or drug resistance mutations. Also, it may be used to find new therapeutic targets, as suggested in this study for the NS4A protein, which plays an important role in the network.

HIV-1 protease inhibitors: effects on HIV-2 replication and resistance

Novel antiretroviral drugs include protease (PR) inhibitors (e.g. atazanavir, tipranavir and darunavir) that block HIV-1 maturation and show remarkable antiviral potency on drug-resistant isolates. However, the strains used as prototypes in the design of the novel drugs belong to a specific clade (i.e. HIV-1 group M subtype B), which is the most prevalent in developed countries. At the same time, there is an increasing concern about the expansion of other HIV-1 clades as well as other related retroviruses, such as HIV-2. The HIV-2 PR is weakly inhibited by some PR inhibitors (e.g. amprenavir), and little is known of the mutational pathways leading to drug resistance in this virus. The design of specific PR inhibitors targeting HIV-2, or potent drugs showing broad specificity on HIV-1 and HIV-2 clades, remains a major challenge for the future.