A multifaceted analysis of HIV-1 protease multidrug resistance phenotypes

HIV and Drug-Resistant Subtypes

Acquired Immunodeficiency Syndrome (AIDS) is a human viral infectious disease caused by the positive-sense single-stranded (ss) RNA Human Immunodeficiency Virus (HIV) (Retroviridae family, Ortervirales order). HIV-1 can be distinguished into various worldwide spread groups and subtypes. HIV-2 also causes human immunodeficiency, which develops slowly and tends to be less aggressive. HIV-2 only partially homologates to HIV-1 despite the similar derivation. Antiretroviral therapy (ART) is the treatment approved to control HIV infection, based on multiple antiretroviral drugs that belong to different classes: (i) NNRTIs, (ii) NRTIs, (iii) PIs, (iv) INSTIs, and (v) entry inhibitors. These drugs, acting on different stages of the HIV life cycle, decrease the patient's total burden of HIV, maintain the function of the immune system, and prevent opportunistic infections. The appearance of several strains resistant to these drugs, however, represents a problem today that needs to be addressed as best as we can. New outbreaks of strains show a widespread geographic distribution and a highly variable mortality rate, even affecting treated patients significantly. Therefore, novel treatment approaches should be explored. The present review discusses updated information on HIV-1- and HIV-2-resistant strains, including details on different mutations responsible for drug resistance.

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

MOTIVATION

Commonly, protease inhibitor failure is characterized by the development of multiple protease resistance mutations (PRMs). While the impact of PRMs on therapy failure are understood, the introduction of Gag mutations with protease remains largely unclear.

RESULTS

Here, we utilized phylogenetic analyses and Bayesian network learning as tools to understand Gag-protease coevolution and elucidate the pathways leading to Lopinavir failure in HIV-1 subtype C infected patients. Our analyses indicate that while PRMs coevolve in response to drug selection pressure within protease, the Gag mutations added to the existing network while specifically interacting with known Lopinavir failure PRMs. Additionally, the selection of mutations at specific positions in Gag-protease suggests that these coevolving mutational changes occurs to maintain structural integrity during Gag cleavage.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pharmacokinetic Parameters of HIV-1 Protease Inhibitors

Since the beginning of the HIV epidemic, research has been carried out to control the virus. Understanding the mechanisms of replication has given access to the various classes of drugs that over time have transformed AIDS into a manageable chronic disease. The class of protease inhibitors (PIs) gained notice in anti-retroviral therapy, once it was found that peptidomimetic molecules act by blocking the active catalytic center of the aspartic protease, which is directly related to HIV maturation. However, mutations in enzymatic internal residues are the biggest issue for these drugs, because a small change in biochemical interaction can generate resistance. Low plasma concentrations of PIs favor viral natural selection; high concentrations can inhibit even partially resistant enzymes. Food-drug/drug-drug interactions can decrease the bioavailability of PIs and are related to many side effects. Therefore, this review summarizes the pharmacokinetic properties of current PIs, the changes when pharmacological boosters are used and also lists the major mutations to help understanding of how long the continuous treatment can ensure a low viral load in patients.

Surveillance of transmitted HIV drug resistance among newly diagnosed, treatment-naive individuals at a county HIV clinic in Santa Clara County

Introduction

To our knowledge, HIV transmitted drug resistance (TDR) patterns have not been characterized specifically in Santa Clara County (SCC), California, one of the largest counties by population in the United States. Understanding TDR here will help improve antiretroviral therapy outcomes and prevent future transmission events.

Material and methods

This is a retrospective analysis of TDR among patients establishing care at a county HIV clinic at the Santa Clara Valley Health and Hospital System. We identified 206 treatment-naive individuals who were newly diagnosed with HIV between 2006-2013. Using these individuals, we assessed the prevalence and temporal trends of total TDR and TDR to nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and integrase strand transfer inhibitors (INSTIs).

Results

We identified a total TDR prevalence of 17.5% during 2006–2013 (7.3% NNRTI, 6.8% NRTI, 2.4% PI, 2.9% INSTI) with 1.9% exhibiting dual-class resistance. Total TDR prevalence initially ranged between 19.0-22.7% during 2006–2008 and decreased to within 10.5–16.2% during 2011–2013, though this decrease was not significant (p = 0.42). NRTI TDR decreased from 22.7% in 2006 to 5.3% in 2013 (p = 0.02), and NNRTI TDR appeared to fluctuate between 2.7-13.5% (p = 0.96). PI and INSTI TDR remained low, with noted E138A prevalence of 2.9%.

Conclusions

The prevalence of TDR was substantial among newly diagnosed, treatment-naive individuals establishing care at a SCC-based county HIV clinic from 2006 to 2013. This, along with the presence of transmitted mutations associated with INSTI resistance, warrants continued surveillance of TDR in SCC and use of baseline genotyping prior to antiretroviral therapy initiation.

Highly resistant HIV-1 proteases and strategies for their inhibition

The virally encoded protease is an important drug target for AIDS therapy. Despite the potency of the current drugs, infections with resistant viral strains limit the long-term effectiveness of therapy. Highly resistant variants of HIV protease from clinical isolates have different combinations of about 20 mutations and several orders of magnitude worse binding affinity for clinical inhibitors. Strategies are being explored to inhibit these highly resistant mutants. The existing inhibitors can be modified by introducing groups with the potential to form new interactions with conserved protease residues, and the flexible flaps. Alternative strategies are discussed, including designing inhibitors to bind to the open conformation of the protease dimer, and inhibition of the protease-catalyzed processing of the Gag-Pol precursor.

Modelling ligand selectivity of serine proteases using integrative proteochemometric approaches improves model performance and allows the multi-target dependent interpretation of features

Serine proteases, implicated in important physiological functions, have a high intra-family similarity, which leads to unwanted off-target effects of inhibitors with insufficient selectivity. However, the availability of sequence and structure data has now made it possible to develop approaches to design pharmacological agents that can discriminate successfully between their related binding sites. In this study, we have quantified the relationship between 12,625 distinct protease inhibitors and their bioactivity against 67 targets of the serine protease family (20,213 data points) in an integrative manner, using proteochemometric modelling (PCM). The benchmarking of 21 different target descriptors motivated the usage of specific binding pocket amino acid descriptors, which helped in the identification of active site residues and selective compound chemotypes affecting compound affinity and selectivity. PCM models performed better than alternative approaches (models trained using exclusively compound descriptors on all available data, QSAR) employed for comparison with R(2)/RMSE values of 0.64 ± 0.23/0.66 ± 0.20 vs. 0.35 ± 0.27/1.05 ± 0.27 log units, respectively. Moreover, the interpretation of the PCM model singled out various chemical substructures responsible for bioactivity and selectivity towards particular proteases (thrombin, trypsin and coagulation factor 10) in agreement with the literature. For instance, absence of a tertiary sulphonamide was identified to be responsible for decreased selective activity (by on average 0.27 ± 0.65 pChEMBL units) on FA10. Among the binding pocket residues, the amino acids (arginine, leucine and tyrosine) at positions 35, 39, 60, 93, 140 and 207 were observed as key contributing residues for selective affinity on these three targets.

Data-intensive analysis of HIV mutations

BACKGROUND

In this study, clustering was performed using a bitmap representation of HIV reverse transcriptase and protease sequences, to produce an unsupervised classification of HIV sequences. The classification will aid our understanding of the interactions between mutations and drug resistance. 10,229 HIV genomic sequences from the protease and reverse transcriptase regions of the pol gene and antiretroviral resistant related mutations represented in an 82-dimensional binary vector space were analyzed.

RESULTS

A new cluster representation was proposed using an image inspired by microarray data, such that the rows in the image represented the protein sequences from the genotype data and the columns represented presence or absence of mutations in each protein position.The visualization of the clusters showed that some mutations frequently occur together and are probably related to an epistatic phenomenon.

CONCLUSION

We described a methodology based on the application of a pattern recognition algorithm using binary data to suggest clusters of mutations that can easily be discriminated by cluster viewing schemes.

Polypharmacology modelling using proteochemometrics (PCM): recent methodological developments, applications to target families, and future prospects

Proteochemometric (PCM) modelling is a computational method to model the bioactivity of multiple ligands against multiple related protein targets simultaneously.

Identification of novel small molecules as inhibitors of hepatitis C virus by structure-based virtual screening

Hepatitis C virus (HCV) NS3/NS4A serine protease is essential for viral replication, which is regarded as a promising drug target for developing direct-acting anti-HCV agents. In this study, sixteen novel compounds with cell-based HCV replicon activity ranging from 3.0 to 28.2 μM (IC₅₀) were successfully identified by means of structure-based virtual screening. Compound 5 and compound 11, with an IC₅₀ of 3.0 μM and 5.1 μM, respectively, are the two most potent molecules with low cytotoxicity.

Prototypical Recombinant Multi-Protease-Inhibitor-Resistant Infectious Molecular Clones of Human Immunodeficiency Virus Type 1

The many genetic manifestations of HIV-1 protease inhibitor (PI) resistance present challenges to research into the mechanisms of PI resistance and the assessment of new PIs. To address these challenges, we created a panel of recombinant multi-PI-resistant infectious molecular clones designed to represent the spectrum of clinically relevant multi-PI-resistant viruses. To assess the representativeness of this panel, we examined the sequences of the panel's viruses in the context of a correlation network of PI resistance amino acid substitutions in sequences from more than 10,000 patients. The panel of recombinant infectious molecular clones comprised 29 of 41 study-defined PI resistance amino acid substitutions and 23 of the 27 tightest amino acid substitution clusters. Based on their phenotypic properties, the clones were classified into four groups with increasing cross-resistance to the PIs most commonly used for salvage therapy: lopinavir (LPV), tipranavir (TPV), and darunavir (DRV). The panel of recombinant infectious molecular clones has been made available without restriction through the NIH AIDS Research and Reference Reagent Program. The public availability of the panel makes it possible to compare the inhibitory activities of different PIs with one another. The diversity of the panel and the high-level PI resistance of its clones suggest that investigational PIs active against the clones in this panel will retain antiviral activity against most if not all clinically relevant PI-resistant viruses.

Collinearity of protease mutations in HIV-1 samples with high-level protease inhibitor class resistance

Objectives

To determine whether pan-protease inhibitor (PI)-resistant virus populations are composed predominantly of viruses with resistance to all PIs or of diverse virus populations with resistance to different subsets of PIs.

Methods

We performed deep sequencing of plasma virus samples from nine patients with high-level genotypic and/or phenotypic resistance to all licensed PIs. The nine virus samples had a median of 12 PI resistance mutations by direct PCR Sanger sequencing.

Results

For each of the nine virus samples, deep sequencing showed that each of the individual viruses within a sample contained nearly all of the mutations detected by Sanger sequencing. Indeed, a median of 94.9% of deep sequence reads had each of the PI resistance mutations present as a single chromatographic peak in the Sanger sequence. A median of 5.0% of reads had all but one of the Sanger mutations that were not part of an electrophoretic mixture.

Conclusions

The collinearity of PI resistance mutations in the nine virus samples demonstrated that pan-PI-resistant viruses are able to replicate in vivo despite their highly mutated protease enzymes. We hypothesize that the marked collinearity of PI resistance mutations in pan-PI-resistant virus populations results from the unique requirements for multi-PI resistance and the extensive cross-resistance conferred by many of the accessory PI resistance mutations.

HIV-1 antiretroviral resistance: scientific principles and clinical applications

The efficacy of an antiretroviral (ARV) treatment regimen depends on the activity of the regimen's individual ARV drugs and the number of HIV-1 mutations required for the development of resistance to each ARV - the genetic barrier to resistance. ARV resistance impairs the response to therapy in patients with transmitted resistance, unsuccessful initial ARV therapy and multiple virological failures. Genotypic resistance testing is used to identify transmitted drug resistance, provide insight into the reasons for virological failure in treated patients, and help guide second-line and salvage therapies. In patients with transmitted drug resistance, the virological response to a regimen selected on the basis of standard genotypic testing approaches the responses observed in patients with wild-type viruses. However, because such patients are at a higher risk of harbouring minority drug-resistant variants, initial ARV therapy in this population should contain a boosted protease inhibitor (PI) - the drug class with the highest genetic barrier to resistance. In patients receiving an initial ARV regimen with a high genetic barrier to resistance, the most common reasons for virological failure are nonadherence and, potentially, pharmacokinetic factors or minority transmitted drug-resistant variants. Among patients in whom first-line ARVs have failed, the patterns of drug-resistance mutations and cross-resistance are often predictable. However, the extent of drug resistance correlates with the duration of uncontrolled virological replication. Second-line therapy should include the continued use of a dual nucleoside/nucleotide reverse transcriptase inhibitor (NRTI)-containing backbone, together with a change in the non-NRTI component, most often to an ARV belonging to a new drug class. The number of available fully active ARVs is often diminished with each successive treatment failure. Therefore, a salvage regimen is likely to be more complicated in that it may require multiple ARVs with partial residual activity and compromised genetic barriers of resistance to attain complete virological suppression. A thorough examination of the patient's ARV history and prior resistance tests should be performed because genotypic and/or phenotypic susceptibility testing is often not sufficient to identify drug-resistant variants that emerged during past therapies and may still pose a threat to a new regimen. Phenotypic testing is also often helpful in this subset of patients. ARVs used for salvage therapy can be placed into the following hierarchy: (i) ARVs belonging to a previously unused drug class; (ii) ARVs belonging to a previously used drug class that maintain significant residual antiviral activity; (iii) NRTI combinations, as these often appear to retain in vivo virological activity, even in the presence of reduced in vitro NRTI susceptibility; and rarely (iv) ARVs associated with previous virological failure and drug resistance that appear to have possibly regained their activity as a result of viral reversion to wild type. Understanding the basic principles of HIV drug resistance is helpful in guiding individual clinical decisions and the development of ARV treatment guidelines.