Clinical Pharmacokinetics of the Novel HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitor Doravirine: An Assessment of the Effect of Patient Characteristics and Drug-Drug Interactions.

Doravirine (MK-1439) is a novel non-nucleoside reverse transcriptase inhibitor indicated for the combination treatment of human immunodeficiency virus type-1 (HIV-1) infection. The recommended dose is 100 mg once daily. This review summarizes the pharmacokinetics of doravirine, the influence of intrinsic factors, and its drug-drug interaction (DDI) profile. Following oral administration, doravirine is rapidly absorbed (median time to maximum plasma concentration, 1-4 h) and undergoes cytochrome P450 (CYP)3A-mediated oxidative metabolism. Steady-state geometric means for AUC0-24, C24, and Cmax in individuals with HIV-1 following administration of doravirine 100 mg once daily are 37.8 µM·h, 930 nM, and 2260 nM, respectively. Age, gender, severe renal impairment, and moderate hepatic impairment have no clinically meaningful effect on doravirine pharmacokinetics, and there is limited potential for DDIs. No dose adjustment is necessary when doravirine is co-administered with strong CYP3A inhibitors. However, doravirine is contraindicated with strong CYP3A inducers (e.g., rifampin), and dose adjustment of doravirine is recommended for co-administration with the moderate CYP3A inducer, rifabutin. Included in this review are clinical trial data from phase I pharmacokinetic trials, including DDI trials and trials in participants with renal and hepatic disease but without HIV-1 infection (N = 326), as well as phase I, II, and III safety and efficacy trials in participants living with HIV-1 (N = 991). Based on these data, the pharmacokinetic profile of doravirine supports its use in diverse populations living with HIV-1 and allows co-administration with various antiretroviral agents and treatments for commonly occurring co-morbidities.

Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few closely related systems has guided our understanding of the mechanisms by which changes such as ligand binding or mutation can alter the function. The general problem of detecting and interpreting such mechanisms from simulations of many related systems, however, remains a challenge. This problem is addressed here by applying supervised and unsupervised machine learning techniques to a variety of thermodynamic observables extracted from molecular dynamics simulations of different systems. As an important test case, these methods are applied to understand the evasion by human immunodeficiency virus type-1 (HIV-1) protease of darunavir, a potent inhibitor to which resistance can develop via the simultaneous mutation of multiple amino acids. Complex mutational patterns have been observed among resistant strains, presenting a challenge to developing a mechanistic picture of resistance in the protease. In order to dissect these patterns and gain mechanistic insight into the role of specific mutations, molecular dynamics simulations were carried out on a collection of HIV-1 protease variants, chosen to include highly resistant strains and susceptible controls, in complex with darunavir. Using a machine learning approach that takes advantage of the hierarchical nature in the relationships among the sequence, structure, and function, an integrative analysis of these trajectories reveals key details of the resistance mechanism, including changes in the protein structure, hydrogen bonding, and protein-ligand contacts.

A spatio-temporal assessment of simian/human immunodeficiency virus (SHIV) evolution reveals a highly dynamic process within the host.

The process by which drug-resistant HIV-1 arises and spreads spatially within an infected individual is poorly understood. Studies have found variable results relating how HIV-1 in the blood differs from virus sampled in tissues, offering conflicting findings about whether HIV-1 throughout the body is homogeneously distributed. However, most of these studies sample only two compartments and few have data from multiple time points. To directly measure how drug resistance spreads within a host and to assess how spatial structure impacts its emergence, we examined serial sequences from four macaques infected with RT-SHIVmne027, a simian immunodeficiency virus encoding HIV-1 reverse transcriptase (RT), and treated with RT inhibitors. Both viral DNA and RNA (vDNA and vRNA) were isolated from the blood (including plasma and peripheral blood mononuclear cells), lymph nodes, gut, and vagina at a median of four time points and RT was characterized via single-genome sequencing. The resulting sequences reveal a dynamic system in which vRNA rapidly acquires drug resistance concomitantly across compartments through multiple independent mutations. Fast migration results in the same viral genotypes present across compartments, but not so fast as to equilibrate their frequencies immediately. The blood and lymph nodes were found to be compartmentalized rarely, while both the blood and lymph node were more frequently different from mucosal tissues. This study suggests that even oft-sampled blood does not fully capture the viral dynamics in other parts of the body, especially the gut where vRNA turnover was faster than the plasma and vDNA retained fewer wild-type viruses than other sampled compartments. Our findings of transient compartmentalization across multiple tissues may help explain the varied results of previous compartmentalization studies in HIV-1.

Atazanavir sulfate + cobicistat for the treatment of HIV infection.

INTRODUCTION: During last two decades several drugs were developed to offer long-term benefits in terms of virologic efficacy, favourable tolerability and toxicity profiles in treatment of HIV infection. Pharmacokinetics boosting of protease inhibitor allows a higher genetic barrier, as few or no drug-resistant mutations are detected in patients with virologic failure. Areas covered: Atazanavir sulfate + cobicistat (ATV/c) was recently approved for the treatment of HIV-1 infection. Bioequivalence between cobicistat (COBI) and ritonavir (RTV) as a pharmacoenhancer of ATV was established. Additionally, randomized clinical trials demonstrated that ATV/c and ATV/ritonavir had comparable efficacy and safety profiles. Low rates of virologic failure and no ATV resistance mutations were observed in these clinical trials. Therefore, COBI shows increased advantages over RTV, such as no activity against HIV, fewer drug-drug interactions and better solubility, which promotes coformulation strategies with less pill burden, better tolerability, and, potentially, higher life-long treatment adherence. Expert commentary: ATV/c regimen supports its useas an effective treatment option for HIV-1 infected patients with increased cardiovascular disease and chronic kidney disease risk associated with aging. In addition, ATV/c is a new opportunity to expand the strategy of switch to a dual therapy to lower the risk of long-term toxicities as well as the advantage of its cost-benefit.

Efavirenz-based antiretroviral therapy versus nevirapine-including regimens for prevention of mother-to-child transmission of HIV option B plus in resource-limited settings: is there anything missing?

In 2013, an estimated 1.5 million HIV-positive pregnant women gave birth, with 240,000 children worldwide acquiring HIV. More than 90% of new pediatric infections occurred in Sub-Saharan Africa. The latest WHO guidelines recommended efavirenz (EFV)-based antiretroviral therapy as the first-line regimen for prevention of mother-to-child transmission of HIV (PMTCT). On the other hand, some data suggest that nevirapine (NVP), a well-known antiretroviral, could still play a relevant role in PMTCT, especially in resource-limited settings (RLSs) where the fertility rate is dramatically high compared to developed countries. Given the lack of an unanimous consensus and definitive opinions, this paper goes through the reasons for WHO decisions and aims at refreshing the debate about NVP and EFV pros and cons for PMTCT in RLSs.

The performance of reverse transcriptase assay for the estimation of the plasma viral load in HIV-1 and HIV-2 infections.

Viral load testing for human immunodeficiency virus 1 (HIV-1) in resource-poor settings continues to be a challenge. Although antiretroviral therapy (ART) is being made available in developing countries, monitoring of viral load is not being done on a regular basis. The purpose of this study was to assess the utility of Cavidi version 3.0, which measures the plasma reverse transcriptase (RT) activity and compare its performance with molecular HIV viral load assays. In all, 125 HIV-1 and 13 HIV-2 positive samples were analyzed. The overall sensitivity of the assay was 86.8% and 94.1% for viral load >1000 copies/ml measured by Qiagen Artus HIV-1 RG RT PCR and Abbott RealTime HIV-1 PCR assays, respectively. Compared with the routine molecular viral load assays, Cavidi version 3.0 is inexpensive, user-friendly, the expenditure on infrastructure is minimal, and it can be used for monitoring of both HIV types.

Sequence-Based Predictive Models of Resistance to HIV-1 Integrase Inhibitors: An n-Grams Approach to Phenotype Assessment.

Amino acid substitutions in HIV-1 proteins critical to the viral replication cycle have the potential to undermine successful inhibition of those targets, with some mutations leading to either reduced susceptibility to certain medications or complete drug resistance. Phenotypic tests are best suited to quantify the effects of complex mutational patterns on drug resistance; however, the relatively high cost and long turnaround time associated with phenotyping has increased the demand for in silico drug-specific models capable of accurately predicting phenotype directly from the target protein sequences. The focus of this study is on the HIV-1 integrase (IN) enzyme, which mediates integration of reversibly transcribed viral DNA into the host cell genome, and the development of predictive statistical learning models of resistance to the IN inhibitors Raltegravir (RAL) and Elvitegravir (EVG). Models were trained using datasets of IN protein sequence variants each having a known phenotype, quantified as the fold change in susceptibility to the respective inhibitor, and obtained using an experimental assay. A sequence-based approach employing n-grams relative frequencies was implemented to uniquely characterize each IN variant as a feature vector of input attributes. Models for classifying IN variants as susceptible or resistant reach cross-validation balanced accuracy rates of 89% with RAL and 85% with EVG. Additionally, regression models achieve Pearson's correlation coefficients, between experimental and predicted log-transformed phenotypic fold change values, as high as r = 0.80 with RAL and r = 0.76 with EVG. Our results suggest that as additional training data are made publicly available, the models may hold promise as supplementary tools for making treatment decisions.

American ginseng (Panax quinquefolius) administration does not affect performance of the Roche COBAS Ampliprep/Taqman HIV-1 RNA assay.

BACKGROUND: Previous data indicate that purified components of ginseng can inhibit HIV reverse transcriptase in vitro, suggesting that ginseng components in plasma may interfere with HIV-1 RNA detection assays. METHODS: Pre- and post-dose plasma from three volunteers dosed with 3000 mg American ginseng was spiked with HIV and analyzed by the Roche COBAS Ampliprep/Taqman v2.0 HIV-1 RNA assay. RESULTS: Presence of American ginseng had no significant effect on measured HIV-1 RNA concentration. Variation within pre- and post-dose plasma pair was insignificant and within assay performance limits. CONCLUSION: Plasma from subjects dosed with 3000 mg American ginseng does not interfere with the Roche COBAS Ampliprep/Taqman v2.0 HIV-1 RNA assay. This implies that in vitro inhibition of HIV reverse transcriptase by American ginseng components is unlikely to be clinically relevant.

Quantitative assessment of in vivo HIV protease activity using genetically engineered QD-based FRET probes.

HIV protease plays a central role in its life cycle leading to release of functional viral particles. It has been successfully used as a therapeutic target to block HIV infection. Several protease inhibitors (PIs) are currently being employed as a part of anti-HIV therapy. However, the constant genetic drift in the virus leads to accumulation of mutations in both cleavage site and the protease, resulting in resistance and failure of therapy. We reported the use of a quantum dot (QD)-based protein probe for the in vivo monitoring of HIV-1 protease activity based on fluorescence resonance energy transfer. In the current study, we demonstrate the utility of this approach by quantifying the in vivo cleavage rates of three known protease and cleavage site mutations in the presence or absence of different PIs. The changes in IC50 values for the different PIs were similar to that observed in patients, validating our assay as a rapid platform for PI screening.

Modular construction of quaternary hemiaminal-based inhibitor candidates and their in cellulo assessment with HIV-1 protease.

Non-peptidomimetic drug-like protease inhibitors have potential for circumventing drug resistance. We developed a much-improved synthetic route to our previously reported inhibitor candidate displaying an unusual quaternized hemi-aminal. This functional group forms from a linear precursor upon passage into physiological media. Seven variants were prepared and tested in cellulo with our HIV-1 fusion-protein technology that result in an eGFP-based fluorescent readout. Three candidates showed inhibition potency above 20µM and toxicity at higher concentrations, making them attractive targets for further refinement. Importantly, our class of original inhibitor candidates is not recognized by two major multidrug resistance pumps, quite in contrast to most clinically applied HIV-1 protease inhibitors.

NMR relaxation in proteins with fast internal motions and slow conformational exchange: model-free framework and Markov state simulations.

Calculating NMR relaxation effects for proteins with dynamics on multiple time scales generally requires very long trajectories based on conventional molecular dynamics simulations. In this report, we have built Markov state models from multiple MD trajectories and used the resulting MSM to capture the very fast internal motions of the protein within a free energy basin on a time scale up to hundreds of picoseconds and the more than 3 orders of magnitude slower conformational exchange between macrostates. To interpret the relaxation data, we derive new equations using the model-free framework which includes two slowly exchanging macrostates, each of which also exhibits fast local motions. Using simulations of HIV-1 protease as an example, we show how the populations of slowly exchanging conformational states as well as order parameters for the different states can be determined from the NMR relaxation data.

Viral fitness cost prevents HIV-1 from evading dolutegravir drug pressure.

BACKGROUND: Clinical studies have shown that integrase strand transfer inhibitors can be used to treat HIV-1 infection. Although the first-generation integrase inhibitors are susceptible to the emergence of resistance mutations that impair their efficacy in therapy, such resistance has not been identified to date in drug-naïve patients who have been treated with the second-generation inhibitor dolutegravir. During previous in vitro selection study, we identified a R263K mutation as the most common substitution to arise in the presence of dolutegravir with H51Y arising as a secondary mutation. Additional experiments reported here provide a plausible explanation for the absence of reported dolutegravir resistance among integrase inhibitor-naïve patients to date. RESULTS: We now show that H51Y in combination with R263K increases resistance to dolutegravir but is accompanied by dramatic decreases in both enzymatic activity and viral replication. CONCLUSIONS: Since H51Y and R263K may define a unique resistance pathway to dolutegravir, our results are consistent with the absence of resistance mutations in antiretroviral drug-naive patients treated with this drug.

Monte Carlo sampling and multivariate adaptive regression splines as tools for QSAR modelling of HIV-1 reverse transcriptase inhibitors.

The present work focuses on the development of an interpretable quantitative structure-activity relationship (QSAR) model for predicting the anti-HIV activities of 67 thiazolylthiourea derivatives. This set of molecules has been proposed as potent HIV-1 reverse transcriptase inhibitors (RT-INs). The molecules were encoded to a diverse set of molecular descriptors, spanning different physical and chemical properties. Monte Carlo (MC) sampling and multivariate adaptive regression spline (MARS) techniques were used to select the most important descriptors and to predict the activity of the molecules. The most important descriptor was found to be the aspherisity index. The analysis of variance (ANOVA) and interpretable spline equations showed that the geometrical shape of the molecules has considerable effect on their activities. It seems that the linear molecules are more active than symmetric top compounds. The final MARS model derived displayed a good predictive ability judging from the determination coefficient corresponding to the leave multiple out (LMO) cross-validation technique, i.e. r (2 )= 0.828 (M = 12) and r (2 )= 0.813 (M = 20). The results of this work showed that the developed spline model is robust, has a good predictive power, and can then be used as a reliable tool for designing novel HIV-1 RT-INs.

BF integrase genes of HIV-1 circulating in São Paulo, Brazil, with a recurrent recombination region.

Although some studies have shown diversity in HIV integrase (IN) genes, none has focused particularly on the gene evolving in epidemics in the context of recombination. The IN gene in 157 HIV-1 integrase inhibitor-naïve patients from the São Paulo State, Brazil, were sequenced tallying 128 of subtype B (23 of which were found in non-B genomes), 17 of subtype F (8 of which were found in recombinant genomes), 11 integrases were BF recombinants, and 1 from subtype C. Crucially, we found that 4 BF recombinant viruses shared a recurrent recombination breakpoint region between positions 4900 and 4924 (relative to the HXB2) that includes 2 gRNA loops, where the RT may stutter. Since these recombinants had independent phylogenetic origin, we argue that these results suggest a possible recombination hotspot not observed so far in BF CRF in particular, or in any other HIV-1 CRF in general. Additionally, 40% of the drug-naïve and 45% of the drug-treated patients had at least 1 raltegravir (RAL) or elvitegravir (EVG) resistance-associated amino acid change, but no major resistance mutations were found, in line with other studies. Importantly, V151I was the most common minor resistance mutation among B, F, and BF IN genes. Most codon sites of the IN genes had higher rates of synonymous substitutions (dS) indicative of a strong negative selection. Nevertheless, several codon sites mainly in the subtype B were found under positive selection. Consequently, we observed a higher genetic diversity in the B portions of the mosaics, possibly due to the more recent introduction of subtype F on top of an ongoing subtype B epidemics and a fast spread of subtype F alleles among the B population.

Virtual drug screen schema based on multiview similarity integration and ranking aggregation.

The current drug virtual screen (VS) methods mainly include two categories. i.e., ligand/target structure-based virtual screen and that, utilizing protein-ligand interaction fingerprint information based on the large number of complex structures. Since the former one focuses on the one-side information while the later one focuses on the whole complex structure, they are thus complementary and can be boosted by each other. However, a common problem faced here is how to present a comprehensive understanding and evaluation of the various virtual screen results derived from various VS methods. Furthermore, there is still an urgent need for developing an efficient approach to fully integrate various VS methods from a comprehensive multiview perspective. In this study, our virtual screen schema based on multiview similarity integration and ranking aggregation was tested comprehensively with statistical evaluations, providing several novel and useful clues on how to perform drug VS from multiple heterogeneous data sources. (1) 18 complex structures of HIV-1 protease with ligands from the PDB were curated as a test data set and the VS was performed with five different drug representations. Ritonavir ( 1HXW ) was selected as the query in VS and the weighted ranks of the query results were aggregated from multiple views through four similarity integration approaches. (2) Further, one of the ranking aggregation methods was used to integrate the similarity ranks calculated by gene ontology (GO) fingerprint and structural fingerprint on the data set from connectivity map, and two typical HDAC and HSP90 inhibitors were chosen as the queries. The results show that rank aggregation can enhance the result of similarity searching in VS when two or more descriptions are involved and provide a more reasonable similarity rank result. Our study shows that integrated VS based on multiple data fusion can achieve a remarkable better performance compared to that from individual ones and, thus, serves as a promising way for efficient drug screening, taking advantages of the rapidly accumulated molecule representations and heterogeneous data in the pharmacological area.

Protease inhibitor-containing antiretroviral treatment and tuberculosis: can rifabutin fill the breach?

OBJECTIVE: To assess how to best manage co-administration of rifabutin (RFB) and human immunodeficiency virus 1 (HIV-1) protease inhibitor (PI) containing antiretroviral treatment (ART). Recommended for initial anti-tuberculosis treatment, rifampicin (RMP) lowers PI concentrations below therapeutic levels, posing significant challenges for ART. As RFB has little effect on PI concentrations, it could be an alternative to RMP. METHODS: A review of the scientific literature on the safety and efficacy of RFB for adult tuberculosis (TB) treatment was conducted, focusing on ART-TB co-therapy. A cost comparison was performed between treatment regimens, and estimates of the burden of TB disease in patients on ART were used to model RFB demand in low- and middle-income countries (LMICs). RESULTS: Eleven clinical studies were identified, comprising 1543 TB patients treated with RFB; 980 (64%) were living with HIV. RFB was as safe and effective as RMP, including in 313 patients receiving co-administered ART (unboosted PIs included indinavir, nelfinavir or saquinavir; a minority received ritonavir [RTV] boosted amprenavir or saquinavir). The total cost for 6 months of all HIV and TB treatment containing RTV-boosted lopinavir (LPV) and RFB is US$410, compared to US$455 if RMP is used with LPV super-boosted with RTV. Our model suggests that demand for RFB in LMICs could be between 10,000 and 18,000 courses by 2012. CONCLUSION: RFB is effective and safe in combination with the PIs studied, cost-saving for co-therapy with currently recommended boosted PIs, and may have a pivotal role in the roll-out of ART. Further research into a daily dose of RFB to simplify dosing regimens and developing fixed-dose combinations can enhance the public sector roll-out of ART.

SMILES-based optimal descriptors: QSAR analysis of fullerene-based HIV-1 PR inhibitors by means of balance of correlations.

Quantitative structure-activity relationships (QSAR) for prediction of binding affinities (pEC50, i.e., minus decimal logarithm of the 50% effective concentration) of 20 fullerene derivatives inhibitors of the HIV-1 PR (human immunodeficiency virus type 1 protease) have been developed by application of the optimal descriptors approach calculated with SMILES (simplified molecular input line entry system). The applied models were constructed by the balance of correlations. Three various splits of the experimental data into subtraining set, calibration set, and test set were examined. Comparison of classic scheme (training-test system) and the balance of correlations (subtraining-calibration-test system) show that the balance of correlations gives more robust predictions than the classic scheme for the pEC50 of the fullerene derivatives.

Assessment of QM/MM scoring functions for molecular docking to HIV-1 protease.

We explore the ability of four quantum mechanical (QM)/molecular mechanical (MM) models to accurately identify the native pose of six HIV-1 protease inhibitors and compare them with the AMBER force field and ChemScore and GoldScore scoring functions. Three QM/MM scoring functions treated the ligand at the HF/6-31G*, AM1d, and PM3 levels; the fourth QM/MM function modeled the ligand and active site at the PM3-D level. For the discrimination of native from non-native poses, solvent-corrected HF/6-31G*:AMBER and AMBER functions exhibited the best overall performance. While the electrostatic component of the MM and QM/MM functions appears important for discriminating the native pose of the ligand, the polarization contribution in the QM/MM functions was relatively insensitive to a ligand's binding mode and, for one ligand, actually hindered discrimination. The inclusion of a desolvation penalty, here using a generalized Born solvent model, improved discrimination for the MM and QM/MM methods. There appeared to be no advantage to binding mode prediction by incorporating active site polarization at the PM3-D level. Finally, we found that choice of the protonation state of the aspartyl dyad in the HIV-1 protease active site influenced the ability of scoring methods to determine the native binding pose.

Computational proteomics analysis of binding mechanisms and molecular signatures of the HIV-1 protease drugs.

OBJECTIVE: Computational proteomics analysis of biomolecular interactions is proposed to determine molecular signatures of the HIV-1 protease inhibitors. A comparative microscopic analysis is conducted for a panel of inhibitors which exemplify a diversity of the HIV-1 PR binding mechanisms, from the active site inhibition to intervening with the protease folding and dimerization. METHODS AND MATERIALS: Replica-exchange Monte Carlo simulations with the conformational ensembles of the HIV-1 PR dimer and monomer structures enable a molecular analysis underlying diversity of the HIV-1 PR binding mechanisms. RESULTS: We have investigated the molecular basis underlying diversity of the HIV-1 PR binding mechanisms. The molecular basis of the HIV-1 PR active site and dimerization inhibition mechanisms has been analyzed for an active site tripeptide inhibitor and a tetrapeptide inhibitor, which can act as both a dimerization inhibitor and a competitive active site inhibitor. We have also simulated a structural mimicry mechanism of the HIV-1 PR folding inhibition and dimerization, according to which the folding inhibitor targets the conserved HIV-1 PR regions by mimicking the interaction network of the active dimer. CONCLUSIONS: We have shown that binding interfaces of the studied dimerization and folding HIV-1 PR inhibitors may enable structural mimicry with the hot spot residues of the HIV-1 PR dimer. The proposed structural models of intervening with the HIV-1 PR dimerization and folding support the mechanism of structural mimicry, which may alleviate drug resistance effects.

Optimization of azoles as anti-human immunodeficiency virus agents guided by free-energy calculations.

Efficient optimization of an inactive 2-anilinyl-5-benzyloxadiazole core has been guided by free energy perturbation (FEP) calculations to provide potent non-nucleoside inhibitors of human immunodeficiency virus (HIV) reverse transcriptase (NNRTIs). An FEP "chlorine scan" was performed to identify the most promising sites for substitution of aryl hydrogens. This yielded NNRTIs 8 and 10 with activities (EC50) of 820 and 310 nM for protection of human T-cells from infection by wild-type HIV-1. FEP calculations for additional substituent modifications and change of the core heterocycle readily led to oxazoles 28 and 29, which were confirmed as highly potent anti-HIV agents with activities in the 10-20 nM range. The designed compounds were also monitored for possession of desirable pharmacological properties by use of additional computational tools. Overall, the trends predicted by the FEP calculations were well borne out by the assay results. FEP-guided lead optimization is confirmed as a valuable tool for molecular design including drug discovery; chlorine scans are particularly attractive since they are both straightforward to perform and highly informative.