HIV protease resistance mutations in patients receiving second-line antiretroviral therapy in Libreville, Gabon.

INTRODUCTION: In 2022, the WHO reported that 29.8 million people around the world were living with HIV (PLHIV) and receiving antiretroviral treatment (ART), including 25| 375 people in Gabon (54% of all those living with HIV in the country). The literature reports a frequency of therapeutic failure with first-line antiretrovirals (ARVs) of between 20% and 82%. Unfortunately, data relating to the failure of second-line ARVs are scarce in Gabon. This study aims to determine the profiles of HIV drug resistance mutations related to protease inhibitors in Gabon. METHODOLOGY: Plasma from 84 PLHIV receiving ARVs was collected from 2019 to 2021, followed by RNA extraction, amplification, and sequencing of the protease gene. ARV resistance profiles were generated using the Stanford interpretation algorithm version 8.9-1 ( https://hivdb.stanford.edu ) and statistical analyses were performed using EpiInfo software version 7.2.1.0 (CDC, USA). RESULTS: Of 84 HIV plasma samples collected from 45 men and 39 women, 342 mutations were detected. Of these, 43.3% (148/342) were associated with nucleoside reverse transcriptase inhibitors (NRTIs), 30.4% (104/342) with non-nucleoside reverse transcriptase inhibitors (NNRTIs), and 26.3% (90/342) with protease inhibitors (PIs). Most NRTI mutations were associated with thymidine analogues (TAMs) (50.7%; 75/148), including T215F/V (14.9%; 22/148), D67DN/E/G/N/T (10.1%; 15/148), M41L (9.5%; 14/148), and K70E/KN/S/R (9.5%; 14/148). Resistance mutations related to non-TAM NRTIs (33.1%; 49/148) were M184V (29.1%; 43/148), and L74I/V (8.1%; 12/148). NNRTI mutations were predominantly K103N/S (32.7%; 34/104), V108I (10.6%; 11/104), A98G (10.6%; 11/104), and P225H (9.6%; 10/104). Minor mutations associated with PIs (60.0%; 54/90) were predominantly K20I (15.6%; 14/90) and L10F/I/V (14.5%; 13/90). The major mutations associated with PIs (40.0%; 36/90) were M41L (12.2%; 11/90), I84V (6.7%; 06/90), and V82A (6.7%; 06/90). The four most prescribed therapeutic regimens were TDF + 3TC + LPV/r (20.3%; 17/84), ABC + DDI + LPV/r (17.9%; 15/84), TDF + FTC + LPV/r (11.9%; 10/84), and ABC + 3TC + LPV/r (11.9%; 10/84). CONCLUSION: This study revealed that HIV drug resistance mutations are common in Gabon. The major mutations associated with PIs were M41L, I84V, and V82A. There is a need for access to new NRTIs, NNRTIs, and PIs for a better therapeutic management of PLHIV in Gabon.

Modeling and Analysis of HIV-1 Pol Polyprotein as a Case Study for Predicting Large Polyprotein Structures.

Acquired immunodeficiency syndrome (AIDS) is caused by human immunodeficiency virus (HIV). HIV protease, reverse transcriptase, and integrase are targets of current drugs to treat the disease. However, anti-viral drug-resistant strains have emerged quickly due to the high mutation rate of the virus, leading to the demand for the development of new drugs. One attractive target is Gag-Pol polyprotein, which plays a key role in the life cycle of HIV. Recently, we found that a combination of M50I and V151I mutations in HIV-1 integrase can suppress virus release and inhibit the initiation of Gag-Pol autoprocessing and maturation without interfering with the dimerization of Gag-Pol. Additional mutations in integrase or RNase H domain in reverse transcriptase can compensate for the defect. However, the molecular mechanism is unknown. There is no tertiary structure of the full-length HIV-1 Pol protein available for further study. Therefore, we developed a workflow to predict the tertiary structure of HIV-1 NL4.3 Pol polyprotein. The modeled structure has comparable quality compared with the recently published partial HIV-1 Pol structure (PDB ID: 7SJX). Our HIV-1 NL4.3 Pol dimer model is the first full-length Pol tertiary structure. It can provide a structural platform for studying the autoprocessing mechanism of HIV-1 Pol and for developing new potent drugs. Moreover, the workflow can be used to predict other large protein structures that cannot be resolved via conventional experimental methods.

Preclinical characterization of a non-peptidomimetic HIV protease inhibitor with improved metabolic stability.

Protease inhibitors (PIs) remain an important component of antiretroviral therapy for the treatment of HIV-1 infection due to their high genetic barrier to resistance development. Nevertheless, the two most commonly prescribed HIV PIs, atazanavir and darunavir, still require co-administration with a pharmacokinetic boosting agent to maintain sufficient drug plasma levels which can lead to undesirable drug-drug interactions. Herein, we describe GS-9770, a novel investigational non-peptidomimetic HIV PI with unboosted once-daily oral dosing potential due to improvements in its metabolic stability and its pharmacokinetic properties in preclinical animal species. This compound demonstrates potent inhibitory activity and high on-target selectivity for recombinant HIV-1 protease versus other aspartic proteases tested. In cell culture, GS-9770 inhibits Gag polyprotein cleavage and shows nanomolar anti-HIV-1 potency in primary human cells permissive to HIV-1 infection and against a broad range of HIV subtypes. GS-9770 demonstrates an improved resistance profile against a panel of patient-derived HIV-1 isolates with resistance to atazanavir and darunavir. In resistance selection experiments, GS-9770 prevented the emergence of breakthrough HIV-1 variants at all fixed drug concentrations tested and required multiple protease substitutions to enable outgrowth of virus exposed to escalating concentrations of GS-9770. This compound also remained fully active against viruses resistant to drugs from other antiviral classes and showed no in vitro antagonism when combined pairwise with drugs from other antiretroviral classes. Collectively, these preclinical data identify GS-9770 as a potent, non-peptidomimetic once-daily oral HIV PI with potential to overcome the persistent requirement for pharmacological boosting with this class of antiretroviral agents.

Web Service for HIV Drug Resistance Prediction Based on Analysis of Amino Acid Substitutions in Main Drug Targets.

Predicting viral drug resistance is a significant medical concern. The importance of this problem stimulates the continuous development of experimental and new computational approaches. The use of computational approaches allows researchers to increase therapy effectiveness and reduce the time and expenses involved when the prescribed antiretroviral therapy is ineffective in the treatment of infection caused by the human immunodeficiency virus type 1 (HIV-1). We propose two machine learning methods and the appropriate models for predicting HIV drug resistance related to amino acid substitutions in HIV targets: (i) k-mers utilizing the random forest and the support vector machine algorithms of the scikit-learn library, and (ii) multi-n-grams using the Bayesian approach implemented in MultiPASSR software. Both multi-n-grams and k-mers were computed based on the amino acid sequences of HIV enzymes: reverse transcriptase and protease. The performance of the models was estimated by five-fold cross-validation. The resulting classification models have a relatively high reliability (minimum accuracy for the drugs is 0.82, maximum: 0.94) and were used to create a web application, HVR (HIV drug Resistance), for the prediction of HIV drug resistance to protease inhibitors and nucleoside and non-nucleoside reverse transcriptase inhibitors based on the analysis of the amino acid sequences of the appropriate HIV proteins from clinical samples.

HIV-1 reverse transcriptase stability correlates with Gag cleavage efficiency: reverse transcriptase interaction implications for modulating protease activation.

Proteolytic processing of human immunodeficiency virus type 1 particles mediated by viral protease (PR) is essential for acquiring virus infectivity. Activation of PR embedded in Gag-Pol is triggered by Gag-Pol dimerization during virus assembly. We previously reported that amino acid substitutions at the RT tryptophan repeat motif destabilize virus-associated RT and attenuate the ability of efavirenz (EFV, an RT dimerization enhancer) to increase PR-mediated Gag cleavage efficiency. Furthermore, a single amino acid change at RT significantly reduces virus yields due to enhanced Gag cleavage. These data raise the possibility of the RT domain contributing to PR activation by promoting Gag-Pol dimerization. To test this hypothesis, we investigated the putative involvement of a hydrophobic leucine repeat motif (LRM) spanning RT L282 to L310 in RT/RT interactions. We found that LRM amino acid substitutions led to RT instability and that RT is consequently susceptible to degradation by PR. The LRM mutants exhibited reduced Gag cleavage efficiencies while attenuating the EFV enhancement of Gag cleavage. In addition, an RT dimerization-defective mutant, W401A, reduced enhanced Gag cleavage via a leucine zipper (LZ) motif inserted at the deleted Gag-Pol region. Importantly, the presence of RT and integrase domains failed to counteract the LZ enhancement of Gag cleavage. A combination of the Gag cleavage enhancement factors EFV and W402A markedly impaired Gag cleavage, indicating a disruption of W402A Gag-Pol dimerization following EFV binding to W402A Gag-Pol. Our results support the idea that RT modulates PR activation by affecting Gag-Pol/Gag-Pol interaction. IMPORTANCE A stable reverse transcriptase (RT) p66/51 heterodimer is required for HIV-1 genome replication in host cells following virus entry. The activation of viral protease (PR) to mediate virus particle processing helps viruses acquire infectivity following cell release. RT and PR both appear to be major targets for inhibiting HIV-1 replication. We found a strong correlation between impaired p66/51RT stability and deficient PR-mediated Gag cleavage, suggesting that RT/RT interaction is critical for triggering PR activation via the promotion of adequate Gag-Pol dimerization. Accordingly, RT/RT interaction is a potentially advantageous method for anti-HIV/AIDS therapy if it is found to simultaneously block PR and RT enzymatic activity.

HIV Protease Hinge Region Insertions at Codon 38 Affect Enzyme Kinetics, Conformational Stability and Dynamics.

HIV-1 protease is essential for the production of mature, infectious virions and is a major target in antiretroviral therapy. We successfully purified a HIV-1 subtype C variant, L38↑N↑L- 4, containing an insertion of asparagine and leucine at position 38 without the four background mutations - K20R, E35D, R57K, V82I using a modified purification protocol. Isothermal titration calorimetry indicated that 50% of the variant protease sample was in the active conformation compared to 62% of the wild type protease. The secondary structure composition of the variant protease was unaffected by the double insertion. The specific activity and kcat values of the variant protease were approximately 50% lower than the wild type protease values. The variant protease also exhibited a 1.6-fold increase in kcat/KM when compared to the wild type protease. Differential scanning calorimetry showed a 5 °C increase in Tm of the variant protease, indicating the variant was more stable than the wild type. Molecular dynamics simulations indicated the variant was more stable and compact than the wild type protease. A 3-4% increase in the flexibility of the hinge regions of the variant protease was observed. In addition, increased flexibility of the flaps, cantilever and fulcrum regions of the variant protease B chain was observed. The variant protease sampled only the closed flap conformation indicating a potential mechanism for drug resistance. The present study highlights the direct impact of a double amino acid insertion in hinge region on enzyme kinetics, conformational stability and dynamics of an HIV-1 subtype C variant protease.

HIV-1 protease inhibitors with a P1 phosphonate modification maintain potency against drug-resistant variants by increased interactions with flap residues.

Protease inhibitors are the most potent antivirals against HIV-1, but they still lose efficacy against resistant variants. Improving the resistance profile is key to developing more robust inhibitors, which may be promising candidates for simplified next-generation antiretroviral therapies. In this study, we explored analogs of darunavir with a P1 phosphonate modification in combination with increasing size of the P1' hydrophobic group and various P2' moieties to improve potency against resistant variants. The phosphonate moiety substantially improved potency against highly mutated and resistant HIV-1 protease variants, but only when combined with more hydrophobic moieties at the P1' and P2' positions. Phosphonate analogs with a larger hydrophobic P1' moiety maintained excellent antiviral potency against a panel of highly resistant HIV-1 variants, with significantly improved resistance profiles. The cocrystal structures indicate that the phosphonate moiety makes extensive hydrophobic interactions with the protease, especially with the flap residues. Many residues involved in these protease-inhibitor interactions are conserved, enabling the inhibitors to maintain potency against highly resistant variants. These results highlight the need to balance inhibitor physicochemical properties by simultaneous modification of chemical groups to further improve resistance profiles.

Towards designing of a potential new HIV-1 protease inhibitor using QSAR study in combination with Molecular docking and Molecular dynamics simulations.

Human Immunodeficiency Virus type 1 protease (HIV-1 PR) is one of the most challenging targets of antiretroviral therapy used in the treatment of AIDS-infected people. The performance of protease inhibitors (PIs) is limited by the development of protease mutations that can promote resistance to the treatment. The current study was carried out using statistics and bioinformatics tools. A series of thirty-three compounds with known enzymatic inhibitory activities against HIV-1 protease was used in this paper to build a mathematical model relating the structure to the biological activity. These compounds were designed by software; their descriptors were computed using various tools, such as Gaussian, Chem3D, ChemSketch and MarvinSketch. Computational methods generated the best model based on its statistical parameters. The model's applicability domain (AD) was elaborated. Furthermore, one compound has been proposed as efficient against HIV-1 protease with comparable biological activity to the existing ones; this drug candidate was evaluated using ADMET properties and Lipinski's rule. Molecular Docking performed on Wild Type, and Mutant Type HIV-1 proteases allowed the investigation of the interaction types displayed between the proteases and the ligands, Darunavir (DRV) and the new drug (ND). Molecular dynamics simulation was also used in order to investigate the complexes' stability allowing a comparative study on the performance of both ligands (DRV & ND). Our study suggested that the new molecule showed comparable results to that of darunavir and maybe used for further experimental studies. Our study may also be used as pipeline to search and design new potential inhibitors of HIV-1 proteases.

Cellular Targets of HIV-1 Protease: Just the Tip of the Iceberg?

Human immunodeficiency virus 1 (HIV-1) viral protease (PR) is one of the most studied viral enzymes and a crucial antiviral target. Despite its well-characterized role in virion maturation, an increasing body of research is starting to focus on its ability to cleave host cell proteins. Such findings are apparently in contrast with the dogma of HIV-1 PR activity being restricted to the interior of nascent virions and suggest catalytic activity within the host cell environment. Given the limited amount of PR present in the virion at the time of infection, such events mainly occur during late viral gene expression, mediated by newly synthesized Gag-Pol polyprotein precursors, rather than before proviral integration. HIV-1 PR mainly targets proteins involved in three different processes: those involved in translation, those controlling cell survival, and restriction factors responsible for innate/intrinsic antiviral responses. Indeed, by cleaving host cell translation initiation factors, HIV-1 PR can impair cap-dependent translation, thus promoting IRES-mediated translation of late viral transcripts and viral production. By targeting several apoptotic factors, it modulates cell survival, thus promoting immune evasion and viral dissemination. Additionally, HIV-1 PR counteracts restriction factors incorporated in the virion that would otherwise interfere with nascent virus vitality. Thus, HIV-1 PR appears to modulate host cell function at different times and locations during its life cycle, thereby ensuring efficient viral persistency and propagation. However, we are far from having a complete picture of PR-mediated host cell modulation, which is emerging as a field that needs further investigation.

Understanding Drug Resistance of Wild-Type and L38HL Insertion Mutant of HIV-1 C Protease to Saquinavir.

Acquired immunodeficiency syndrome (AIDS) is one of the most challenging infectious diseases to treat on a global scale. Understanding the mechanisms underlying the development of drug resistance is necessary for novel therapeutics. HIV subtype C is known to harbor mutations at critical positions of HIV aspartic protease compared to HIV subtype B, which affects the binding affinity. Recently, a novel double-insertion mutation at codon 38 (L38HL) was characterized in HIV subtype C protease, whose effects on the interaction with protease inhibitors are hitherto unknown. In this study, the potential of L38HL double-insertion in HIV subtype C protease to induce a drug resistance phenotype towards the protease inhibitor, Saquinavir (SQV), was probed using various computational techniques, such as molecular dynamics simulations, binding free energy calculations, local conformational changes and principal component analysis. The results indicate that the L38HL mutation exhibits an increase in flexibility at the hinge and flap regions with a decrease in the binding affinity of SQV in comparison with wild-type HIV protease C. Further, we observed a wide opening at the binding site in the L38HL variant due to an alteration in flap dynamics, leading to a decrease in interactions with the binding site of the mutant protease. It is supported by an altered direction of motion of flap residues in the L38HL variant compared with the wild-type. These results provide deep insights into understanding the potential drug resistance phenotype in infected individuals.

Highly Ambiguous HIV-1 Pol Positions Encoding Multiple Amino Acids Usually Result from Antiviral or Immune Selection Pressure.

HIV-1 pol nucleotide ambiguities encoding amino acid mixtures occur commonly during population-based genotypic drug resistance testing. However, few studies have addressed the validity of sequences with fully ambiguous codons (FACs) containing codons translatable to more than four amino acids. We identified 839 published HIV-1 pol sequences with 846 FACs at 131 positions and determined their distribution relative to 215 HLA-associated pol positions (HAPs) and 84 drug-resistance positions. Among HIV-1 reverse transcriptase (RT) and protease sequences from antiretroviral therapy (ART)-naive and -experienced persons, there was a strong correlation between the likelihood a position was a FAC and that it was an HAP (Spearman's correlation coefficient rho >0.40; p < 1e-6). Among HIV-1 RT sequences from ART-experienced persons, there was a correlation between the likelihood that a position was a FAC and that it was a drug-resistance position (rho = 0.2; p = 8e-4). In the context of population-based genotypic resistance testing, FACs usually result from antiviral or immune selection pressure.

Different Mutation Tolerance of Lentiviral (HIV-1) and Deltaretroviral (BLV and HTLV) Protease Precursors.

The bovine leukemia virus (BLV) and the human T-lymphothropic viruses (HTLVs) are members of the deltaretrovirus genus of Retroviridae family. An essential event of the retroviral life cycle is the processing of the polyproteins by the viral protease (PR); consequently, these enzymes became important therapeutic targets of the anti-retroviral drugs. As compared to human immunodeficiency viruses (HIVs), the deltaretroviruses have a different replication strategy, as they replicate predominantly in the DNA form, by forcing the infected cell to divide, unlike HIV-1, which replicates mainly by producing a vast number of progeny virions and by reinfection. Due to bypassing the error-prone reverse transcription step of replication, the PRs of deltaretroviruses did not undergo such extensive evolution as HIV PRs and remained more highly conserved. In this work, we studied the abilities of wild-type and modified BLV, HTLV (type 1, 2 and 3), and HIV-1 PRs (fused to an N-terminal MBP tag) for self-processing. We designed a cleavage site mutant MBP-fused BLV PR precursor as well, this recombinant enzyme was unable for self-proteolysis, the MBP fusion tag decreased its catalytic efficiency but showed an unusually low Ki for the IB-268 protease inhibitor. Our results show that the HTLV and BLV deltaretrovirus PRs exhibit lower mutation tolerance as compared to HIV-1 PR, and are less likely to retain their activity upon point mutations at various positions, indicating a higher flexibility of HIV-1 PR in tolerating mutations under selective pressure.

Protease and gag diversity and drug resistance mutations among treatment-naive Mexican people living with HIV.

INTRODUCTION: In Mexico, HIV genotyping is performed in people living with HIV (PLWH) failing their first-line antiretroviral (ARV) regimen; it is not routinely done for all treatment-naive PLWH before ARV initiation. The first nationally representative survey published in 2016 reported that the prevalence of pretreatment drug mutations in treatment-naive Mexican PLWH was 15.5% to any antiretroviral drug and 10.6% to non-nucleoside reverse transcriptase inhibitors (NNRTIs) using conventional Sanger sequencing. Most reports in Mexico focus on HIV pol gene and nucleoside and non-nucleoside reverse transcriptase inhibitor (NRTI and NNRTI) drug resistance mutations (DRMs) prevalence, using Sanger sequencing, next-generation sequencing (NGS) or both. To our knowledge, NGS has not be used to detect pretreatment drug resistance mutations (DRMs) in the HIV protease (PR) gene and its substrate the Gag polyprotein. METHODS: Treatment-naive adult Mexican PLWH were recruited between 2016 and 2019. HIV Gag and protease sequences were obtained by NGS and DRMs were identified using the WHO surveillance drug resistance mutation (SDRM) list. RESULTS: One hundred PLWH attending a public national reference hospital were included. The median age was 28 years-old, and most were male. The median HIV viral load was 4.99 [4.39-5.40] log copies/mL and median CD4 cell count was 150 [68.0-355.78] cells/mm3. As expected, most sequences clustered with HIV-1 subtype B (97.9%). Major PI resistance mutations were detected: 8 (8.3%) of 96 patients at a detection threshold of 1% and 3 (3.1%) at a detection threshold of 20%. A total of 1184 mutations in Gag were detected, of which 51 have been associated with resistance to PI, most of them were detected at a threshold of 20%. Follow-up clinical data was available for 79 PLWH at 6 months post-ART initiation, seven PLWH failed their first ART regimen; however no major PI mutations were identified in these individuals at baseline. CONCLUSIONS: The frequency of DRM in the HIV protease was 7.3% at a detection threshold of 1% and 3.1% at a detection threshold of 20%. NGS-based HIV drug resistance genotyping provide improved detection of DRMs. Viral load was used to monitor ARV response and treatment failure was 8.9%.

Potential Resistance of SARS-CoV-2 Main Protease (Mpro) against Protease Inhibitors: Lessons Learned from HIV-1 Protease.

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome 2 (SARS-CoV-2), has been one of the most devastating pandemics of recent times. The lack of potent novel antivirals had led to global health crises; however, emergence and approval of potent inhibitors of the viral main protease (Mpro), such as Pfizer's newly approved nirmatrelvir, offers hope not only in the therapeutic front but also in the context of prophylaxis against the infection. By their nature, RNA viruses including human immunodeficiency virus (HIV) have inherently high mutation rates, and lessons learnt from previous and currently ongoing pandemics have taught us that these viruses can easily escape selection pressure through mutation of vital target amino acid residues in monotherapeutic settings. In this paper, we review nirmatrelvir and its binding to SARS-CoV-2 Mpro and draw a comparison to inhibitors of HIV protease that were rendered obsolete by emergence of resistance mutations, emphasizing potential pitfalls in the design of inhibitors that may be of important relevance to the long-term use of novel inhibitors against SARS-CoV-2.

HIV-1 drug resistance profiling using amino acid sequence space cartography.

MOTIVATION: Human immunodeficiency virus (HIV) drug resistance is a global healthcare issue. The emergence of drug resistance influenced the efficacy of treatment regimens, thus stressing the importance of treatment adaptation. Computational methods predicting the drug resistance profile from genomic data of HIV isolates are advantageous for monitoring drug resistance in patients. However, existing computational methods for drug resistance prediction are either not suitable for emerging HIV strains with complex mutational patterns or lack interpretability, which is of paramount importance in clinical practice. The approach reported here overcomes these limitations and combines high accuracy of predictions and interpretability of the models. RESULTS: In this work, a new methodology based on generative topographic mapping (GTM) for biological sequence space representation and quantitative genotype-phenotype relationships prediction purposes was introduced. The GTM-based resistance landscapes allowed us to predict the resistance of HIV strains based on sequencing and drug resistance data for three viral proteins [integrase (IN), protease (PR) and reverse transcriptase (RT)] from Stanford HIV drug resistance database. The average balanced accuracy for PR inhibitors was 0.89 ± 0.01, for IN inhibitors 0.85 ± 0.01, for non-nucleoside RT inhibitors 0.73 ± 0.01 and for nucleoside RT inhibitors 0.84 ± 0.01. We have demonstrated in several case studies that GTM-based resistance landscapes are useful for visualization and analysis of sequence space as well as for treatment optimization purposes. Here, GTMs were applied for the in-depth analysis of the relationships between mutation pattern and drug resistance using mutation landscapes. This allowed us to predict retrospectively the importance of the presence of particular mutations (e.g. V32I, L10F and L33F in HIV PR) for the resistance development. This study highlights some perspectives of GTM applications in clinical informatics and particularly in the field of sequence space exploration. AVAILABILITY AND IMPLEMENTATION: https://github.com/karinapikalyova/ISIDASeq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prediction and molecular field view of drug resistance in HIV-1 protease mutants.

Conquering the mutational drug resistance is a great challenge in anti-HIV drug development and therapy. Quantitatively predicting the mutational drug resistance in molecular level and elucidating the three dimensional structure-resistance relationships for anti-HIV drug targets will help to improve the understanding of the drug resistance mechanism and aid the design of resistance evading inhibitors. Here the MB-QSAR (Mutation-dependent Biomacromolecular Quantitative Structure Activity Relationship) method was employed to predict the molecular drug resistance of HIV-1 protease mutants towards six drugs, and to depict the structure resistance relationships in HIV-1 protease mutants. MB-QSAR models were constructed based on a published data set of Ki values for HIV-1 protease mutants against drugs. Reliable MB-QSAR models were achieved and these models display both well internal and external prediction abilities. Interpreting the MB-QSAR models supplied structural information related to the drug resistance as well as the guidance for the design of resistance evading drugs. This work showed that MB-QSAR method can be employed to predict the resistance of HIV-1 protease caused by polymorphic mutations, which offer a fast and accurate method for the prediction of other drug target within the context of 3D structures.

Amino acid substitutions at the HIV-1 transframe region significantly impair virus infectivity.

A transframe region within HIV-1 Gag-Pol (referred to as p6* or p6pol), directly linked to the protease (PR) N-terminus, plays a pivotal role in modulating PR activation. To identify specific p6* residues involved in PR activation, we created a series of p6* mutants by making substitutions for conserved p6* residues. Our results indicate that some p6* mutants were defective in terms of virus infectivity, despite displaying a wild-type virus particle processing pattern. Mutations at p6* F8 reduced virus infectivity associated with insufficient virus processing, due in part to impaired PR maturation and RT packaging. Our data strongly suggest that conserved Phe (F) residues at position 8 of p6* are involved in the PR maturation process.

Detection of Gag C-terminal mutations among HIV-1 non-B subtypes in a subset of Cameroonian patients.

Response to ritonavir-boosted-protease inhibitors (PI/r)-based regimen is associated with some Gag mutations among HIV-1 B-clade. There is limited data on Gag mutations and their covariation with mutations in protease among HIV-1 non-B-clades at PI/r-based treatment failure. Thus, we characterized Gag mutations present in isolates from HIV-1 infected individuals treated with a PI/r-regimen (n = 143) and compared them with those obtained from individuals not treated with PI/r (ART-naïve [n = 101] or reverse transcriptase inhibitors (RTI) treated [n = 118]). The most frequent HIV-1 subtypes were CRF02_AG (54.69%), A (13.53%), D (6.35%) and G (4.69%). Eighteen Gag mutations showed a significantly higher prevalence in PI/r-treated isolates compared to ART-naïve (p < 0.05): Group 1 (prevalence < 1% in drug-naïve): L449F, D480N, L483Q, Y484P, T487V; group 2 (prevalence 1-5% in drug-naïve): S462L, I479G, I479K, D480E; group 3 (prevalence ≥ 5% in drug-naïve): P453L, E460A, R464G, S465F, V467E, Q474P, I479R, E482G, T487A. Five Gag mutations (L449F, P453L, D480E, S465F, Y484P) positively correlated (Phi ≥ 0.2, p < 0.05) with protease-resistance mutations. At PI/r-failure, no significant difference was observed between patients with and without these associated Gag mutations in term of viremia or CD4 count. This analysis suggests that some Gag mutations show an increased frequency in patients failing PIs among HIV-1 non-B clades.

Limits to detecting epistasis in the fitness landscape of HIV.

The rapid evolution of HIV is constrained by interactions between mutations which affect viral fitness. In this work, we explore the role of epistasis in determining the mutational fitness landscape of HIV for multiple drug target proteins, including Protease, Reverse Transcriptase, and Integrase. Epistatic interactions between residues modulate the mutation patterns involved in drug resistance, with unambiguous signatures of epistasis best seen in the comparison of the Potts model predicted and experimental HIV sequence "prevalences" expressed as higher-order marginals (beyond triplets) of the sequence probability distribution. In contrast, experimental measures of fitness such as viral replicative capacities generally probe fitness effects of point mutations in a single background, providing weak evidence for epistasis in viral systems. The detectable effects of epistasis are obscured by higher evolutionary conservation at sites. While double mutant cycles in principle, provide one of the best ways to probe epistatic interactions experimentally without reference to a particular background, we show that the analysis is complicated by the small dynamic range of measurements. Overall, we show that global pairwise interaction Potts models are necessary for predicting the mutational landscape of viral proteins.

Co-evolution of drug resistance and broadened substrate recognition in HIV protease variants isolated from an Escherichia coli genetic selection system.

A genetic selection system for activity of HIV protease is described that is based on a synthetic substrate constructed as a modified AraC regulatory protein that when cleaved stimulate l-arabinose metabolism in an Escherichia coli araC strain. Growth stimulation on selective plates was shown to depend on active HIV protease and the scissile bond in the substrate. In addition, the growth of cells correlated well with the established cleavage efficiency of the sites in the viral polyprotein, Gag, when these sites were individually introduced into the synthetic substrate of the selection system. Plasmids encoding protease variants selected based on stimulation of cell growth in the presence of saquinavir or cleavage of a site not cleaved by wild-type protease, were indistinguishable with respect to both phenotypes. Also, both groups of selected plasmids encoded side chain substitutions known from clinical isolates or displayed different side chain substitutions but at identical positions. One highly frequent side chain substitution, E34V, not regarded as a major drug resistance substitution was found in variants obtained under both selective conditions and is suggested to improve protease processing of the synthetic substrate. This substitution is away from the substrate-binding cavity and together with other substitutions in the selected reading frames supports the previous suggestion of a substrate-binding site extended from the active site binding pocket itself.