HIV-1 protease inhibitors are central to antiretroviral therapy, yet their long-term efficacy is undermined by the rapid emergence of drug-resistant variants. Although virtual screening of small-molecule libraries and resistance prediction have each been used to guide inhibitor design, there is still no integrated framework that jointly optimizes intrinsic potency and robustness to protease mutations at ultra-large chemical scale. Here, we present a multistage, machine learning (ML)-first hierarchical virtual screening pipeline that enables billion-scale prioritization of the ZINC20 chemical space while reserving computationally intensive structure-based analyses for the most promising candidates. Ensemble ML models for wild-type (WT) activity were first used to evaluate the full library (∼1.4 billion compounds) by ML inference, progressively reducing the chemical space to 19,911 candidates with predicted sub-nanomolar activity. These prioritized candidates were then assessed for cross-variant resistance using an LGBM-Chemprop drug-isolate fold-change (DIF) model, followed by molecular docking, MM/GBSA binding free energy calculations, all atom molecular dynamics (MD) simulations, and Neural Relational Inference (NRI) analysis on increasingly focused candidate subsets. This workflow prioritizes three computationally predicted mutation-tolerant candidates, of which ZINC000408994641 shows the most consistent in silico profile, with favorable or comparable predicted binding energetics and efficiency metrics relative to darunavir and tipranavir, and limited predicted loss of affinity across clinically relevant protease variants. These results demonstrate that coupling ML-based large-scale prioritization with structure-based and dynamical validation can prospectively enrich for resistance-robust HIV-1 protease inhibitors and provide a generalizable framework for anticipating drug resistance in rapidly evolving viral targets.

Purinergic receptor (P2X7R), an adenosine triphosphate (ATP) gated nonselective cation channel, is an emerging target for several neurodegenerative conditions, including retinal degeneration. In particular, P2X7R has an established role in multiple inflammatory and immune responses, being implicated in the formation and activation of NLRP3 inflammasome leading to inflammatory priming and release of immune cytokines. Despite several efforts in P2X7R antagonist design, no drugs have reached the market yet. In this perspective, through an integrated in silico and in vitro approach, we aimed to repurpose FDA approved drugs in search of novel safe treatments for retinal degenerative diseases, where P2X7R has been found to play a detrimental role. Virtual screening of about 10,000 FDA approved drugs identified 6 putative P2X7 antagonists. Three out of these six compounds inhibited hP2X7, but not rat receptors, while only one compound, tipranavir, inhibited also mouse P2X7R. Then, for these three P2X7R antagonists, namely bazedoxifene, teniposide and tipranavir, we have evaluated the in vitro tolerability by treating immortalized human Müller cells (MIO-M1), primary retinal endothelial cells (HRECs), human umbilical vein endothelial cells (HUVECs) and human retinal pigmented epithelial cells (hRPEs). Tipranavir and teniposide were well tolerated by the mentioned retinal cells, thereby they have been further evaluated in in vitro models of glaucoma, diabetic retinopathy, and age-related macular degeneration. Tipranavir and teniposide showed retinal cell protection, modulating the expression of HIF-1α, VEGF-A, and inflammatory cytokines. Therefore, these compounds are worthy of further investigation to manage retinal degenerative conditions.

Cervical cancer (CC) is a major contributor to cancer-related deaths. Human papillomavirus (HPV) genotypes, especially HPV16 and HPV18, are the primary causes of CC-related infections. Although the oncogenic potential of HPV is well established, the molecular mechanisms underlying cancer initiation and persistence remain unclear. In this study, the common proteins between the virus-host interaction network and CC proteome datasets were analyzed to identify proteins involved in HPV-driven oncogenesis. Network topology analysis revealed two key viral proteins, viz. VE7_HPV16 and VE6_HPV18, along with subsequent sequence analysis, identified short linear motifs (SLiMs) in each target that may act as potential hotspots for therapeutic interventions. Different in silico validations, such as active site prediction, protein-protein docking and blind docking analysis, were performed to evaluate the therapeutic potential of the SLiMs-containing regions. In the next step, a structure-based virtual screening approach was employed to identify possible antivirals that bind to the active sites (SLiMs-containing regions) of these proteins. Ten candidate drugs, Pleconaril, Pirodavir, Saquinavir, Delavirdine, and Tipranavir for VE7_HPV16 and Beclabuvir, Velpatasvir, Paritaprevir, Odalasvir, and Ledipasvir for VE6_HPV18, were predicted to exhibit high binding affinities with their respective viral targets. Additionally, Molecular Dynamics (MD) simulations were performed to examine the stability of the protein-ligand complexes and evaluate the role of SLiMs-containing regions in modulating virus-host interactions. Collectively, this comprehensive analysis of the virus-host network identified key HPV protein targets and proposed antiviral drug candidates to impede viral contributions to cervical carcinogenesis.

The serine protease 23 (PRSS23) is a highly conserved member of trypsin-like serine proteases, which are associated with numerous essential processes, including digestion, blood coagulation, fibrinolysis, development, fertilization, apoptosis, and immunity. Original reports on PRSS23 unfolded not earlier than 2006 when a molecular biology study characterized and described PRSS23 as an ovarian protease. Then, in 2012, another important study was published linking PRSS23 with proliferation of breast cancer cells by an estrogen receptor 1 (ESR1)-dependent transcriptional activation of the serine protease. Thereafter, a developmental study in zebrafish reported the implication of PRSS23 in endothelial-to-mesenchymal transition (EndMT) during cardiac valve formation. Although these early studies on PRSS23 have revealed its involvement in some critical or fundamental processes, only in recent years an increasing number of studies have evolved describing the expression and functions of PRSS23 in various normal physiological conditions, diseases, and experimental configurations. Besides breast cancer, PRSS23 has been shown to be involved in different types of malignancies, e.g., in gastric cancer, where drug screening found that the protease inhibitor tipranavir impedes cancer-promoting PRSS23 expression. New innovative techniques such as single cell RNA-sequencing (scRNA-seq) and bioinformatics studies accelerated the discovery of gene expression changes in smaller cell populations, which, e.g., led to the identification of marked PRSS23 expression in a myofibroblast-like subpopulation in localized scleroderma. This review compiles major and significant research results that have contributed to our current knowledge of PRSS23 and briefly discusses where prospective studies could add to our understanding of this versatile serine protease.

A new series of 4-substituted oxycoumarin scaffolds was designed, synthesized, and evaluated for antiviral activity against both SARS-CoV-2 and HSV-2 viruses. Results indicated that compounds 3a, 4a, 4d, and 6d were found to be the most active members against SARS-CoV-2 with IC50 values of 11.17-16.65 μg/mL, with respect to acyclovir (IC50 15.94 μg/mL). On the other hand, compounds 3a, 4a, 6b, 6c, and 6d had the best antiviral activity against HSV-2, with IC50 ranging from 20.41 to 23.55 μg/mL in comparison to acyclovir (IC50 13.07 μg/mL) as a reference drug. A dual mechanistic study for active compounds against SARS-CoV-2 was performed against both 3CL protease and RNA polymerase while the DNA binding mechanism for HSV-2 was tested. Compounds 3a and 4a exhibited excellent inhibitory activity against the 3CL protease enzyme with IC50s of 2.061 and 1.356 μg/mL, respectively, against tipranavir (IC50 7.057 μg/mL). In addition, compound 4a exhibited a good RNA-dependent RNA polymerase inhibitory activity, showing IC50 1.072 μg/mL against remdesivir (IC50 0.541 μg/mL). HSV-2 inhibition activity was mechanistically studied through DNA binding, where it was found that compounds 6c and 6d showed good DNA binding affinity with IC50 of 36.18 and 42.7 μg/mL, respectively, against doxorubicin (IC50 31.54 μg/mL). Molecular docking studies were performed on SARS 3CL protease, RNA polymerase enzymes, and HSV-2 double-stranded DNA. Docking results exhibited excellent agreement with the obtained biological results. Physicochemical parameters and pharmacokinetic profile studies for the most active candidates, which were obtained from software calculations, proved credible drug-likeness that might act as good orally active antiviral scaffolds.

A phytochemical investigation of the aerial parts of Marrubium alysson L. yielded 10 compounds: β-sitosterol (1), glycerol monopalmitate (2), β-sitosterol glucoside (3), chrysoeriol (4), apigenin (5), (apigenin-7-O-(3'',6''-E-p-dicoumaroyl)-β-d-glucoside) (6), apigenin-7-O-(3''-E-p-coumaroyl)-β-d-glucopyranoside (7), apigenin-7-O-(6''-E-p-coumaroyl)-β-d-glucoside (8), apigenin-7-O-β-glucopyranoside (9) and verbascoside (10). Their structures were established using 1D and 2D NMR spectroscopic techniques. Compounds 1, 2, 6, 7 and 8 are reported from M. alysson L. for the first time in this study. The in vitro inhibitory activities against the SARS-CoV-2 main protease (Mpro) were evaluated using fluorogenic substrate assay. Compound 6 showed the highest inhibitory activity against the SARS-CoV-2 main protease (Mpro) with IC50 = 8.349 ± 0.35 μM, comparing favourably with the reference tipranavir (IC50 = 3.231 ± 0.14 μM). The antioxidant activities were determined using in vitro ABTS radical scavenging assay; it is noteworthy that compounds 6, 7 and 8 have potent antioxidant activity compared with l-ascorbic acid, while compound 10 has radical scavenging activity with IC50 = 25.58 ± 0.12 μM, more potent than the reference l-ascorbic acid (IC50 = 30.43 ± 0.14 μM). Molecular modelling studies of compound 6 showed that it is perfectly engaged in a wide range of hydrogen bonding with multiple residues, including Met49, Glu47, Thr24, Thr26, Gly143, and Gln 189 in the active site of CoV-2-3CL protease. This is reflected by its promising binding affinity, which explains the observed biochemical activity of compound 6 for inhibiting SARS-CoV-2 main protease (Mpro). Assessments of the pharmacokinetics, drug likeness and medicinal chemistry friendliness of the isolated compounds were also conducted.

The Nipah virus (NiV) is an emerging zoonotic pathogen that causes severe febrile encephalitis, transmitted from infected animals to humans. Since its initial outbreak in Malaysia, subsequent epidemics have occurred across Asia, including India, with mortality rates ranging from 40 to 75%. There are no approved vaccines, or antiviral treatments currently exist for NiV infections. In this study, molecular docking was conducted using 42 FDA-approved drugs targeting the Nipah virus glycoprotein-human receptor complex. Binding affinities and 2D interaction profiles were analyzed, revealing five promising candidates: Saquinavir, Nelfinavir, Simeprevir, Paritaprevir, and Tipranavir. These compounds exhibited strong binding affinities, ranging from - 9.8 to -11.1 kcal/mol. These five top potential drugs were subjected to molecular dynamics (MD) simulations for 200 ns to further assess their stability, flexibility and compactness. MM/GBSA analysis was employed to estimate their binding free energies. The MD simulations confirmed their favourable binding properties, demonstrating significant stability and minimal fluctuation during the stability. Subsequently, drug-likeness evaluations were performed to assess key pharmacokinetic parameters, including absorption, distribution, metabolism, excretion, and toxicity (ADMET), with an emphasis on toxicity prediction and drug-like properties. The results revealed stable interactions with minimal structural fluctuations, supporting their potential as repurposed therapeutics for Nipah virus infection. To evaluate their efficacy and contribute to the development of effective antiviral treatments against NiV, further in vivo testing in animal models and human trials is recommended.

The current study aims at developing non-peptidic new antiviral hits against main protease (M[pro]) of SARS-COV2 using the non-peptidic M[pro] inhibitor tipranavir (TPV) as a starting point. In vitro protease inhibition assay of the targeted compounds indicated that compound 6f and its cyclized triazole analogue 7f were the most active in the present study with IC50 values of 6.48 and 7.38 μM, respectively. These values were better than the 9.06 μM IC50 value of reference standard; TPV. In general, acylthiosemicarbazide derivatives 6e-g were more potent than corresponding acylsemicarbazide derivatives 6a-c. Also, the 4-chlorophenyl combined with either thiosemicabazide or 5-mercaptotriazolyl moieties in the molecules were the best for protease inhibitory activity. Cytotoxicity testing assay suggested that the tested molecules were relatively safe for the normal human lung fibroblast cell line WI-38 with IC50 values that ranged from 48.75 to 399.96 μM. Results of the molecular modeling study were consistent with those of in vitro biological evaluation. Collectively, compounds 6f and 7f could be considered as non-peptidic new antiviral hits with protease inhibitory activity for further modifications and development to potent antiviral agents as protease inhibitors.

The clinical management of cervical cancer remains constrained by limited therapeutic options and a paucity of targeted pharmacological interventions. Drug repurposing emerges as a promising strategy to expedite oncological therapeutics development. This study systematically investigates the antineoplastic potential of HIV protease inhibitors saquinavir (SQV) and tipranavir (TPV) through multimodal mechanistic validation. In vitro analyses demonstrated dose-dependent inhibition of cervical cancer cell proliferation accompanied by significant upregulation of senescence-associated β-galactosidase (SA-β-Gal) activity. Molecular characterization revealed concomitant activation of senescence-regulatory proteins p53, p21, and p16, suggesting induction of tumor-suppressive senescence pathways. Transcriptomic profiling of inhibitor-treated SiHa cells identified critical cell cycle regulators CDK1 and CDK6, findings corroborated by molecular docking simulations revealing high-affinity binding to cyclin-dependent kinases (-32.0607 to -47.6820 kJ/mol). In vivo validation using xenograft models demonstrated comparable tumor growth inhibition to doxorubicin with preserved host viability and negligible systemic toxicity. Mechanistic integration revealed dual pathway modulation: G1-phase cell cycle arrest mediated through CDK1/6 suppression and coordinated activation of the p53/p21/p16 senescence signaling axis. These findings establish SQV and TPV as multi-targeted senotherapeutic agents, providing preclinical rationale for repurposing HIV antivirals as novel therapeutic strategy against cervical malignancies.

Background/Objectives: The molecular heterogeneity and metabolic flexibility of Hepatocellular Carcinoma (HCC) pose significant challenges to the efficacy of systemic therapy for advanced cases. Early screening difficulties often delay diagnosis, leading to more advanced stages at presentation. Combined with the inconsistent responses to current systemic therapies, HCC continues to have one of the highest mortality rates among cancers. Thus, this paper seeks to contribute to the development of systemic therapy options through the consideration of HCC's metabolic vulnerabilities and lay the groundwork for future in vitro studies. Methods: Transcriptomic data were used to calculate single and double knockout options for HCC using genetic Minimal Cut Sets. Furthermore, using QSAR modeling, drug repositioning opportunities were assessed to inhibit the selected genes. Results: Two single knockout options that were also annotated as essential pairs were found within the pyrimidine metabolism pathway of HCC, wherein the knockout of either DHODH or TYMS is potentially disruptive to proliferation. The result of the flux balance analysis and gene knockout simulation indicated a significant decrease in biomass production. Three machine learning algorithms were assessed for their performance in predicting the pIC50 of a given compound for the selected genes. SVM-rbf performed the best on unseen data achieving an R[2] of 0.82 for DHODH and 0.81 for TYMS. For DHODH, the drugs Oteseconazole, Tipranavir, and Lusutrombopag were identified as potential inhibitors. For TYMS, the drugs Tadalafil, Dabigatran, Baloxavir Marboxil, and Candesartan Cilexetil showed promise as inhibitors. Conclusions: Overall, this study suggests in vitro testing of the identified drugs to assess their capabilities in inducing pyrimidine starvation on HCC.

An efficient and highly enantioselective synthesis of tipranavir is realized based on an iridium-catalyzed asymmetric allylic substitution. High yield and diastereoselectivity (>20:1), as well as excellent enantioselectivity (99% ee), were obtained for the key intermediate through direct asymmetric alkylation reaction of dihydropyranone with allylic tert-butyl carbonate. Anti-AIDS drug of tipranavir was finally accomplished in 8 steps and 6 pots starting from commercially available 1-phenyl-3-hexanone in 20.7% overall yield with 99% ee and >20:1 dr.

The presence of pretreatment drug resistance (PDR) is posing an increasing threat to HIV control. Here we investigated drug resistance mutations (DRMs) and PDR among 6831 HIV-infected individuals from 2018 to 2022 in Guangzhou, China. DRMs were detected among 24.5% of the patients. The overall prevalence of PDR was 7.4%, with resistance rate to nucleotide reverse transcriptase inhibitor (NRTI) being 1.3%, nonnucleoside reverse transcriptase inhibitor (NNRTI) 4.8%, and protease inhibitor (PI) 1.4%. Abacavir (0.8%) resistance was the most common in NRTI, followed by resistance to emtricitabine (0.6%), lamivudine (0.6%), and tenofovir disoproxil fumarate (0.3%). In NNRTI, nevirapine (3.7%) resistance was the most common, followed by efavirenz (3.5%) and rilpivirine (3.4%). Among PI, resistance to tipranavir (0.8%), nelfinavir (0.6%), fosamprenavir (0.2%) and lopinavir (0.1%) was most frequent. Annual prevalence of PDR showed an increase trend from 2018 to 2022, although not significant. In the multivariable logistic regression model, hepatitis B surface antigen positivity, circulating recombinant form (CRF) 55_01B, CRF08_BC, CRF59_01B, and subtype B were demonstrated as associated risk factors for PDR. The overall prevalence of PDR in Guangzhou was moderate, with relatively severe NNRTI resistance. Therefore, it remains crucial to continue monitoring PDR among newly diagnosed HIV-infected individuals.

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 (R[2] varied from 0.828 to 0.909) protease inhibitors, while R[2] for predicting tipranavir fold ratio was lower (R[2] 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.