HIV-1 polymerase inhibition by nucleoside analogs: cellular- and kinetic parameters of efficacy, susceptibility and resistance selection

Model-based predictions of protective HIV pre-exposure prophylaxis adherence levels in cisgender women

Most human immunodeficiency virus (HIV) infections occur in cisgender women in resource-limited settings. In women, self-protection with emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) constitutes a major pillar of HIV prevention. However, clinical trials in women had inconsistent outcomes, sparking uncertainty about adherence requirements and reluctance in evaluating on-demand regimens. We analyzed data from published FTC/TDF-PrEP trials to establish efficacy ranges in cisgender women. In a 'bottom-up' approach, we modeled hypotheses in the context of risk-group-specific, adherence-efficacy profiles and challenged those hypotheses with clinical data. We found that different clinical outcomes were related to the proportion of women taking the product, allowing coherent interpretation of the data. Our analysis showed that 90% protection was achieved when women took some product. We found that hypotheses of putative male/female differences were either not impactful or statistically inconsistent with clinical data. We propose that differing clinical outcomes could arise from pill-taking behavior rather than biological factors driving specific adherence requirements in cisgender women.

Synthesis of protective oral PrEP adherence levels in cisgender women using convergent clinical- and bottom-up modeling

Globally, most HIV infections occur in heterosexual women in resource-limited settings. In these settings, female self-protection with generic emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) may constitute a major pillar of the HIV prevention portfolio. However, clinical trials in women had inconsistent outcomes, sparking uncertainty regarding risk-group specific adherence requirements and causing reluctance in testing and recommending on-demand regimen in women. We analyzed all FTC/TDF-PrEP trials to establish PrEP efficacy ranges in women. In a 'bottom-up' approach, we modeled hypotheses corroborating risk-group specific adherence-efficacy profiles. Finally, we used the clinical efficacy ranges to (in-)validate hypotheses. We found that different clinical outcomes could solely be explained by the proportion of enrolled participants not taking the product, allowing, for the first time, to unify clinical observations. This analysis showed that 90% protection was achieved, when women took some of the product. Using 'bottom-up' modelling, we found that hypotheses of putative male/female differences were either irrelevant, or statistically inconsistent with clinical data. Furthermore, our multiscale modelling indicated that 90% protection was achieved if oral FTC/TDF was taken at least twice weekly.

Mathematical Modelling of the Molecular Mechanisms of Interaction of Tenofovir with Emtricitabine against HIV

The combination of the two nucleoside reverse transcriptase inhibitors (NRTI) tenofovir disoproxil fumarate (TDF) and emtricitabine (FTC) is used in most highly active antiretroviral therapies for treatment of HIV-1 infection, as well as in pre-exposure prophylaxis against HIV acquisition. Administered as prodrugs, these drugs are taken up by HIV-infected target cells, undergo intracellular phosphorylation and compete with natural deoxynucleoside triphosphates (dNTP) for incorporation into nascent viral DNA during reverse transcription. Once incorporated, they halt reverse transcription. In vitro studies have proposed that TDF and FTC act synergistically within an HIV-infected cell. However, it is unclear whether, and which, direct drug–drug interactions mediate the apparent synergy. The goal of this work was to refine a mechanistic model for the molecular mechanism of action (MMOA) of nucleoside analogues in order to analyse whether putative direct interactions may account for the in vitro observed synergistic effects. Our analysis suggests that depletion of dNTP pools can explain apparent synergy between TDF and FTC in HIV-infected cells at clinically relevant concentrations. Dead-end complex (DEC) formation does not seem to significantly contribute to the synergistic effect. However, in the presence of non-nucleoside reverse transcriptase inhibitors (NNRTIs), its role might be more relevant, as previously reported in experimental in vitro studies.

The Restrictome of Flaviviruses

Flaviviruses are a genus of mostly arthropod-borne RNA viruses that cause a range of pathologies in humans. Basic knowledge on flaviviruses is rapidly expanding, partly due to their status as frequent emerging or re-emerging pathogens. Flaviviruses include the dengue, Zika, West Nile, tick-borne encephalitis and yellow fever viruses (DENV, ZIKV, WNV, TBEV and YFV, respectively). As is the case with other families of viruses, the success of productive infection of human cells by flaviviruses depends in part on the antiviral activity of a heterogeneous group of cellular antiviral proteins called restriction factors. Restriction factors are the effector proteins of the cell-autonomous innate response against viruses, an immune pathway that also includes virus sensors as well as intracellular and extracellular signal mediators such as type I interferons (IFN-I). In this review, I summarize recent progress toward the identification and characterization of flavivirus restriction factors. In particular, I focus on IFI6, Schlafen 11, FMRP, OAS-RNase L, RyDEN, members of the TRIM family of proteins (TRIM5α, TRIM19, TRIM56, TRIM69 and TRIM79α) and a new mechanism of action proposed for viperin. Recent and future studies on this topic will lead to a more complete picture of the flavivirus restrictome, defined as the ensemble of cellular factors with demonstrated anti-flaviviral activity.

Modeling HIV Pre-Exposure Prophylaxis

Pre-exposure prophylaxis (PrEP) has emerged as a promising strategy for preventing the transmission of HIV. Although only one formulation is currently approved for PrEP, research into both new compounds and new delivery systems for PrEP regimens offer intriguing challenges from the perspective of pharmacokinetic and pharmacodynamic modeling. This review aims to provide an overview the current modeling landscape for HIV PrEP, focused on PK/PD and QSP models relating to antiretroviral agents. Both current PrEP treatments and new compounds that show promise as PrEP agents are highlighted, as well as models of uncommon administration routes, predictions based on models of mechanism of action and viral dynamics, and issues related to adherence to therapy. The spread of human immunodeficiency virus (HIV) remains one of the foremost global health concerns. In the absence of a vaccine, other prophylactic strategies have been developed to prevent HIV transmission. One approach, known as pre-exposure prophylaxis (PrEP), allows HIV-negative individuals who are at high risk of exposure to the virus, be it through an HIV-positive sexual partner or through the shared use of drug injection equipment, to substantially reduce the risk of developing an HIV infection. PrEP is a relatively recent approach to combating the HIV epidemic, with the only currently approved treatment being Truvada, a daily oral antiretroviral (ARV) therapy initially indicated in the treatment of active HIV-1 infections, but approved for HIV PrEP in 2012. Although PrEP therapy has consistently demonstrated high efficacy in preventing HIV infection, this efficacy is dependent on patient adherence to the prescribed treatment regimen. This can present a significant problem in low- and middle-income countries, which may lack the infrastructure to provide sufficient access to PrEP medication to maintain daily dosing regimens. Furthermore, while the conventional approach has generally been to advocate for continuous administration akin to regimens used for viral suppression in infected patients, there has been some discussion of whether a better treatment paradigm might be to push for PrEP therapy primarily during those known periods of heightened exposure risk, while relying on post-exposure prophylaxis regimens to prevent infection after unanticipated exposures during low-risk periods. These considerations have led to a push for the development of long-duration and on-demand PrEP formulations, including subdermal and subcutaneous implants, slow-release intramuscular depot injections, vaginal and rectal antimicrobial gels, and intravaginal rings and dissolving films. PrEP therapy is a quickly evolving field, with a variety of antiretroviral compounds and formulations under investigation. This review aims to report on notable drugs and formulations from a pharmacokinetic/pharmacodynamic (PK/PD) modeling perspective. Given the nature of PrEP as a preventive therapy designed for long-term use, clinical trials for PrEP therapies can last for months or even years, particularly in the case of long-duration formulations. Furthermore, in contrast to antiretroviral trials in infected patients, pharmacodynamic endpoints in PrEP therapies are difficult to quantify, as the primary endpoint for efficacy is generally the rate of seroconversion. Computational modeling approaches offer flexible and powerful tools to provide insight into drug behavior in clinical settings, and can ultimately reduce the time, expense, and patient burden incurred in the development of PrEP therapies.

Quasispecies dynamics in disease prevention and control

Medical interventions to prevent and treat viral disease constitute evolutionary forces that may modify the genetic composition of viral populations that replicate in an infected host and influence the genomic composition of those viruses that are transmitted and progress at the epidemiological level. Given the adaptive potential of viruses in general and the RNA viruses in particular, the selection of viral mutants that display some degree of resistance to inhibitors or vaccines is a tangible challenge. Mutant selection may jeopardize control of the viral disease. Strategies intended to minimize vaccination and treatment failures are proposed and justified based on fundamental features of viral dynamics explained in the preceding chapters. The recommended use of complex, multiepitopic vaccines, and combination therapies as early as possible after initiation of infection falls under the general concept that complexity cannot be combated with simplicity. It also follows that sociopolitical action to interrupt virus replication and spread as soon as possible is as important as scientifically sound treatment designs to control viral disease on a global scale.

Mechanistic framework predicts drug-class specific utility of antiretrovirals for HIV prophylaxis

Currently, there is no effective vaccine to halt HIV transmission. However, pre-exposure prophylaxis (PrEP) with the drug combination Truvada can substantially decrease HIV transmission in individuals at risk. Despite its benefits, Truvada-based PrEP is expensive and needs to be taken once-daily, which often leads to inadequate adherence and incomplete protection. These deficits may be overcome by next-generation PrEP regimen, including currently investigated long-acting formulations, or patent-expired drugs. However, poor translatability of animal- and ex vivo/in vitro experiments, and the necessity to conduct long-term (several years) human trials involving considerable sample sizes (N>1000 individuals) are major obstacles to rationalize drug-candidate selection. We developed a prophylaxis modelling tool that mechanistically considers the mode-of-action of all available drugs. We used the tool to screen antivirals for their prophylactic utility and identify lower bound effective concentrations that can guide dose selection in PrEP trials. While in vitro measurable drug potency usually guides PrEP trial design, we found that it may over-predict PrEP potency for all drug classes except reverse transcriptase inhibitors. While most drugs displayed graded concentration-prophylaxis profiles, protease inhibitors tended to switch between none- and complete protection. While several treatment-approved drugs could be ruled out as PrEP candidates based on lack-of-prophylactic efficacy, darunavir, efavirenz, nevirapine, etravirine and rilpivirine could more potently prevent infection than existing PrEP regimen (Truvada). Notably, some drugs from this candidate set are patent-expired and currently neglected for PrEP repurposing. A next step is to further trim this candidate set by ruling out compounds with ominous safety profiles, to assess different administration schemes in silico and to test the remaining candidates in human trials.

Pre-exposure prophylaxis (PrEP) is a novel, promising strategy to halt HIV transmission. PrEP with Truvada can substantially decrease the risk of infection. However, individuals often inadequately adhere to the once-daily regimen and the drug is expensive. These shortcomings may be overcome by next-generation PrEP compounds, including long-acting formulations. However, poor translatability of animal- and ex vivo/in vitro experiments, and difficulties in conducting long-term trials involving considerable sample sizes (N > 1000 individuals) make drug-candidate selection and optimization of administration schemes costly and often infeasible. We developed a simulation tool that mechanistically considers the mode-of-action of all antivirals. We used the tool to screen all available antivirals for their prophylactic utility and identified lower bound effective concentrations for designing PrEP dosing regimen in clinical trials. We found that in vitro measured drug potency may over-predict PrEP potency, for all antiviral classes except reverse transcriptase inhibitors. We could rule out a number of antivirals for PrEP repurposing and predicted that darunavir, efavirenz, nevirapine, etravirine and rilpivirine provide complete protection at clinically relevant concentrations. Further trimming of this candidate set by compound-safety and by assessing different implementation schemes is envisaged.

Molecular evolution of HIV-1 integrase during the 20 years prior to the first approval of integrase inhibitors

BACKGROUND

Detailed knowledge of the evolutionary potential of polymorphic sites in a viral protein is important for understanding the development of drug resistance in the presence of an inhibitor. We therefore set out to analyse the molecular evolution of the HIV-1 subtype B integrase at the inter-patient level in Germany during a 20-year period prior to the first introduction of integrase strand inhibitors (INSTIs).

METHODS

We determined 337 HIV-1 integrase subtype B sequences (amino acids 1-278) from stored plasma samples of antiretroviral treatment-naïve individuals newly diagnosed with HIV-1 between 1986 and 2006. Shannon entropy was calculated to determine the variability at each amino acid position. Time trends in the frequency of amino acid variants were identified by linear regression. Direct coupling analysis was applied to detect covarying sites.

RESULTS

Twenty-two time trends in the frequency of amino acid variants demonstrated either single amino acid exchanges or variation in the degree of polymorphy. Covariation was observed for 17 amino acid variants with a temporal trend. Some minor INSTI resistance mutations (T124A, V151I, K156 N, T206S, S230 N) and some INSTI-selected mutations (M50I, L101I, T122I, T124 N, T125A, M154I, G193E, V201I) were identified at overall frequencies >5%. Among these, the frequencies of L101I, T122I, and V201I increased over time, whereas the frequency of M154I decreased. Moreover, L101I, T122I, T124A, T125A, M154I, and V201I covaried with non-resistance-associated variants.

CONCLUSIONS

Time-trending, covarying polymorphisms indicate that long-term evolutionary changes of the HIV-1 integrase involve defined clusters of possibly structurally or functionally associated sites independent of selective pressure through INSTIs at the inter-patient level. Linkage between polymorphic resistance- and non-resistance-associated sites can impact the selection of INSTI resistance mutations in complex ways. Identification of these sites can help in improving genotypic resistance assays, resistance prediction algorithms, and the development of new integrase inhibitors.

Structural Insights into HIV Reverse Transcriptase Mutations Q151M and Q151M Complex That Confer Multinucleoside Drug Resistance

HIV-1 reverse transcriptase (RT) is targeted by multiple drugs. RT mutations that confer resistance to nucleoside RT inhibitors (NRTIs) emerge during clinical use. Q151M and four associated mutations, A62V, V75I, F77L, and F116Y, were detected in patients failing therapies with dideoxynucleosides (didanosine [ddI], zalcitabine [ddC]) and/or zidovudine (AZT). The cluster of the five mutations is referred to as the Q151M complex (Q151Mc), and an RT or virus containing Q151Mc exhibits resistance to multiple NRTIs. To understand the structural basis for Q151M and Q151Mc resistance, we systematically determined the crystal structures of the wild-type RT/double-stranded DNA (dsDNA)/dATP (complex I), wild-type RT/dsDNA/ddATP (complex II), Q151M RT/dsDNA/dATP (complex III), Q151Mc RT/dsDNA/dATP (complex IV), and Q151Mc RT/dsDNA/ddATP (complex V) ternary complexes. The structures revealed that the deoxyribose rings of dATP and ddATP have 3'-endo and 3'-exo conformations, respectively. The single mutation Q151M introduces conformational perturbation at the deoxynucleoside triphosphate (dNTP)-binding pocket, and the mutated pocket may exist in multiple conformations. The compensatory set of mutations in Q151Mc, particularly F116Y, restricts the side chain flexibility of M151 and helps restore the DNA polymerization efficiency of the enzyme. The altered dNTP-binding pocket in Q151Mc RT has the Q151-R72 hydrogen bond removed and has a switched conformation for the key conserved residue R72 compared to that in wild-type RT. On the basis of a modeled structure of hepatitis B virus (HBV) polymerase, the residues R72, Y116, M151, and M184 in Q151Mc HIV-1 RT are conserved in wild-type HBV polymerase as residues R41, Y89, M171, and M204, respectively; functionally, both Q151Mc HIV-1 and wild-type HBV are resistant to dideoxynucleoside analogs.

Multiscale Systems-Pharmacology Pipeline to Assess the Prophylactic Efficacy of NRTIs Against HIV-1

While HIV-1 continues to spread, the use of antivirals in preexposure prophylaxis (PrEP) has recently been suggested. Here we present a modular systems pharmacology modeling pipeline, predicting PrEP efficacy of nucleotide reverse transcriptase inhibitors (NRTIs) at the scale of reverse transcription, target-cell, and systemic infection and after repeated viral exposures, akin to clinical trials. We use this pipeline to benchmark the prophylactic efficacy of all currently approved NRTIs in wildtype and mutant viruses. By integrating pharmacokinetic models, we find that intracellular tenofovir-diphosphate builds up too slowly to halt infection when taken "on demand" and that lamivudine may substitute emtricitabine in PrEP combinations. Lastly, we delineate factors confounding clinical PrEP efficacy estimates and provide a method to overcome these. The presented framework is useful to screen and optimize PrEP candidates and strategies and to understand their clinical efficacy by integrating the diverse scales which determine PrEP efficacy.

Top-down and bottom-up modeling in system pharmacology to understand clinical efficacy: An example with NRTIs of HIV-1

A major aim of Systems Pharmacology is to understand clinically relevant mechanisms of action (MOA) of drugs and to use this knowledge in order to optimize therapy. To enable this mission it is necessary to obtain knowledge on how in vitro testable insights translate into clinical efficacy. Mathematical modeling and data integration are essential components to achieve this goal. Two modeling philosophies are prevalent, each of which in isolation is not sufficient to achieve the above described: In a 'top-down' approach, a minimal pharmacokinetic-pharmacodynamic (PK-PD) model is derived from- and fitted to available clinical data. This model may lack interpretability in terms of mechanisms and may only be predictive for scenarios already covered by the data used to derive it. A 'bottom-up' approach builds on mechanistic insights derived from in vitro/ex vivo experiments, which can be conducted under controlled conditions, but may not be fully representative for the in vivo/clinical situation. In this work, we employ both approaches side-by-side to predict the clinical potency (IC₅₀ values) of the nucleoside reverse transcriptase inhibitors (NRTIs) lamivudine, emtricitabine and tenofovir. In the 'top-down' approach, this requires to establish the dynamic link between the intracellularly active NRTI-triphosphates (which exert the effect) and plasma prodrug PK and to subsequently link this composite PK model to viral kinetics. The 'bottom-up' approach assesses inhibition of reverse transcriptase-mediated viral DNA polymerization by the intracellular, active NRTI-triphosphates, which has to be brought into the context of target cell infection. By using entirely disparate sets of data to derive and parameterize the respective models, our approach serves as a means to assess the clinical relevance of the 'bottom-up' approach. We obtain very good qualitative and quantitative agreement between 'top-down' vs. 'bottom-up' predicted IC₅₀ values, arguing for the validity of the 'bottom-up' approach. We noted, however, that the 'top-down' approach is strongly dependent on the sparse and noisy intracellular pharmacokinetic data. All in all, our work provides confidence that we can translate in vitro parameters into measures of clinical efficacy using the 'bottom-up' approach. This may allow to infer the potency of various NRTIs in inhibiting e.g. mutant viruses, to distinguish sources of interaction of NRTI combinations and to assess the efficacy of different NRTIs for repurposing, e.g. for pre-exposure prophylaxis.

Optimal Treatment Strategies in the Context of 'Treatment for Prevention' against HIV-1 in Resource-Poor Settings

An estimated 2.7 million new HIV-1 infections occurred in 2010. `Treatment-for-prevention’ may strongly prevent HIV-1 transmission. The basic idea is that immediate treatment initiation rapidly decreases virus burden, which reduces the number of transmittable viruses and thereby the probability of infection. However, HIV inevitably develops drug resistance, which leads to virus rebound and nullifies the effect of `treatment-for-prevention’ for the time it remains unrecognized. While timely conducted treatment changes may avert periods of viral rebound, necessary treatment options and diagnostics may be lacking in resource-constrained settings. Within this work, we provide a mathematical platform for comparing different treatment paradigms that can be applied to many medical phenomena. We use this platform to optimize two distinct approaches for the treatment of HIV-1: (i) a diagnostic-guided treatment strategy, based on infrequent and patient-specific diagnostic schedules and (ii) a pro-active strategy that allows treatment adaptation prior to diagnostic ascertainment. Both strategies are compared to current clinical protocols (standard of care and the HPTN052 protocol) in terms of patient health, economic means and reduction in HIV-1 onward transmission exemplarily for South Africa. All therapeutic strategies are assessed using a coarse-grained stochastic model of within-host HIV dynamics and pseudo-codes for solving the respective optimal control problems are provided. Our mathematical model suggests that both optimal strategies (i)-(ii) perform better than the current clinical protocols and no treatment in terms of economic means, life prolongation and reduction of HIV-transmission. The optimal diagnostic-guided strategy suggests rare diagnostics and performs similar to the optimal pro-active strategy. Our results suggest that ‘treatment-for-prevention’ may be further improved using either of the two analyzed treatment paradigms.

HIV-1 continues to spread globally. Antiviral treatment cannot cure patients, but it slows disease progression and may prevent HIV transmission by decreasing the amount of transmittable viruses in treated individuals. ‘Treatment-for-prevention’ argues for immediate treatment initiation and may reduce transmission by 96% (CI: 73–99%), according to the results of a large clinical study (HPTN052). In order to ensure long-lasting treatment success, early therapy initiation demands more sophisticated treatment strategies & exceeding funds. However, countries facing the highest HIV burden are among the poorest. Within this work, we provide a mathematical framework that allows assessing different treatment paradigms using optimal control theory together with stochastic modelling of within-host viral dynamics and drug resistance development. We use this framework to compute and evaluate two distinct optimal long-term treatment strategies for resource-constrained settings: (i) a diagnostic-guided and (ii) a pro-active treatment strategy. The cost of a strategy is evaluated from a national economic perspective, valuating a severe patient health status in terms of an economic loss. The optimal strategies are compared with current clinical treatment protocols and no treatment in terms of costs, life expectation and reduction of secondary cases. Our simulations indicate that the pro-active treatment strategy performs comparably to the diagnostic-guided treatment strategy. Both strategies perform better than current clinical protocols, suggesting directions for improvement.

Linking the population pharmacokinetics of tenofovir and its metabolites with its cellular uptake and metabolism

Empirical pharmacokinetic models are used to explain the pharmacokinetics of the antiviral drug tenofovir (TFV) and its metabolite TFV diphosphate (TFV-DP) in peripheral blood mononuclear cells. These empirical models lack the ability to explain differences between the disposition of TFV-DP in HIV-infected patients vs. healthy individuals. Such differences may lie in the mechanisms of TFV transport and phosphorylation. Therefore, we developed an exploratory model based on mechanistic mass transport principles and enzyme kinetics to examine the uptake and phosphorylation kinetics of TFV. TFV-DP median C_max from the model was 38.5 fmol/10⁶ cells, which is bracketed by two reported healthy volunteer studies (38 and 51 fmol/10⁶ cells). The model presented provides a foundation for exploration of TFV uptake and phosphorylation kinetics for various routes of TFV administration and can be updated as more is known on actual mechanisms of cellular transport of TFV.

Estimating HIV-1 fitness characteristics from cross-sectional genotype data

Despite the success of highly active antiretroviral therapy (HAART) in the management of human immunodeficiency virus (HIV)-1 infection, virological failure due to drug resistance development remains a major challenge. Resistant mutants display reduced drug susceptibilities, but in the absence of drug, they generally have a lower fitness than the wild type, owing to a mutation-incurred cost. The interaction between these fitness costs and drug resistance dictates the appearance of mutants and influences viral suppression and therapeutic success. Assessing in vivo viral fitness is a challenging task and yet one that has significant clinical relevance. Here, we present a new computational modelling approach for estimating viral fitness that relies on common sparse cross-sectional clinical data by combining statistical approaches to learn drug-specific mutational pathways and resistance factors with viral dynamics models to represent the host-virus interaction and actions of drug mechanistically. We estimate in vivo fitness characteristics of mutant genotypes for two antiretroviral drugs, the reverse transcriptase inhibitor zidovudine (ZDV) and the protease inhibitor indinavir (IDV). Well-known features of HIV-1 fitness landscapes are recovered, both in the absence and presence of drugs. We quantify the complex interplay between fitness costs and resistance by computing selective advantages for different mutants. Our approach extends naturally to multiple drugs and we illustrate this by simulating a dual therapy with ZDV and IDV to assess therapy failure. The combined statistical and dynamical modelling approach may help in dissecting the effects of fitness costs and resistance with the ultimate aim of assisting the choice of salvage therapies after treatment failure.

Mutations conferring drug resistance represent major threats to the therapeutic success of highly active antiretroviral therapy (HAART) against human immunodeficiency virus (HIV)-1 infection. Viral mutants differ in their fitness and assessing viral fitness is a challenging task. In this article, we estimate drug-specific mutational pathways by learning from clinical data using statistical techniques and incorporate these into mathematical models of in vivo viral infection dynamics. This approach enables us to estimate mutant fitness characteristics. We illustrate our method by predicting fitness characteristics of mutant genotypes for two different antiretroviral therapies with the drugs zidovudine and indinavir. We recover several established features of mutant fitnesses and quantify fitness characteristics both in the absence and presence of drugs. Our model extends naturally to multiple drugs and we illustrate this by simulating a dual therapy with ZDV and IDV to assess therapy failure. Additionally, our modelling approach relies only on cross-sectional clinical data. We believe that such an approach is a highly valuable tool in assisting the choice of salvage therapies after treatment failure.

In vitro HIV-1 evolution in response to triple reverse transcriptase inhibitors & in silico phenotypic analysis

BACKGROUND

Effectiveness of ART regimens strongly depends upon complex interactions between the selective pressure of drugs and the evolution of mutations that allow or restrict drug resistance.

METHODS

Four clinical isolates from NRTI-exposed, NNRTI-naive subjects were passaged in increasing concentrations of NVP in combination with 1 µM 3 TC and 2 µM ADV to assess selective pressures of multi-drug treatment. A novel parameter inference procedure, based on a stochastic viral growth model, was used to estimate phenotypic resistance and fitness from in vitro combination passage experiments.

RESULTS

Newly developed mathematical methods estimated key phenotypic parameters of mutations arising through selective pressure exerted by 3 TC and NVP. Concentrations of 1 µM 3 TC maintained the M184V mutation, which was associated with intrinsic fitness deficits. Increasing NVP concentrations selected major NNRTI resistance mutations. The evolutionary pathway of NVP resistance was highly dependent on the viral genetic background, epistasis as well as stochasticity. Parameter estimation indicated that the previously unrecognized mutation L228Q was associated with NVP resistance in some isolates.

CONCLUSION

Serial passage of viruses in the presence of multiple drugs may resemble the selection of mutations observed among treated individuals and populations in vivo and indicate evolutionary preferences and restrictions. Phenotypic resistance estimated here "in silico" from in vitro passage experiments agreed well with previous knowledge, suggesting that the unique combination of "wet-" and "dry-lab" experimentation may improve our understanding of HIV-1 resistance evolution in the future.

A novel method for the analysis of drug-resistant phenotypes of hepatitis B virus

Chronic hepatitis B virus (CHB) infection is a major cause of cirrhosis and hepatocellular carcinoma. Nucleoside analogs (NAs) are popularly used to treat chronic hepatitis B virus (HBV) infections; however, the anti-HBV effect is attenuated by drug-resistant viral mutations selected during long-term antiviral therapy. The timely analysis of drug-resistance mutations is essential in order to adjust treatment regimes. In this study, a T1699C substitution was introduced into the x gene of pHBV1.3 to generate an additional XhoI site, termed pHBV1.3‑XhoI, which is a nonsense mutation and does not influence protein expression, HBV replication ability, or NA susceptibility. Based on co-transfection with weak or non-replicative HBV plasmids and pHBV1.3-XhoI or pHBV1.3 and -XhoI-P-null plasmids into hepatocellular carcinoma cells, PCR was used to amplify 1176‑bp segments of T/C1699 using the isolated HBV encapsulated DNA as a template, modified by XhoI digestion and subjected to agarose gel electrophoresis. Different bands composed of different virions were used to distinguish the replication capacities of the plasmids. Our results demonstrated no significant effects when different virions co-existed. A novel resistance test method was developed by co-transfection with pHBV1.3-XhoI and -rtL180M/M204V and treatment with various NA concentrations. Different bands composed of pHBV1.3-XhoI or -rtL180M/M204V were used to distinguish NA susceptibility. The bands composed of pHBV1.3 were more sharply reduced by lamivudine (LMV) than -rtL180M/M204V. The data demonstrate that the method established in our study may be used for the analysis of drug-resistant phenotypes at the cellular level.

The nucleoside reverse transcriptase inhibitors, nonnucleoside reverse transcriptase inhibitors, and protease inhibitors in the treatment of HIV infections (AIDS)

The majority of the drugs currently used for the treatment of HIV infections (AIDS) belong to either of the following three classes: nucleoside reverse transcriptase inhibitors (NRTIs), nonnucleoside reverse transcriptase inhibitors (NNRTIs), and protease inhibitors (PIs). At present, there are 7 NRTIs, 5 NNRTIs, and 10 PIs approved for clinical use. They are discussed from the following viewpoints: (i) chemical formulae; (ii) mechanism of action; (iii) drug combinations; (iv) clinical aspects; (v) preexposure prophylaxis; (vi) prevention of mother-to-child transmission; (vii) their use in children; (viii) toxicity; (ix) adherence (compliance); (x) resistance; (xi) new NRTIs, NNRTIs, or PIs in (pre)clinical development; and (xii) the prospects for a "cure" of the disease.

Pharmacokinetics and pharmacodynamics of the reverse transcriptase inhibitor tenofovir and prophylactic efficacy against HIV-1 infection

Antiviral pre-exposure prophylaxis (PrEP) through daily drug administration can protect healthy individuals from HIV-1 infection. While PrEP was recently approved by the FDA, the potential long-term consequences of PrEP implementation remain entirely unclear. The aim of this study is to predict the efficacy of different prophylactic strategies with the pro-drug tenofovir-disoproxil-fumarate (TDF) and to assess the sensitivity towards timing- and mode of TDF administration (daily- vs. single dose), adherence and the number of transmitted viruses. We developed a pharmacokinetic model for TDF and its active anabolite tenofovir-diphosphate (TFV-DP) and validated it with data from 4 different trials, including 4 distinct dosing regimes. Pharmacokinetics were coupled to an HIV model and viral decay following TDF mono-therapy was predicted, consistent with available data. Subsequently, a stochastic approach was used to estimate the % infections prevented by (i) daily TDF-based PrEP, (ii) one week TDF started either shortly before, or -after viral exposure and (iii) a single dose oral TDF before viral challenge (sd-PrEP). Analytical solutions were derived to assess the relation between intracellular TFV-DP concentrations and prophylactic efficacy. The predicted efficacy of TDF was limited by a slow accumulation of active compound (TFV-DP) and variable TFV-DP half-life and decreased with increasing numbers of transmitted viruses. Once daily TDF-based PrEP yielded [Formula: see text]80% protection, if at least 40% of pills were taken. Sd-PrEP with 300 mg or 600 mg TDF could prevent [Formula: see text]50% infections, when given at least before virus exposure. The efficacy dropped to [Formula: see text]10%, when given 1 h before 24 h exposure. Efficacy could not be increased with increasing dosage or prolonged administration. Post-exposure prophylaxis poorly prevented infection. The use of drugs that accumulate more rapidly, or local application of tenofovir gel may overcome the need for drug administration long before virus exposure.

A pyrophosphatase activity associated with purified HIV-1 particles

Treatment of HIV-1 with nucleoside reverse transcription inhibitors leads to the emergence of resistance mutations in the reverse transcriptase (RT) gene. Resistance to 3'-azido-3'-deoxythymidine (AZT) and to a lesser extent to 2'-3'-didehydro-2'-3'-dideoxythymidine is mediated by phosphorolytic excision of the chain terminator. Wild-type RT excises AZT by pyrophosphorolysis, while thymidine-associated resistance mutations in RT (TAMs) favour ATP as the donor substrate. However, in vitro, resistant RT still uses pyrophosphate more efficiently than ATP. We performed in vitro (-) strong-stop DNA synthesis experiments, with wild-type and AZT-resistant HIV-1 RTs, in the presence of physiologically relevant pyrophosphate and/or ATP concentrations and found that in the presence of pyrophosphate, ATP and AZTTP, TAMs do not enhance in vitro (-) strong-stop DNA synthesis. We hypothesized that utilisation of ATP in vivo is driven by intrinsic low pyrophosphate concentrations within the reverse transcription complex, which could be explained by the packaging of a cellular pyrophosphatase. We showed that over-expressed flagged-pyrophosphatase was associated with HIV-1 viral-like particles. In addition, we demonstrated that when HIV-1 particles were purified in order to avoid cellular microvesicle contamination, a pyrophosphatase activity was specifically associated to them. The presence of a pyrophosphatase activity in close proximity to the reverse transcription complex is most likely advantageous to the virus, even in the absence of any drug pressure.