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.

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.

The Gag-Pol polyprotein in human immunodeficiency virus type I (HIV-1) encodes enzymes that are essential for virus replication: protease (PR), reverse transcriptase (RT), and integrase (IN). The mature forms of PR, RT and IN are homodimer, heterodimer and tetramer, respectively. The precise mechanism underlying the formation of dimer or tetramer is not yet understood. Here, to gain insight into the dimerization of PR and RT in the precursor, we prepared a model precursor, PR-RT, incorporating an inactivating mutation at the PR active site, D25A, and including two residues in the p6* region, fused to a SUMO-tag, at the N-terminus of the PR region. We also prepared two mutants of PR-RT containing a dimer dissociation mutation either in the PR region, PR(T26A)-RT, or in the RT region, PR-RT(W401A). Size exclusion chromatography showed both monomer and dimer fractions in PR-RT and PR(T26A)-RT, but only monomer in PR-RT(W401A). SEC experiments of PR-RT in the presence of protease inhibitor, darunavir, significantly enhanced the dimerization. Additionally, SEC results suggest an estimated PR-RT dimer dissociation constant that is higher than that of the mature RT heterodimer, p66/p51, but slightly lower than the premature RT homodimer, p66/p66. Reverse transcriptase assays and RT maturation assays were performed as tools to assess the effects of the PR dimer-interface on these functions. Our results consistently indicate that the RT dimer-interface plays a crucial role in the dimerization in PR-RT, whereas the PR dimer-interface has a lesser role.

Fullerenes, particularly C60, exhibit unique properties that make them promising candidates for various applications, including drug delivery and nanomedicine. However, their interactions with biomolecules, especially proteins, remain not fully understood. This study implements both explicit and implicit C60 models into the UNRES coarse-grained force field, enabling the investigation of fullerene-protein interactions without the need for restraints to stabilize protein structures. The UNRES force field offers computational efficiency, allowing for longer timescale simulations while maintaining accuracy. Five model proteins were studied: FK506 binding protein, HIV-1 protease, intestinal fatty acid binding protein, PCB-binding protein, and hen egg-white lysozyme. Molecular dynamics simulations were performed with and without C60 to assess protein stability and investigate the impact of fullerene interactions. Analysis of contact probabilities reveals distinct interaction patterns for each protein. FK506 binding protein (1FKF) shows specific binding sites, while intestinal fatty acid binding protein (1ICN) and uteroglobin (1UTR) exhibit more generalized interactions. The explicit C60 model shows good agreement with all-atom simulations in predicting protein flexibility, the position of C60 in the binding pocket, and the estimation of effective binding energies. The integration of explicit and implicit C60 models into the UNRES force field, coupled with recent advances in coarse-grained modeling and multiscale approaches, provides a powerful framework for investigating protein-nanoparticle interactions at biologically relevant scales without the need to use restraints stabilizing the protein, thus allowing for large conformational changes to occur. These computational tools, in synergy with experimental techniques, can aid in understanding the mechanisms and consequences of nanoparticle-biomolecule interactions, guiding the design of nanomaterials for biomedical applications.

HIV genotyping is used to assess HIV susceptibility to antiretroviral drugs. The Applied Biosystems HIV-1 Genotyping Kit with Integrase (AB kit, Thermo Fisher Scientific) detects resistance-associated mutations (RAMs) in HIV protease (PR), reverse transcriptase (RT), and integrase (IN). We compared results from the AB kit with results obtained previously with the ViroSeq HIV-1 Genotyping System. DNA amplicons from the AB kit were also analyzed using next-generation sequencing (NGS). HIV RNA was extracted using the MagNA Pure 24 instrument (Roche Diagnostics; 96 plasma samples, HIV subtype B, viral load range: 530-737,741 copies/mL). FASTA files were generated from AB kit data using Exatype (Hyrax Biosciences). DNA amplicons from the AB kit were also analyzed by NGS using the Nextera XT kit (Illumina). Drug resistance was predicted using the Stanford HIV Drug Resistance Database. The mean genetic distance for sequences from ViroSeq and the AB kit was 0.02% for PR/RT and 0.04% for IN; 103 major RAMs were detected by both methods. Four additional major RAMs were detected by the AB kit only. These four major RAMs were also detected by NGS (detected in 18.1%-38.2% of NGS reads). NGS detected 27 major RAMs that were not detected with either of the Sanger sequencing-based kits. All major RAMs detected with ViroSeq were detected with the AB kit; additional RAMs were detected with the AB kit only. DNA amplicons from the AB kit can be used for NGS for more sensitive detection of RAMs.

Despite increasing scale-up of antiretroviral therapy (ART) coverage, challenges related to adherence and HIV drug resistance (HIVDR) remain. The high cost of HIVDR surveillance is a persistent challenge with implementation in resource-constrained settings. Dried blood spot (DBS) specimens have been demonstrated to be a feasible alternative to plasma or serum for HIVDR genotyping and are more suitable for lower resource settings. There is a need for affordable HIVDR genotyping assays which can amplify HIV-1 sequences from DBS specimens, particularly those with low viral loads, at a low cost. Here, we present an in-house assay capable of reliably amplifying HIV-1 protease and partial reverse transcriptase genes from DBS specimens, which covers the complete World Health Organization 2009 list of drug resistance mutations under surveillance. DBS specimens were prepared using whole blood spiked with HIV-1 at concentrations of 10,000, 5000, 1000, and 500 copies/mL (n=30 for each concentration). Specimens were tested in triplicate. A two-step approach was used consisting of cDNA synthesis followed by nested PCR. The limit of detection of the assay was calculated to be approximately 5000 (95% CI: 3200-10,700) copies/mL for the protease gene and 3600 (95% CI: 2200-10,000) copies/mL for reverse transcriptase. The assay was observed to be most sensitive with higher viral load specimens (97.8% [95% CI: 92.2-99.7]) for both protease and reverse transcriptase at 10,000 copies/mL with performance decreasing with the use of specimens with lower viral loads (46.7% [36.1-57.5] and 60.0% [49.1-70.2] at 500 copies/mL for protease and reverse transcriptase, respectively). Ultimately, this assay presents a promising opportunity for use in resource-constrained settings. Future work should involve validation under field conditions including sub-optimal storage conditions and preparation of DBS with fingerprick blood in order to accurately reflect real-world collection scenarios.

BACKGROUND: 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.
METHODS: 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).
CONCLUSIONS: 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.

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.

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.

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.