Bioinformatics. 2025 Mar 17:btaf117. doi: 10.1093/bioinformatics/btaf117. Online ahead of print.

ABSTRACT

MOTIVATION: Identifying drug target interactions is a crucial step in drug repurposing and drug discovery. The significant increase in demand and the expensive nature for experimentally identifying drug target interactions necessitate computational tools for automated prediction and comprehension of drug target interactions. Despite recent advancements, current methods fail to fully leverage the hierarchical information in drug target interactions.

RESULTS: Here we introduce H2GnnDTI, a novel two-level hierarchical heterogeneous graph learning model to predict drug target interactions, by integrating the structures of drugs and proteins via a low-level view GNN (LGNN) and a high-level view GNN (HGNN). The hierarchical graph consists of high-level heterogeneous nodes representing drugs and proteins, connected by edges representing known DTIs. Each drug or protein node is further detailed in a low-level graph, where nodes represent molecules within each drug or amino acids within each protein, accompanied by their respective chemical descriptors. Two distinct low-level graph neural networks are first deployed to capture structural and chemical features specific to drugs and proteins from these low-level graphs. Subsequently, a high-level graph encoder is employed to comprehensively capture and merge interactive features pertaining to drugs and proteins from the high-level graph. The high-level encoder incorporates a structure and attribute information fusion module designed to explicitly integrate representations acquired from both a feature encoder and a graph encoder, facilitating consensus representation learning. Extensive experiments conducted on three benchmark datasets have shown that our proposed H2GnnDTI model consistently outperforms state-of-the-art deep learning methods.

AVAILABILITY AND IMPLEMENTATION: The codes are freely available at https://github.com/LiminLi-xjtu/H2GnnDTI.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:40097269 | DOI:10.1093/bioinformatics/btaf117

Brain Res. 2025 Mar 15:149571. doi: 10.1016/j.brainres.2025.149571. Online ahead of print.

ABSTRACT

Dravet Syndrome is a severe childhood drug-resistant epilepsy. The predominant etiology of this condition is related to de novo mutations within the SCN1A gene, which codes for the alpha subunit of the NaV1.1 sodium channels. This dysfunction leads to hypoexcitability of GABAergic interneurons. In turn, the loss of electrical excitability in GABAergic interneurons leads to an imbalance of excitation over inhibition in many neural circuits. Notably, exacerbation of symptoms is observed when non-selective sodium channel blockers are administered to patients with Dravet. Recent studies in animal models of Dravet have highlighted the potential of highly specific sodium channel blockers capable of blocking other sodium channel subtypes without inhibiting NaV1.1 current and selective activators of NaV1.1 as viable therapeutic strategies for alleviating Dravet Syndrome symptoms. Here, we describe the development and validation of ligand-based machine learning models to identify ligands with inhibitory effects on sodium channel isoforms NaV1.1 and NaV1.2. These models were built based on in-house open-source routines and Mordred molecular descriptors. First, linear classifiers were inferred using a combination of feature-bagging and Forward Stepwise selection. Secondly, ensemble learning was applied to build meta-classifiers with improved predictive ability, whose performance was tested in retrospective screening experiments. After in silico validation, the models were applied to screen for drug repurposing opportunities in the DrugBank and Drug Repurposing Hub databases, to identify selective blocking agents of NaV1.2 devoid of NaV1.1 blocking activity as potential compounds for the treatment of Dravet Syndrome. Forty in silico hits were later identified in a prospective screening experiment. Four of them were acquired and submitted to experimental confirmation via patch clamp: three of these candidates, Eltrombopag, Sufugolix, and Glesatinib, showed blocking effects on NaV1.2 currents, although no subtype selectivity was observed. The different predictive abilities of the NaV1.1 and NaV1.2 models may be attributed to the different sizes of the datasets used to train and validate the respective models.

PMID:40096941 | DOI:10.1016/j.brainres.2025.149571

Biophys Chem. 2025 Mar 10;322:107434. doi: 10.1016/j.bpc.2025.107434. Online ahead of print.

ABSTRACT

Emergence of viruses cause unprecedented challenges and thus leading to wide-ranging consequences today. The world has faced massive disruptions like COVID-19 and continues to suffer in terms of public health and world economy. Fighting with this emergence of viruses and its reemergence plays a critical role in the health care industry. Identification of novel virus-drug associations is a vital step in drug discovery. Prediction and prioritization of novel virus-drug associations through computational approaches is an alternative and best choice considering the cost and risk of biological experiments. This study proposes a method, KR-AEVDA that relies on k-nearest neighbor based reliable negative sample selection and autoencoder based feature extraction to explore promising virus-drug associations for further experimental validation. The method analyzes complex relationships among drugs and viruses by investigating similarity and association data between drugs and viruses. It generates feature vectors from the similarity data, and reliable negative samples are extracted through an effective distance-based algorithm from the unlabeled samples in the dataset. Then high level features are extracted via an autoencoder and is fed to an ensemble classifier for inferring novel associations. Experimental results on three different datasets showed that KR-AEVDA reliably attained better performance than other state-of-the-art methods. Molecular docking is carried out between the top-predicted drugs and the crystal structure of the SARS-CoV-2's main protease to further validate the predictions. Case studies for SARS-CoV-2 illustrate the effectiveness of KR-AEVDA in identifying potential virus-drug associations.

PMID:40096790 | DOI:10.1016/j.bpc.2025.107434

Front Pharmacol. 2025 Feb 28;16:1449062. doi: 10.3389/fphar.2025.1449062. eCollection 2025.

ABSTRACT

BACKGROUND: Anti-hypertensive drugs have been reported to demonstrate anti-inflammatory and anti-angiogenic effects. This study aims to investigate the association between anti-hypertensive drugs and the prognosis of colorectal cancer (CRC) patients.

METHODS: Clinical data of 1134 CRC patients with hypertensions and the prescription of anti-hypertensive drugs who had undergone curative surgery in our hospital between 2005 and 2015 were retrieved. Their survival data and immune cell population in circulatory blood were compared among different types of anti-hypertensive drugs and overall CRC patients.

RESULTS: The 5-year overall survival for the antihypertensives-treated patients (65.2%) was higher than the CRC patients in Hong Kong (58.2%). Hydrochlorothiazide (HCTZ) group showed the best prognosis (79.1%) among different antihypertensive drug, particularly for advance stage or elderly patients, which are poor prognostic factors for overall CRC patients, demonstrated an obviously improved prognosis upon HCTZ treatment. Moreover, our data showed the recurrence rate was significantly lower for HCTZ group (18.3%) compared to non-HCTZ group (26.8%) and the reported rate (31%) of CRC patients in Hong Kong. Finally, patients with a lower pre-operative basophil level showed better overall and disease-free survival following HCTZ treatment.

CONCLUSION: This study demonstrated the association of HCTZ treatment with a better prognosis of CRC patients.

PMID:40093321 | PMC:PMC11906466 | DOI:10.3389/fphar.2025.1449062

medRxiv [Preprint]. 2025 Mar 4:2025.02.28.25323099. doi: 10.1101/2025.02.28.25323099.

ABSTRACT

Psychiatric disorders and symptoms are associated with differences in pain perception and sensitivity. These differences can have important implications in treating spinal degenerative disease (SDD) and chronic low-back pain (CLBP). Leveraging data from the UK Biobank (UKB) and the All of Us Research Program (AoU), we investigated the effects linking psychiatric disorders (alcohol use disorder, anxiety, attention deficit hyperactivity disorder, bipolar disorder, cannabis use disorder, depression, opioid use disorder, posttraumatic stress disorder, and schizophrenia) to SDD and CLBP. We applied multi-nominal regression models, polygenic risk scoring (PRS), and one-sample Mendelian randomization (MR) to triangulate the effects underlying the associations observed. We also performed gene ontology and drug-repurposing analyses to dissect the biology shared among mental illnesses, SDD, and CLBP. Comparing individuals affected only by SDD (UKB N=37,745, AoU N=3,477), those affected only by CLBP (UKB N=15,496, AoU N=23,325), and those affected by both conditions (UKB N=11,463, AoU N= 13,451) to controls (UKB N=337,362, AoU N= 117,162), observational and genetically informed analyses highlighted that the strongest effects across the three case groups were observed for alcohol use disorder, anxiety, depression, and posttraumatic stress disorder. Additionally, schizophrenia and its PRS appeared to have an inverse relationship with CLBP, SDD, and their comorbidity. One-sample MR highlighted a potential direct effect of internalizing disorders on the outcomes investigated that was particularly strong on SDD. Our drug-repurposing analyses identified histone deacetylase inhibitors as targeting molecular pathways shared among psychiatric disorders, SDD, and CLBP. In conclusion, these findings support that the comorbidity among psychiatric disorders, SDD, and CLBP is due to the contribution of direct effects and shared biology linking these health outcomes. These pleiotropic mechanisms together with sociocultural factors play a key role in shaping the SDD-CLBP comorbidity patterns observed across the psychopathology spectrum.

PMID:40093242 | PMC:PMC11908311 | DOI:10.1101/2025.02.28.25323099

Expert Opin Pharmacother. 2025 Mar 17. doi: 10.1080/14656566.2025.2480764. Online ahead of print.

ABSTRACT

INTRODUCTION: Pulmonary hypertension is a life-threatening condition characterized by elevated mean pulmonary arterial pressure and vascular resistance. Significant advances in diagnosis and treatment have been achieved over the 20th and 21st centuries, yet challenges remain in improving long-term outcomes.

AREAS COVERED: This review discusses the historical milestones in understanding and pharmacotherapy of the pulmonary arterial hypertension (PAH). A comprehensive literature search was conducted to explore the earliest reports of each approved medication for pulmonary hypertension, along with historical papers detailing the pathophysiological and diagnostic development. Additionally, the search aimed to identify novel therapeutic strategies, including repositioned drugs and emerging targets.

EXPERT OPINION: While current therapies, such as prostacyclin analogs and PDE5 inhibitors, improve functional capacity and hemodynamics, they face limitations, including costs, administration, and a predominantly vasodilatory approach. Additionally, the limitations of current clinical trial designs for rare diseases like pulmonary arterial hypertension hinder the evaluation of potentially effective drugs. These challenges underscore the urgent need for translational research to optimize trial methodologies, accelerating the development of new therapies. Innovative approaches, such as drug repositioning and the exploration of novel molecular targets, are critical to overcoming these barriers and ensuring timely, effective, and affordable treatment options for patients with PAH.

PMID:40091694 | DOI:10.1080/14656566.2025.2480764

Microbiol Spectr. 2025 Mar 17:e0331824. doi: 10.1128/spectrum.03318-24. Online ahead of print.

ABSTRACT

Fungal pathogens pose a serious threat to human health, with Candida and Aspergillus spp. representing some of the most significant opportunistic invaders. Aspergillus fumigatus causes aspergillosis, one of the most prevalent fungal diseases of humans. There is a limited number of drugs available to combat these infections, and antifungal drug resistance is on the rise. In this manuscript, we show 4-[4-(4-Piperidinyl) phenyl]-7-[4-(-(trifluoromethyl) phenyl]-2-naphthalenecarboxylic acid (PPTN), a highly specific antagonist of the human P2Y14 receptor, is a promising antifungal adjuvant against diverse fungal pathogens. PPTN interacts with caspofungin (CAS), ibrexafungerp, voriconazole (VOR), and amphotericin against A. fumigatus CAS- and VOR-resistant clinical isolates, and also CAS against Candida spp and Cryptococcus neoformans. The combination of PPTN and CAS increases cell death in A. fumigatus. In the model yeast Saccharomyces cerevisiae, heterozygous deletion of genes involved in chromatin remodeling results in PPTN hypersensitivity, and in A. fumigatus, PPTN can have increased fungicidal activity when combined with the histone deacetylase inhibitor trichostatin A and the DNA methyltransferase inhibitor 5-azacytidine. Finally, PPTN has reduced toxicity to human immortalized cell lineages and partially clears A. fumigatus conidia infection in A549 pulmonary epithelial cells. Our results indicate that PPTN is a novel adjuvant antifungal drug against fungal diseases caused by A. fumigatus and Candida spp.

IMPORTANCE: Invasive fungal infections have a high mortality rate, causing more deaths annually than tuberculosis or malaria. Aspergillus fumigatus is the main etiological agent of aspergillosis, one of the most prevalent and deadly fungal diseases. There are few therapeutic options for treating this disease, and treatment commonly fails due to host complications or the emergence of antifungal resistance. Drug repurposing, where existing drugs are deployed for other clinical indications, has increasingly been used in the process of drug discovery. Here, we show that 4-[4-(4-Piperidinyl) phenyl]-7-[4-(-(trifluoromethyl) phenyl]-2-naphthalenecarboxylic acid (PPTN), a highly specific antagonist of the human P2Y14 receptor, when combined with caspofungin (CAS), ibrexafungerp, voriconazole (VOR), and amphotericin can increase the fungicidal activity against not only A. fumigatus CAS- and VOR-resistant clinical isolates but also CAS against Candida spp.

PMID:40090930 | DOI:10.1128/spectrum.03318-24

J Mol Biol. 2025 Mar 13:169089. doi: 10.1016/j.jmb.2025.169089. Online ahead of print.

ABSTRACT

Dr. Donita C. Brady is the Harrison McCrea Dickson, MD, and Clifford C. Baker, MD Presidential Associate Professor of Cancer Biology at the University of Pennsylvania Perelman School of Medicine. She earned her BS in Chemistry from Radford University and her PhD in Pharmacology from UNC-Chapel Hill before completing postdoctoral training at Duke University with Dr. Christopher Counter. At Penn, Dr. Brady leads a research program pioneeringmetalloallostery, where redox-active metals regulate kinase activity. Her lab investigates the intersection of kinase signaling and copper (Cu) homeostasis, identifying Cu-dependent kinases and developing targeted therapies through drug repurposing and novel drug design. Her work has advanced our understanding of metals in nutrient signaling, energy homeostasis, and cancer metabolism. Dr. Brady has received numerous honors, including being a Pew Biomedical Scholar, a V Foundation Scholar, and the recipient of the Perelman School of Medicine's Michael S. Brown New Investigator Research Award. A dedicated advocate for diversity, equity, inclusion, and accessibility (DEIA), she has spent the past decade addressing barriers to representation in STEM. In 2021, she was appointed the inaugural Assistant Dean for Inclusion, Diversity, and Equity (IDE) in Research Training at Penn, leading efforts to foster an inclusive research environment. For these contributions, she received the 2022 Vanderbilt Basic Science Juneteenth Icon Award and the Penn Biomedical Graduate Studies Cell and Molecular Biology Graduate Group Community Service Award.

PMID:40089146 | DOI:10.1016/j.jmb.2025.169089

Drug Discov Today. 2025 Mar 13:104331. doi: 10.1016/j.drudis.2025.104331. Online ahead of print.

ABSTRACT

Ovarian cancer (OC) has poor survival statistics and increasing prevalence. One of the new options for its therapy could be overcoming platinum resistance. In this review, we have considered the idea of repositioning angiotensin-converting enzyme inhibitors (ACE-Is) as chemosensitizers. These drugs have been shown to suppress angiogenesis and OC cell migration in preclinical studies. Moreover, clinical data have shown that using ACE-Is with standard chemotherapy prolongs patient survival. Based on this rationale, we discuss the available in vitro models of OC for future studies with ACE-Is and demonstrate an in silico approach that has enabled us to select the most promising molecules: perindopril, ramipril, trandolapril and their diketopiperazine derivatives.

PMID:40089017 | DOI:10.1016/j.drudis.2025.104331

Comput Biol Med. 2025 Mar 14;189:109984. doi: 10.1016/j.compbiomed.2025.109984. Online ahead of print.

ABSTRACT

The deployment of artificial intelligence (AI) is revolutionizing neuropharmacology and drug development, allowing the modulation of neurotransmitter systems at the personal level. This review focuses on the neuropharmacology and regulation of neurotransmitters using predictive modeling, closed-loop neuromodulation, and precision drug design. The fusion of AI with applications such as machine learning, deep-learning, and even computational modeling allows for the real-time tracking and enhancement of biological processes within the body. An exemplary application of AI is the use of DeepMind's AlphaFold to design new GABA reuptake inhibitors for epilepsy and anxiety. Likewise, Benevolent AI and IBM Watson have fast-tracked drug repositioning for neurodegenerative conditions. Furthermore, we identified new serotonin reuptake inhibitors for depression through AI screening. In addition, the application of Deep Brain Stimulation (DBS) settings using AI for patients with Parkinson's disease and for patients with major depressive disorder (MDD) using reinforcement learning-based transcranial magnetic stimulation (TMS) leads to better treatment. This review highlights other challenges including algorithm bias, ethical concerns, and limited clinical validation. Their proposal to incorporate AI with optogenetics, CRISPR, neuroprosthesis, and other advanced technologies fosters further exploration and refinement of precision neurotherapeutic approaches. By bridging computational neuroscience with clinical applications, AI has the potential to revolutionize neuropharmacology and improve patient-specific treatment strategies. We addressed critical challenges, such as algorithmic bias and ethical concerns, by proposing bias auditing, diverse datasets, explainable AI, and regulatory frameworks as practical solutions to ensure equitable and transparent AI applications in neurotransmitter modulation.

PMID:40088712 | DOI:10.1016/j.compbiomed.2025.109984

Mol Divers. 2025 Mar 14. doi: 10.1007/s11030-025-11162-1. Online ahead of print.

ABSTRACT

Telomerase, a reverse transcriptase implicated in replicative immortality of cancers, remains a challenging target for therapeutic intervention due to its structural complexity and the absence of clinically approved small-molecule inhibitors. In this study, we explored drug repurposing as a pragmatic approach to address this gap, leveraging FDA-approved drugs to accelerate the identification of potential telomerase inhibitors. Using a structure-based drug discovery framework, we screened the DrugBank database through a previously validated pharmacophore model for the FVYL pocket in the hTERT thumb domain, the established binding site of BIBR1532. This was followed by molecular docking, pharmacokinetic filtering, and molecular dynamics (MD) simulations to evaluate the stability of protein-ligand complexes. Binding free energy calculations (MM-PBSA and MM-GBSA) were employed for cross-validation, identifying five promising candidates. Experimental validation using the Telomerase Repeat Amplification Protocol (TRAP) assay confirmed the inhibitory potential of Raltitrexed, showing significant inhibition with IC50 8.899 µM in comparison to control. Decomposition analysis and Structure-Activity Relationship (SAR) studies further offered insights into the binding mechanism, reinforcing the utility of the FVYL pocket as a druggable site. Raltitrexed's dual mechanism of action, targeting both telomerase and thymidylate synthase, underscores its potential as a versatile anticancer agent, suitable for combination therapies or standalone treatment. As the top lead, Raltitrexed demonstrates the potential of repurposed drugs in telomerase-targeted therapies, offering a time and cost-effective strategy for advancing its clinical development. The study also provides a robust framework for future drug development, addressing challenges in targeting telomerase for anticancer therapy.

PMID:40087255 | DOI:10.1007/s11030-025-11162-1

Mol Genet Metab. 2025 Mar 1;144(4):109073. doi: 10.1016/j.ymgme.2025.109073. Online ahead of print.

ABSTRACT

Rare diseases affect over 400 million people worldwide, with approved treatment available for less than 6 % of these diseases. Drug repurposing is a key strategy in the development of therapies for rare disease patients with large unmet medical needs. The process of repurposing drugs compared to novel drug development is a time-saving and cost-efficient method potentially resulting in higher success rates. To accelerate and ensure sustainability in therapy development for rare neurometabolic, neurological, and neuromuscular diseases, an international consortium SIMilarities in clinical and molecular PATHology (SIMPATHIC) has been established where we move away from the one drug one disease concept and move towards one drug targeting a pathomechanism shared between diseases, by applying parallel preclinical and clinical drug development. Here the consortium describes accelerators of drug repurposing pursued by the consortium, including 1) co-creation, 2) patient empowerment, 3) use of standardized induced pluripotent stem cell (iPSC)-derived disease models and cellular and molecular profiling, 4) high-throughput drug screening in neurons, 5) innovative clinical trial design, and 6) selection of appropriate exploitation and patient access models. In this way, a fast and effective drug repurposing pathway for several rare diseases will be established to reduce time from discovery to patient access.

PMID:40086177 | DOI:10.1016/j.ymgme.2025.109073

Drug Discov Today. 2025 Mar 11:104327. doi: 10.1016/j.drudis.2025.104327. Online ahead of print.

ABSTRACT

Rheumatoid arthritis (RA) presents a significant challenge in clinical management because of the dearth of effective drugs despite advances in understanding its mechanisms. Drug repurposing has emerged as a promising strategy to address this gap, offering potential cost savings and expediting drug discovery. Notably, computational methods, particularly machine learning (ML), have shown promise in RA drug repurposing. In this review, we survey various drug-repurposing approaches, both classical and contemporary, highlighting the pivotal role of ML. We summarize RA candidate drugs identified through computational strategies and discuss prevailing challenges in this domain. Leveraging ML, alongside a deepening understanding of RA mechanisms, holds promise for enhancing pharmacological treatment options for patients with RA.

PMID:40081521 | DOI:10.1016/j.drudis.2025.104327

Int J Mol Sci. 2025 Feb 28;26(5):2195. doi: 10.3390/ijms26052195.

ABSTRACT

Sphingolipidoses, a subgroup of lysosomal storage diseases (LSDs), are rare and debilitating disorders caused by defects in sphingolipid metabolism. Despite advancements in treatment, therapeutic options remain limited. Miglustat, a glucosylceramide synthase EC 2.4.1.80 (GCS) inhibitor, is one of the few available pharmacological treatments; however, it is associated with significant adverse effects that impact patients' quality of life. Drug repurposing offers a promising strategy to identify new therapeutic agents from approved drugs, expanding treatment options for rare diseases with limited therapeutic alternatives. This study aims to identify potential alternative inhibitors of GCS through a drug-repurposing approach, using computational and experimental methods to assess their therapeutic potential for sphingolipidoses. A library of approved drugs was screened using advanced computational techniques, including molecular docking, molecular dynamics simulations, and metadynamics, to identify potential GCS inhibitors. Promising candidates were selected for further in vitro validation to evaluate their inhibitory activity and potential as therapeutic alternatives to Miglustat. Computational screening identified several potential GCS inhibitors, with Dapagliflozin emerging as the most promising candidate. Experimental validation confirmed its efficacy, revealing a complementary mechanism of action to Miglustat while potentially offering a more favorable side effect profile. This study underscores the utility of computational and experimental methodologies in drug repurposing for rare diseases. The identification of Dapagliflozin as a potential GCS inhibitor provides a foundation for further preclinical and clinical evaluation, supporting its potential application in the treatment of sphingolipidoses.

PMID:40076817 | DOI:10.3390/ijms26052195

Int J Mol Sci. 2025 Feb 23;26(5):1910. doi: 10.3390/ijms26051910.

ABSTRACT

Reductive stress (RS), characterized by excessive accumulation of reducing equivalents such as NADH and NADPH, is emerging as a key factor in metabolic disorders and cancer. While oxidative stress (OS) has been widely studied, RS and its complex interplay with endocrine regulation remain less understood. This review explores molecular circuits of bidirectional crosstalk between metabolic hormones and RS, focusing on their role in diabetes, obesity, cardiovascular diseases, and cancer. RS disrupts insulin secretion and signaling, exacerbates metabolic inflammation, and contributes to adipose tissue dysfunction, ultimately promoting insulin resistance. In cardiovascular diseases, RS alters vascular smooth muscle cell function and myocardial metabolism, influencing ischemia-reperfusion injury outcomes. In cancer, RS plays a dual role: it enhances tumor survival by buffering OS and promoting metabolic reprogramming, yet excessive RS can trigger proteotoxicity and mitochondrial dysfunction, leading to apoptosis. Recent studies have identified RS-targeting strategies, including redox-modulating therapies, nanomedicine, and drug repurposing, offering potential for novel treatments. However, challenges remain, particularly in distinguishing physiological RS from pathological conditions and in overcoming therapy-induced resistance. Future research should focus on developing selective RS biomarkers, optimizing therapeutic interventions, and exploring the role of RS in immune and endocrine regulation.

PMID:40076537 | DOI:10.3390/ijms26051910

Molecules. 2025 Feb 24;30(5):1031. doi: 10.3390/molecules30051031.

ABSTRACT

Our research group aimed for the optimization of pharmacologic ascorbate (Ph-Asc)-induced cancer cell death. To reduce the required time and resources needed for development, an in silico system biological approach, an already approved medication, and a mild bioactive compound were used in our previous studies. It was revealed that both Ph-Asc and resveratrol (RES) caused DSBs in the DNA, and chloroquine (CQ) treatment amplified the cytotoxic effect of both Ph-Asc and RES in an autophagy independent way. In the present study, we aimed at the further clarification of the cytotoxic mechanism of Ph-Asc, CQ, and RES by comparing their DNA damaging abilities, effects on the cells' bioenergetic status, ROS, and lipid ROS generation abilities with those of the three currently investigated compounds (menadione, RSL3, H2O2). It could be assessed that the induction of DSBs is certainly a common point of their mechanism of action; furthermore, the observed cancer cell death due to the investigated treatments are independent of the bioenergetic status. Contrary to other investigated compounds, the DNA damaging effect of CQ seemed to be ROS independent. Surprisingly, the well-known ferroptosis inducer RSL3 was unable to induce lipid peroxidation in the pancreas ductal adenocarcinoma (PDAC) Mia PaCa-2 cell line. At the same time, it induced DSBs in the DNA, and the RSL3-induced cell death could not be suspended by the well-known ferroptosis inhibitors. All these observations suggest the ferroptosis resistance of this cell line. The observed DNA damaging effect of RSL3 definitely creates a new perspective in anticancer research.

PMID:40076255 | DOI:10.3390/molecules30051031

Cancers (Basel). 2025 Mar 6;17(5):903. doi: 10.3390/cancers17050903.

ABSTRACT

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 R2 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.

PMID:40075750 | DOI:10.3390/cancers17050903

Purinergic Signal. 2025 Mar 13. doi: 10.1007/s11302-025-10078-7. Online ahead of print.

ABSTRACT

Neuroblastoma is a pediatric tumor accounting for approximately 8% of childhood cancers and is associated with high mortality rates among children aged 1 to 5 years. Standard treatments often fall short, leading to recurrence and metastasis due to the development of chemoresistance. A promising approach to address this challenge involves targeting purinergic signaling pathways and drug repurposing. The combination of flubendazole in nanoformulation and vincristine exhibited synergistic effects in ACN cells, enhancing treatment efficacy. Vincristine combined with the P2X7 receptor antagonist Brilliant Blue-G showed antagonistic effects, and interactions between nanoFBZ and Brilliant Blue-G were dose-dependent. Furthermore, ACN cells exposed to 213 nM of vincristine weekly for three weeks resulted in vincristine-resistant cells with significantly higher resistance (IC50 approximately 300 times greater) compared to parental cells. P2Y2 receptor expression was augmented in vincristine-resistant cells, particularly after treatment with nanoFBZ and Brilliant Blue-G, while adenosine A1, A2B, and P2Y6 receptor expression levels decreased. P2X7 receptor expression was also reduced in vincristine-resistant cells treated with nanoFBZ. P2X7 receptor agonism and P2Y2 receptor blockade slightly elevated resistance. In conclusion, this study suggests that combining nanoFBZ with vincristine chemotherapy may offer a promising strategy for improving the treatment efficacy of neuroblastoma. The synergy between nanoFBZ and vincristine enhanced therapeutic outcomes, and P2X7 receptor antagonism further reduced neuroblastoma cell viability.

PMID:40075009 | DOI:10.1007/s11302-025-10078-7

Sci Rep. 2025 Mar 12;15(1):8518. doi: 10.1038/s41598-024-83633-8.

ABSTRACT

Although the SARS-CoV-2 epidemic worldwide has gradually decreased, in some areas, the situation has not yet been stamped and has become a global health emergency. It is quite possible that we could again be threatened by a new coronavirus. Therefore, new nucleotide analog drugs and vaccines or using drug repositioning for SARS-CoV-2 still has been developed, yet their safety and efficacy against COVID-19 remains underexplored. Malabaricone C is 2,6-dihydroxyphenyl acylphenol found in edible plants such as the mace spice of nutmeg derived from the seeds of Myristica fragrans. In this study, we identified malabaricone C as the first inhibitor of SARS-CoV-2 from natural food with a safe alternative for drugs. Malabaricone C and its chemical derivatives showed EC50 values of 1-1.5 μM against SARS-CoV-2 (WK-521, ancestral strain) and its variant strains in mammalian cells (HEK293T and Vero E6). In addition, we have successfully established novel evaluation system for the inhibition of SARS virus cell fusion by visualization for providing a versatile tool for study SARS-CoV-2 mediated fusion. Furthermore, our experiments suggested that malabaricone C could affect the distribution of sphingomyelin on the plasma membrane, which involves in viral infections. Thus, in light of the beneficial effect of malabaricone C on viral infection, the nontoxic malabaricone C is a suitable candidate as a drug that can be employed in the treatment and prevention of COVID-19. Moreover, it may potentially be used to treat acute infections of other enveloped viruses.

PMID:40074774 | DOI:10.1038/s41598-024-83633-8

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2024 Oct 28;49(10):1601-1610. doi: 10.11817/j.issn.1672-7347.2024.240109.

ABSTRACT

OBJECTIVES: Staphylococcus epidermidis (S. epidermidis) adheres to the surface of medical devices, forming highly drug-resistant biofilms, which has made the development of novel antibacterial agents against S. epidermidis and its biofilms a key research focus. By drug repurposing, this study aims to explore the combinational antimicrobial effects between pinaverium bromide (PVB), a L-type calcium channel blocker, and oxacillin (OXA) against S. epidermidis.

METHODS: Clinical isolates of S. epidermidis were collected from January to September 2022 at the Department of Clinical Laboratory of the Third Xiangya Hospital, Central South University. The minimal inhibitory concentrations (MICs) of PVB and OXA were determined using the broth microdilution method. Checkerboard assays and time-kill curves were performed to assess the fractional inhibitory concentration index and synergistic bactericidal efficiency of the drug combination. Resistance selection assays evaluated PVB's ability to inhibit the development of OXA resistance. Biofilm eradication assays, combined with confocal laser scanning microscopy (CLSM) and the persister cell quantification, were conducted to evaluate the effect of PVB and OXA on drug-resistant biofilms and persister cells. The mechanisms of PVB action were further investigated using transmission electronic microscopy (TEM), reactive oxygen species (ROS) quantification, and ATP quantification.

RESULTS: The MICs of PVB and OXA against the standard strain S. epidermidis RP62A were both 8 μg/mL. Checkerboard assays showed that the fractional inhibitory concentration index (FICI) for the combination was 0.250 0 for RP62A and ranged from 0.187 5 to 0.500 0 for clinical isolates, indicating synergistic effects. Resistance selection assays demonstrated that PVB not only failed to induce resistance but also effectively inhibited the development of OXA resistance. The combination of 1×MIC of PVB and OXA reduced biofilm biomass (A570 nm) from (2.36±0.46) to (1.12±0.39) (t=3.504, P=0.02). CLSM revealed significant biofilm structural disruption and an increased proportion of dead bacteria. Additionally, after 4 hours of treatment, the total persister cell count was reduced from lg(7.73±0.21) to lg(2.79±0.43) (t=4.143, P=0.014). Synergistic biofilm eradication was further confirmed in clinical isolates. TEM revealed that PVB caused significant bacterial structural damage. The combination of OXA and PVB significantly induced ROS production, increasing the relative fluorescence intensity from (30 000.00±2 000.00) to (45 666.67±2 081.67) (t=10.68, P<0.001), and markedly reduced ATP generation, lowering the relative fluorescence intensity form (565.00±33.18) to (205.67±35.23) (t=4.932, P=0.003).

CONCLUSIONS: The combination of PVB and OXA exhibits significant synergistic antimicrobial activity against S. epidermidis, its biofilms, and persister cells. This combination holds promise as a potential alternative therapy for biofilm-associated infections caused by S. epidermidis.

PMID:40074309 | DOI:10.11817/j.issn.1672-7347.2024.240109