Novel combinatorial approach: Harnessing HIV protease inhibitors to enhance amphotericin B's antifungal efficacy in cryptococcosis.

Cryptococcosis is a fungal infection that is becoming increasingly prevalent worldwide, particularly among individuals with compromised immune systems, such as HIV patients. Amphotericin B (AmB) is the first-line treatment mainly combined with flucytosine. The scarcity and the prohibitive cost of this regimen urge the use of fluconazole as an alternative, leading to increased rates of treatment failure and relapses. Therefore, there is a critical need for efficient and cost-effective therapy to enhance the efficacy of AmB. In this study, we evaluated the efficacy of the HIV protease inhibitors (PIs) to synergize the activity of AmB in the treatment of cryptococcosis. Five PIs (ritonavir, atazanavir, saquinavir, lopinavir, and nelfinavir) were found to synergistically potentiate the killing activity of AmB against Cryptococcus strains with Æ©FICI ranging between 0.09 and 0.5 against 20 clinical isolates. This synergistic activity was further confirmed in a time-kill assay, where different AmB/PIs combinations exhibited fungicidal activity within 24 hrs. Additionally, PIs in combination with AmB exhibited an extended post-antifungal effect on treated cryptococcal cells for approximately 10 hrs compared to 4 hours with AmB alone. This promising activity against cryptococcal cells did not exhibit increased cytotoxicity towards treated kidney cells, ruling out the risk of drug combination-induced nephrotoxicity. Finally, we evaluated the efficacy of AmB/PIs combinations in the Caenorhabditis elegans model of cryptococcosis, where these combinations significantly reduced the fungal burden of the treated nematodes by approximately 2.44 Log10 CFU (92.4%) compared to the untreated worms and 1.40 Log10 ((39.4%) compared to AmB alone. The cost-effectiveness and accessibility of PIs in resource-limited geographical areas compared to other antifungal agents, such as flucytosine, make them an appealing choice for combination therapy.

Resistance to protease inhibitors among persons living with HIV in Ghana: a case for viral load and drug resistance monitoring.

OBJECTIVE: Routine viral load and drug resistance testing are well supported in most resource-rich settings and provide valuable benefits in the clinical care of PLWH in these communities. Undoubtedly, there exist financial and political constraints for the scale-up of viral load and drug resistance testing in Sub-Saharan Africa. To achieve the global UNAIDS 95/95/95 targets, there is the need to bridge this inequity in patient care and allow for a universal approach that leaves no community behind. METHODS: Venous blood from 96 PLWH on second-line ART from Korle-Bu Teaching Hospital were collected and processed into plasma for CD4+ T- cell and viral load assessments. Ribonucleic acid (RNA) was extracted from stored plasma and the protease gene amplified, sequenced and analyzed for subtype and drug resistance mutations using the Stanford HIV drug resistance database. RESULTS: Out of the 96 PLWH, 37 experienced virological failure with 8 patients' samples successfully sequenced. The predominant HIV-1 subtype identified was CRF02_AG (6/8, 75.0%) with 12.5% (1/8) each of CFR06_cpx infection and one case unable to subtype. The major PI resistance mutations identified were; M46I, I54V, V82A, I47V, I84V and L90M. CONCLUSIONS: Persons living with HIV who had experienced virologic failure in this study harboured drug resistance mutations to PI, thus compromise the effectiveness of the drugs in the second line. Resistance testing is strongly recommended prior to switching to a new regimen. This will help to inform the choice of drug and to achieve optimum therapeutic outcome among PLWH in Ghana.

Quantitative Prediction of Human Immunodeficiency Virus Drug Resistance.

Drug resistance of pathogens, including viruses, is one of the reasons for decreased efficacy of therapy. Considering the impact of HIV type 1 (HIV-1) on the development of progressive immune dysfunction and the rapid development of drug resistance, the analysis of HIV-1 resistance is of high significance. Currently, a substantial amount of data has been accumulated on HIV-1 drug resistance that can be used to build both qualitative and quantitative models of HIV-1 drug resistance. Quantitative models of drug resistance can enrich the information about the efficacy of a particular drug in the scheme of antiretroviral therapy. In our study, we investigated the possibility of developing models for quantitative prediction of HIV-1 resistance to eight protease inhibitors based on the analysis of amino acid sequences of HIV-1 protease for 900 virus variants. We developed random forest regression (RFR), support vector regression (SVR), and self-consistent regression (SCR) models using binary vectors containing values from 0 or 1, depending on the presence of a specific peptide fragment in each amino acid sequence as independent variables, while fold ratio, reflecting the level of resistance, was the predicted variable. The SVR and SCR models showed the highest predictive performances. The models built demonstrate reasonable performances for eight out of nine (R2 varied from 0.828 to 0.909) protease inhibitors, while R2 for predicting tipranavir fold ratio was lower (R2 was 0.642). We believe that the developed approach can be applied to evaluate drug resistance of molecular targets of other viruses where appropriate experimental data are available.

LSTM-driven drug design using SELFIES for target-focused de novo generation of HIV-1 protease inhibitor candidates for AIDS treatment.

The battle against viral drug resistance highlights the need for innovative approaches to replace time-consuming and costly traditional methods. Deep generative models offer automation potential, especially in the fight against Human immunodeficiency virus (HIV), as they can synthesize diverse molecules effectively. In this paper, an application of an LSTM-based deep generative model named "LSTM-ProGen" is proposed to be tailored explicitly for the de novo design of drug candidate molecules that interact with a specific target protein (HIV-1 protease). LSTM-ProGen distinguishes itself by employing a long-short-term memory (LSTM) architecture, to generate novel molecules target specificity against the HIV-1 protease. Following a thorough training process involves fine-tuning LSTM-ProGen on a diverse range of compounds sourced from the ChEMBL database. The model was optimized to meet specific requirements, with multiple iterations to enhance its predictive capabilities and ensure it generates molecules that exhibit favorable target interactions. The training process encompasses an array of performance evaluation metrics, such as drug-likeness properties. Our evaluation includes extensive silico analysis using molecular docking and PCA-based visualization to explore the chemical space that the new molecules cover compared to those in the training set. These evaluations reveal that a subset of 12 de novo molecules generated by LSTM-ProGen exhibit a striking ability to interact with the target protein, rivaling or even surpassing the efficacy of native ligands. Extended versions with further refinement of LSTM-ProGen hold promise as versatile tools for designing efficacious and customized drug candidates tailored to specific targets, thus accelerating drug development and facilitating the discovery of new therapies for various diseases.

Premature Activation of the HIV-1 Protease Is Influenced by Polymorphisms in the Hinge Region.

HIV-1 protease inhibitors are an essential component of antiretroviral therapy. However, drug resistance is a pervasive issue motivating a persistent search for novel therapies. Recent reports found that when protease activates within the host cell's cytosol, it facilitates the pyroptotic killing of infected cells. This has led to speculation that promoting protease activation, rather than inhibiting it, could help to eradicate infected cells and potentially cure HIV-1 infection. Here, we used a nanoscale flow cytometry-based assay to characterize protease resistance mutations and polymorphisms. We quantified protease activity, viral concentration, and premature protease activation and confirmed previous findings that major resistance mutations generally destabilize the protease structure. Intriguingly, we found evidence that common polymorphisms in the hinge domain of protease can influence its susceptibility to premature activation. This suggests that viral heterogeneity could pose a considerable challenge for therapeutic strategies aimed at inducing premature protease activation in the future.

Natural Polymorphisms D60E and I62V Stabilize a Closed Conformation in HIV-1 Protease in the Absence of an Inhibitor or Substrate.

HIV infection remains a global health issue plagued by drug resistance and virological failure. Natural polymorphisms (NPs) contained within several African and Brazilian protease (PR) variants have been shown to induce a conformational landscape of more closed conformations compared to the sequence of subtype B prevalent in North America and Western Europe. Here we demonstrate through experimental pulsed EPR distance measurements and molecular dynamic (MD) simulations that the two common NPs D60E and I62V found within subtypes F and H can induce a closed conformation when introduced into HIV-1PR subtype B. Specifically, D60E alters the conformation in subtype B through the formation of a salt bridge with residue K43 contained within the nexus between the flap and hinge region of the HIV-1 PR fold. On the other hand, I62V modulates the packing of the hydrophobic cluster of the cantilever and fulcrum, also resulting in a more closed conformation.

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.

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors.

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Machine learning-guided design of potent darunavir analogs targeting HIV-1 proteases: A computational approach for antiretroviral drug discovery.

In the pursuit of novel antiretroviral therapies for human immunodeficiency virus type-1 (HIV-1) proteases (PRs), recent improvements in drug discovery have embraced machine learning (ML) techniques to guide the design process. This study employs ensemble learning models to identify crucial substructures as significant features for drug development. Using molecular docking techniques, a collection of 160 darunavir (DRV) analogs was designed based on these key substructures and subsequently screened using molecular docking techniques. Chemical structures with high fitness scores were selected, combined, and one-dimensional (1D) screening based on beyond Lipinski's rule of five (bRo5) and ADME (absorption, distribution, metabolism, and excretion) prediction implemented in the Combined Analog generator Tool (CAT) program. A total of 473 screened analogs were subjected to docking analysis through convolutional neural networks scoring function against both the wild-type (WT) and 12 major mutated PRs. DRV analogs with negative changes in binding free energy ( ΔΔ G bind ) compared to DRV could be categorized into four attractive groups based on their interactions with the majority of vital PRs. The analysis of interaction profiles revealed that potent designed analogs, targeting both WT and mutant PRs, exhibited interactions with common key amino acid residues. This observation further confirms that the ML model-guided approach effectively identified the substructures that play a crucial role in potent analogs. It is expected to function as a powerful computational tool, offering valuable guidance in the identification of chemical substructures for synthesis and subsequent experimental testing.

Advanced molecular mechanisms of modified DRV compounds in targeting HIV-1 protease mutations and interrupting monomer dimerization.

HIV-1 protease (PR) plays a crucial role in the treatment of HIV as a key target. The global issue of emerging drug resistance is escalating, and PR mutations pose a substantial challenge to the effectiveness of inhibitors. HIV-1 PR is an ideal model for studying drug resistance to inhibitors. The inhibitor, darunavir (DRV), exhibits a high genetic barrier to viral resistance, but with mutations of residues in the PR, there is also some resistance to DRV. Inhibitors can impede PR in two ways: one involves binding to the active site of the dimerization protease, and the other involves binding to the PR monomer, thereby preventing dimerization. In this study, we aimed to investigate the inhibitory effect of DRV with a modified inhibitor on PR, comparing the differences between wild-type and mutated PR, using molecular dynamics simulations. The inhibitory effect of the inhibitors on PR monomers was subsequently investigated. And molecular mechanics Poisson-Boltzmann surface area evaluated the binding free energy. The energy contribution of individual residues in the complex was accurately calculated by the alanine scanning binding interaction entropy method. The results showed that these inhibitors had strong inhibitory effects against PR mutations, with GRL-142 exhibiting potent inhibition of both the PR monomer and dimer. Improved inhibitors could strengthen hydrogen bonds and interactions with PR, thereby boosting inhibition efficacy. The binding of the inhibitor and mutation of the PR affected the distance between D25 and I50, preventing their dimerization and the development of drug resistance. This study could accelerate research targeting HIV-1 PR inhibitors and help to further facilitate drug design targeting both mechanisms.

Enhanced antifungal activity of posaconazole against Candida auris by HIV protease inhibitors, atazanavir and saquinavir.

The increasing incidence and dissemination of multidrug-resistant Candida auris represents a serious global threat. The emergence of pan-resistant C. auris exhibiting resistance to all three classes of antifungals magnifies the need for novel therapeutic interventions. We identified that two HIV protease inhibitors, atazanavir and saquinavir, in combination with posaconazole exhibited potent activity against C. auris in vitro and in vivo. Both atazanavir and saquinavir exhibited a remarkable synergistic activity with posaconazole against all tested C. auris isolates and other medically important Candida species. In a time-kill assay, both drugs restored the fungistatic activity of posaconazole, resulting in reduction of 5 and 5.6 log10, respectively. Furthermore, in contrast to the individual drugs, the two combinations effectively inhibited the biofilm formation of C. auris by 66.2 and 81.2%, respectively. Finally, the efficacy of the two combinations were tested in a mouse model of C. auris infection. The atazanavir/posaconazole and saquinavir/posaconazole combinations significantly reduced the C. auris burden in mice kidneys by 2.04- (99.1%) and 1.44-log10 (96.4%) colony forming unit, respectively. Altogether, these results suggest that the combination of posaconazole with the HIV protease inhibitors warrants further investigation as a new therapeutic regimen for the treatment of C. auris infections.

A detailed characterization of drug resistance during darunavir/ritonavir monotherapy highlights a high barrier to the emergence of resistance mutations in protease but identifies alternative pathways of resistance.

BACKGROUND: Maintenance monotherapy with ritonavir-boosted darunavir has yielded variable outcomes and is not recommended. Trial samples offer valuable opportunities for detailed studies. We analysed samples from a 48 week trial in Cameroon to obtain a detailed characterization of drug resistance. METHODS: Following failure of NNRTI-based therapy and virological suppression on PI-based therapy, participants were randomized to ritonavir-boosted darunavir (n = 81) or tenofovir disoproxil fumarate/lamivudine +ritonavir-boosted lopinavir (n = 39). At study entry, PBMC-derived HIV-1 DNA underwent bulk Protease and Reverse Transcriptase (RT) sequencing. At virological rebound (confirmed or last available HIV-1 RNA ≥ 60 copies/mL), plasma HIV-1 RNA underwent ultradeep Protease and RT sequencing and bulk Gag-Protease sequencing. The site-directed mutant T375A (p2/p7) was characterized phenotypically using a single-cycle assay. RESULTS: NRTI and NNRTI resistance-associated mutations (RAMs) were detected in 52/90 (57.8%) and 53/90 (58.9%) HIV-1 DNA samples, respectively. Prevalence in rebound HIV-1 RNA (ritonavir-boosted darunavir, n = 21; ritonavir-boosted lopinavir, n = 2) was 9/23 (39.1%) and 10/23 (43.5%), respectively, with most RAMs detected at frequencies ≥15%. The resistance patterns of paired HIV-1 DNA and RNA sequences were partially consistent. No darunavir RAMs were found. Among eight participants experiencing virological rebound on ritonavir-boosted darunavir (n = 12 samples), all had Gag mutations associated with PI exposure, including T375N, T375A (p2/p7), K436R (p7/p1) and substitutions in p17, p24, p2 and p6. T375A conferred 10-fold darunavir resistance and increased replication capacity. CONCLUSIONS: The study highlights the high resistance barrier of ritonavir-boosted darunavir while identifying alternative pathways of resistance through Gag substitutions. During virological suppression, resistance patterns in HIV-1 DNA reflect treatment history, but due to technical and biological considerations, cautious interpretation is warranted.

Resistencia transmitida de VIH-1 en pacientes sin exposición a tratamiento antirretroviral: Guatemala / Transmitted HIV-1 resistance in patients without exposure to antiretroviral treatment: Guatemala / Resistência transmitida ao HIV-1 em pacientes sem exposição ao tratamento antirretroviral: Guatemala

El objetivo del estudio fue describir los niveles de resistencia transmitida de VIH-1 en adultos atendidos en Unidades de Atención Integral de Guatemala. El estudio incluyó registros de 185 pacientes adultos VIH-1 positivo, de reciente diagnóstico sin antecedente de uso de TAR, de noviembre del 2019 a noviembre del 2020. El análisis se realizó en el software DeepChek® v2.0, para la clasificación de la resistencia se siguió el algoritmo de Stanford HIVdb (v9.4 - 07/12/2022). Se encontró 18.4% (IC 95% 13.1 - 24.7%) de resistencia general a alguna familia de ARVs. Se evidenció 15.1% (IC 95% 10.3 - 21.1%) de resistencia individual a la familia de INNTR afectando principalmente a NVP y EFV; 2.2% (IC 95% 0.6 - 5.4%) de resistencia a INTR, mayormente a FTC/3TC; y 2.7% (IC 95% 0.9 - 6.2%) de resistencia intermedia y baja los IP NFV y LPV/r. Tres casos presentaron resistencia múltiple a los INTR + INNTR. Las mutaciones más frecuentemente encontradas fueron K103N (41.2%), M184V/I (8.8%) y M46I (5.9%). La elevada resistencia transmitida del VIH-1 en pacientes atendidos en distintas Unidades de Atención Integral del VIH, demuestra la importancia de analizar periódicamente la tendencia de la resistencia en personas que no han estado expuestas a ARVs, lo cual a su vez es un marcador indirecto de presencia de resistencia adquirida en el país, datos que evidencian la necesidad de acciones e intervenciones prontas y efectivas dado su impacto en la salud pública.

The objective of this study was to describe the levels of transmitted HIV-1 resistance in patients with a recent HIV diagnosis before starting ART, treated in Comprehensive Care Units in Guatemala during the years 2019 and 2020. The study included records of 185 HIV-positive adult patients, recently diagnosed with HIV without a history of ART use. The analysis was carried out in the DeepChek® v2.0 software, the Stanford HIVdb algorithm (v9.4 - 07/12/2022) was followed to classify resistance. 18.4% (95% CI 13.1 - 24.7%) of general resistance to some family of ARVs was found. There was evidence of 15.1% (95% CI 10.3 - 21.1%) of individual resistance to the NNRTI family, mainly affecting NVP and EFV; 2.2% (95% CI 0.6 - 5.4%) resistance to INTR, mostly to FTC/3TC; and 2.7% (95% CI 0.9 - 6.2%) of intermediate and low resistance IP NFV and LPV/r. Three cases presented multiple resistance to NRTIs + NNRTIs. The most frequently found mutations were K103N (41.2%), M184V/I (8.8%) and M46I (5.9%). The high transmitted resistance of HIV-1 in patients treated in different Comprehensive HIV Care Units demonstrates the importance of periodically analyzing the trend of resistance in people who have not been exposed to ARVs, which in turn is an indirect marker. of the presence of acquired resistance in the country, data that demonstrate the need for prompt and effective actions and interventions given its impact on public health.

O objetivo deste estudo foi descrever os níveis de resistência transmitida ao HIV-1 em adultos tratados em Unidades de Cuidados Integrais na Guatemala. O estudo incluiu prontuários de 185 pacientes adultos HIV-1 positivos, recentemente diagnosticados sem histórico de uso de TARV, no período de novembro de 2019 a novembro de 2020. A análise foi realizada no software DeepChek® v2.0, para classificação da resistência, O algoritmo Stanford HIVdb (v9.4 - 07/12/2022) foi seguido. Foi encontrada 18.4% (IC 95% 13.1 - 24.7%) de resistência geral a alguma família de ARVs. Houve evidência de 15.1% (IC 95% 10.3 - 21.1%) de resistência individual à família de NNRTI, afetando principalmente NVP e EFV; 2.2% (IC 95% 0.6 - 5.4%) resistência ao INTR, principalmente ao FTC/3TC; e 2.7% (IC 95% 0.9 - 6.2%) de resistência intermediária e baixa ao IP NFV e LPV/r. Três casos apresentaram resistência múltipla a NRTIs + NNRTIs. As mutações mais frequentemente encontradas foram K103N (41.2%), M184V/I (8.8%) e M46I (5.9%). A elevada resistência transmitida do HIV-1 em pacientes atendidos em diferentes Unidades de Cuidados Integrados ao HIV demonstra a importância de analisar periodicamente a tendência de resistência em pessoas que não foram expostas aos ARVs, o que por sua vez é um marcador indireto da presença de ARVs adquiridos. resistência no país, dados que demonstram a necessidade de ações e intervenções rápidas e eficazes dado o seu impacto na saúde pública.

[Current antiretroviral therapy: A review].

The article presents an overview of clinical recommendations for currant antiretroviral therapy. Currently, the current preferred first-line antiretroviral therapy regimens are combinations of 2 or 3 antiretroviral drugs (ARVs) in one tablet with a frequency of administration 1 time per day and, as a rule, include drugs of the 2nd generation (integrase inhibitors or non-nucleoside reverse transcriptase inhibitors). These schemes have high efficiency and a good genetic barrier in the development of HIV resistance mutations. HIV protease inhibitors are used as alternative regimens. Schemes with the least number and spectrum of side effects, no effect on metabolic processes and minimal drug interactions have advantages. Switching patients to injectable therapy regimens with a frequency of administration of drugs once every 2 months can significantly improve the quality of life of patients and, accordingly, adherence to their treatment. The development and introduction of new classes of ARVs into clinical practice ensures the suppression of HIV replication in most patients with HIV strains resistant to drugs of the main groups of ARVs (nucleoside/nucleotide reverse transcriptase.

Lopinavir and ritonavir act synergistically with azoles against Candida auris in vitro and in a mouse model of disseminated candidiasis.

INTRODUCTION AND OBJECTIVES: The emergence of Candida auris has created a global health challenge. Azole antifungals are the most affected antifungal class because of the extraordinary capability of C. auris to develop resistance against these drugs. Here, we used a combinatorial therapeutic approach to sensitize C. auris to azole antifungals. METHODS AND RESULTS: We have demonstrated the capability of the HIV protease inhibitors lopinavir and ritonavir, at clinically relevant concentrations, to be used with azole antifungals to treat C. auris infections both in vitro and in vivo. Both lopinavir and ritonavir exhibited potent synergistic interactions with the azole antifungals, particularly with itraconazole against 24/24 (100%) and 31/34 (91%) of tested C. auris isolates, respectively. Furthermore, ritonavir significantly interfered with the fungal efflux pump, resulting in a significant increase in Nile red fluorescence by 44%. In a mouse model of C. auris systemic infection, ritonavir boosted the activity of lopinavir to work synergistically with fluconazole and itraconazole and significantly reduced the kidney fungal burden by a 1.2 log (∼94%) and 1.6 log (∼97%) CFU, respectively. CONCLUSION: Our results urge further comprehensive assessment of azoles and HIV protease inhibitors as a novel drug regimen for the treatment of serious invasive C. auris infections.

A Combination of Novel HIV-1 Protease Inhibitor and Cytochrome P450 (CYP) Enzyme Inhibitor to Explore the Future Prospective of Antiviral Agents: Evotaz.

Viruses belong to the class of micro-organisms that are well known for causing infections in the human body. Antiviral medications are given out to prevent the spread of disease-causing viruses. When the viruses are actively reproducing, these agents have their greatest impact. It is particularly challenging to develop virus-specific medications since viruses share the majority of the metabolic functions of the host cell. In the continuous search for better antiviral agents, the United States Food and Drug Administration (USFDA) approved a new drug named Evotaz on January 29, 2015 for the treatment of human immunodeficiency virus (HIV). Evotaz is a combined once-daily fixed drug, containing Atazanavir, an HIV protease inhibitor, and cobicistat, an inhibitor of the human liver cytochrome P450 (CYP) enzyme. The medication is created such that it can kill viruses by concurrently inhibiting protease and CYP enzymes. The medicine is still being studied for a number of criteria, but its usefulness in children under the age of 12 is currently unknown. The preclinical and clinical characteristics of Evotaz, as well as its safety and efficacy profiles and a comparison of the novel drug with antiviral medications presently available in the market, are the main topics of this review paper.

AI-Aided Search for New HIV-1 Protease Ligands.

The availability of drugs capable of blocking the replication of microorganisms has been one of the greatest triumphs in the history of medicine, but the emergence of an ever-increasing number of resistant strains poses a serious problem for the treatment of infectious diseases. The search for new potential ligands for proteins involved in the life cycle of pathogens is, therefore, an extremely important research field today. In this work, we have considered the HIV-1 protease, one of the main targets for AIDS therapy. Several drugs are used today in clinical practice whose mechanism of action is based on the inhibition of this enzyme, but after years of use, even these molecules are beginning to be interested by resistance phenomena. We used a simple artificial intelligence system for the initial screening of a data set of potential ligands. These results were validated by docking and molecular dynamics, leading to the identification of a potential new ligand of the enzyme which does not belong to any known class of HIV-1 protease inhibitors. The computational protocol used in this work is simple and does not require large computational power. Furthermore, the availability of a large number of structural information on viral proteins and the presence of numerous experimental data on their ligands, with which it is possible to compare the results obtained with computational methods, make this research field the ideal terrain for the application of these new computational techniques.

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.

Molecular Factors and Pathways of Hepatotoxicity Associated with HIV/SARS-CoV-2 Protease Inhibitors.

Antiviral protease inhibitors are peptidomimetic molecules that block the active catalytic center of viral proteases and, thereby, prevent the cleavage of viral polyprotein precursors into maturation. They continue to be a key class of antiviral drugs that can be used either as boosters for other classes of antivirals or as major components of current regimens in therapies for the treatment of infections with human immunodeficiency virus (HIV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, sustained/lifelong treatment with the drugs or drugs combined with other substance(s) often leads to severe hepatic side effects such as lipid abnormalities, insulin resistance, and hepatotoxicity. The underlying pathogenic mechanisms are not fully known and are under continuous investigation. This review focuses on the general as well as specific molecular mechanisms of the protease inhibitor-induced hepatotoxicity involving transporter proteins, apolipoprotein B, cytochrome P450 isozymes, insulin-receptor substrate 1, Akt/PKB signaling, lipogenic factors, UDP-glucuronosyltransferase, pregnane X receptor, hepatocyte nuclear factor 4α, reactive oxygen species, inflammatory cytokines, off-target proteases, and small GTPase Rab proteins related to ER-Golgi trafficking, organelle stress, and liver injury. Potential pharmaceutical/therapeutic solutions to antiviral drug-induced hepatic side effects are also discussed.

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.