Biomed Pharmacother. 2025 May 3;187:118124. doi: 10.1016/j.biopha.2025.118124. Online ahead of print.

ABSTRACT

Chronic kidney disease (CKD) is characterized by kidney fibrosis involving epithelial-mesenchymal transition (EMT), and extracellular matrix (ECM) accumulation, and often leads to end-stage kidney disease (ESKD). Currently, available therapies are not uniformly effective and lead to serious adverse effects. Levosimendan (LVS), a calcium sensitizer and an inodilator, manages cardiac failure. We aimed to evaluate the renoprotective effect of LVS on unilateral ureteral obstruction (UUO)-induced CKD in male Sprague-Dawley (SD) rats and exogenous transforming growth factor-β1 (TGF-β1)-induced fibrosis in NRK-52E cells. Rats were randomly grouped as normal control (NC), sham, UUO and UUO + LVS (3 mg/kg, p.o., o.d.) for 21 days. All animals were sacrificed post-treatment, and plasma, urine and kidney specimens were utilized for biochemistry, histology, immunohistochemistry and immunoblotting. Moreover, exogenous TGF-β1 was used to stimulate kidney fibrosis in NRK-52E cells and treated with LVS (10 µM) for 48 h. The in-vitro samples were collected for cell morphology, viability, immunofluorescence and immunoblotting. LVS treatment significantly improved the kidney mass, plasma and urine creatinine, BUN, urine urea nitrogen and plasma proteins levels of TGF-β1 and fibronectin. Histology revealed a significant decrease in tubular necrosis, glomerulosclerosis and tubulointerstitial fibrosis in LVS-treated rats. Moreover, LVS treatment remarkably downregulated the levels of α-SMA, vimentin, p-Smad 2/3 and upregulated E-cadherin in UUO rats, decreased Smad 4, collagen I, β-catenin, and MMP-7-mediated ECM and increased Smurf 2 and Smad 7 in NRK-52E cells. LVS inhibits EMT and ECM turnover via TGF-β1/Smad axis modulation, highlighting the potential clinical use of LVS for CKD.

PMID:40319657 | DOI:10.1016/j.biopha.2025.118124

Angew Chem Int Ed Engl. 2025 May 3:e202425206. doi: 10.1002/anie.202425206. Online ahead of print.

ABSTRACT

New compounds targeting human malaria parasites are critical for effective malaria control and elimination. Here, we pursued the imidazoquinolinone AZD0156 (MMV1580483), a human ataxia-telangiectasia mutated (ATM) kinase inhibitor that completed Phase I clinical trials as an anticancer agent. We validated its in vitro activity against the two main forms of the Plasmodium falciparum parasite in the human host, viz. the asexual blood (symptomatic) stage and sexual gametocyte (transmission) stage. Resistance selection, cross-resistance, biochemical and conditional knockdown studies revealed that AZD0156 inhibits P. falciparum phosphatidylinositol 4-kinase type III beta (PfPI4Kβ), a clinically-validated target for the treatment of malaria. Metabolic perturbations, fixed-ratio isobolograms, killing kinetics and morphological evaluation correlated AZD0156 inhibition with other known PI4Kβ inhibitors. The compound showed favourable in vivo pharmacokinetic properties and 81% antimalarial efficacy (4 x 50 mg/kg) in a P. berghei mouse malaria infection model. Importantly, a cleaner biochemical profile was measured against human kinases (MAP4K4, MINK1) implicated in embryofoetal developmental toxicity associated with the PfPI4Kβ inhibitor MMV390048. This improved kinase selectivity profile and structural differentiation from other PI4Kβ inhibitors, together with its multistage antiplasmodial activity and favourable pharmacokinetic properties, makes AZD0156 an attractive candidate for target-based drug repositioning against malaria via a medicinal chemistry optimisation approach.

PMID:40317875 | DOI:10.1002/anie.202425206

Antiviral Res. 2025 Apr 30:106184. doi: 10.1016/j.antiviral.2025.106184. Online ahead of print.

ABSTRACT

Helicases have emerged as promising targets in antiviral drug development but remain largely undrugged. To support the focused development of viral helicase inhibitors we identified, collected, and integrated all chemogenomics data for all helicases annotated in the ChEMBL database. After thoroughly curating and enriching the data with accurate annotations we have created a derivative database of helicase inhibitors which we dubbed Heli-SMACC (Helicase-targeting SMAll Molecule Compound Collection). Heli-SMACC contains 13,597 molecules, 29 proteins, and 20,431 bioactivity entries for viral, human, and bacterial helicases. We selected 30 compounds with promising viral helicase activity and tested them in a SARS-CoV-2 NSP13 ATPase assay. Twelve compounds demonstrated ATPase inhibition and a consistent dose-response curve. While Heli-SMACC provides a rich resource for identifying candidate inhibitors, cross-species compound transferability remains a significant challenge. In particular, inhibitory activity observed against viral helicases often does not translate well to human or bacterial homologs and vice versa due to differences in binding site composition, helicase structure, and cofactor dependencies. Despite these limitations, Heli-SMACC offers a valuable starting point for structure-based optimization and target-specific inhibitor design. The Heli-SMACC database may serve as a reference for virologists and medicinal chemists working on the development of novel helicase inhibitors. Heli-SMACC is publicly available at https://smacc.mml.unc.edu.

PMID:40316178 | DOI:10.1016/j.antiviral.2025.106184

Brief Bioinform. 2025 May 1;26(3):bbaf163. doi: 10.1093/bib/bbaf163.

ABSTRACT

Host-directed antivirals offer a promising strategy for addressing the challenge of viral resistance. Virus-host interactions often trigger stage-specific metabolic reprogramming in the host, and the causal links between these interactions and virus-induced metabolic changes provide valuable insights for identifying host targets. In this study, we present a workflow for repurposing host-directed antivirals using virus-induced protein networks. These networks capture the dynamic progression of viral infection by integrating host proteins directly interacting with the virus and enzymes associated with significantly altered metabolic fluxes, identified through dual-species genome-scale metabolic models. This approach reveals numerous hub nodes as potential host targets. As a case study, 50 approved drugs with potential anti-influenza virus A (IVA) activity were identified through eight stage-specific IVA-induced protein networks, each comprising 699-899 hub nodes. Lisinopril, saxagliptin, and gliclazide were further validated for anti-IVA efficacy in vitro through assays measuring the inhibition of cytopathic effects and viral titers in A549 cells infected with IVA PR8. This workflow paves the way for the rapid repurposing of host-directed antivirals.

PMID:40315435 | DOI:10.1093/bib/bbaf163

Cornea. 2025 May 2. doi: 10.1097/ICO.0000000000003877. Online ahead of print.

NO ABSTRACT

PMID:40315261 | DOI:10.1097/ICO.0000000000003877

Front Bioinform. 2025 Apr 17;5:1522401. doi: 10.3389/fbinf.2025.1522401. eCollection 2025.

ABSTRACT

The incidence of non-alcoholic fatty liver disease (NAFLD), encompassing the more severe non-alcoholic steatohepatitis (NASH), is rising alongside the surges in diabetes and obesity. Increasing evidence indicates that NASH is responsible for a significant share of idiopathic hepatocellular carcinoma (HCC) cases, a fatal cancer with a 5-year survival rate below 22%. Biomarkers can facilitate early screening and monitoring of at-risk NAFLD/NASH patients and assist in identifying potential drug candidates for treatment. This study utilized an ensemble feature selection framework to analyze transcriptomic data, identifying biomarker genes associated with the stage-wise progression of NAFLD-related HCC. Seven machine learning algorithms were assessed for disease stage classification. Twelve feature selection methods including correlation-based techniques, mutual information-based methods, and embedded techniques were utilized to rank the top genes as features, through this approach, multiple feature selection methods were combined to yield more robust features important in this disease progression. Cox regression-based survival analysis was carried out to evaluate the biomarker potentiality of these genes. Furthermore, multiphase drug repurposing strategy and molecular docking were employed to identify potential drug candidates against these biomarkers. Among the seven machine learning models initially evaluated, DISCR resulted as the most accurate disease stage classifier. Ensemble feature selection identified ten top genes, among which eight were recognized as potential biomarkers based on survival analysis. These include genes ABAT, ABCB11, MBTPS1, and ZFP1 mostly involved in alanine and glutamate metabolism, butanoate metabolism, and ER protein processing. Through drug repurposing, 81 candidate drugs were found to be effective against these markers genes, with Diosmin, Esculin, Lapatinib, and Phenelzine as the best candidates screened through molecular docking and MMGBSA. The consensus derived from multiple methods enhances the accuracy of identifying relevant robust biomarkers for NAFLD-associated HCC. The use of these biomarkers in a multiphase drug repurposing strategy highlights potential therapeutic options for early intervention, which is essential to stop disease progression and improve outcomes.

PMID:40313868 | PMC:PMC12043677 | DOI:10.3389/fbinf.2025.1522401

Int J Neuropsychopharmacol. 2025 May 2:pyaf029. doi: 10.1093/ijnp/pyaf029. Online ahead of print.

ABSTRACT

BACKGROUND: Vortioxetine is a serotonin reuptake inhibitor and serotonin receptor modulator used for the treatment of major depressive disorder, but recent studies have also reported anticancer effects in models of glioblastoma. Given the well-established benefits of drug repositioning, we examined the pharmacological mechanism for these anticancer actions using bioinformatics and molecular docking.

METHODS: Putative molecular targets for vortioxetine were identified by searching DrugBank, GeneCards, SwissTargetPrediction, CTD, and SuperPred databases, while glioblastoma-related proteins were identified using GeneCards, OMIM, and TTD. A protein-protein interaction (PPI) network was constructed from vortioxetine targets also involved in glioblastoma to identify core (hub) targets, which were then characterized by GO and KEGG pathway enrichment analyses using DAVID. Cytoscape was utilized to generate a drug-pathway-target-disease network, and molecular docking simulations were performed to evaluate direct interactions between vortioxetine and core target proteins.

RESULTS: A total of 234 unique vortioxetine protein targets were identified. Among 234 vortioxetine targets identified, 48 were also related to glioblastoma. Topological analysis of the PPI network revealed five core targets: the serine/threonine kinase AKT1, transcription factor hypoxia-inducible factor (HIF)-1, cell adhesion molecule cadherin-E, NF-κB subunit p105, and prostaglandin-endoperoxide synthase 2. According to GO and KEGG pathway analyses, the anticancer efficacy of vortioxetine may be mediated by effects on glucose metabolism, cell migration, phosphorylation, inflammatory responses, apoptosis, and signaling via Rap1, chemical carcinogenesis-reactive oxygen species, and HIF-1. Molecular docking revealed moderately strong affinities between vortioxetine and four core targets.

CONCLUSIONS: This study suggests that vortioxetine may inhibit glioblastoma development through direct effects on multiple targets, and further emphasizes the value of bioinformatics analyses for drug repositioning.

PMID:40312983 | DOI:10.1093/ijnp/pyaf029

Prog Neuropsychopharmacol Biol Psychiatry. 2025 Apr 29:111386. doi: 10.1016/j.pnpbp.2025.111386. Online ahead of print.

ABSTRACT

The development of new drugs is a complex, expensive, and time-consuming process, often fraught with a high likelihood of failure. Amid these challenges, drug repurposing, which identifies new therapeutic applications for already existing medications, offers a more economical and time-saving approach, particularly in the challenging field of neurological and psychiatric disorders. This narrative review explores both preclinical and clinical studies to examine the potential of anesthetics such as ketamine, nitrous oxide, isoflurane, sevoflurane, propofol, dexmedetomidine, and sodium oxybate in treating central nervous system disorders. Various research highlights the potential of anesthetics to provide rapid antidepressant effects, enhance learning and memory, improve synaptic plasticity, and offer neuroprotective benefits, demonstrating promise for treating depression, post-traumatic stress disorder, cognitive decline, traumatic brain injury, and neurodegenerative disorders. Anesthetics appear to alleviate symptoms in neurological conditions, likely by modulating GABAergic and glutamatergic pathways. However, challenges such as dose-dependent neurotoxicity, variability in preclinical and clinical outcomes, as well as environmental concerns remain significant issues. Future research is essential to optimize dosing strategies, ensure long-term safety, and gain a deeper understanding of the precise mechanisms of action. The concept of anesthetics' repurposing presents a unique solution to tackle the challenges in neurological and psychiatric therapy by providing a platform for the development of new and improved therapies.

PMID:40311741 | DOI:10.1016/j.pnpbp.2025.111386

J Neuroimmune Pharmacol. 2025 May 1;20(1):49. doi: 10.1007/s11481-025-10205-6.

ABSTRACT

Current medications for seizure symptoms can reduce seizure severity but do not stop or slow their progression. These drugs often have unpleasant side effects and may not work for all patients. The search for new therapeutic targets for seizure progression can be expedited through drug repurposing, which leverages existing approved medications, ultimately reducing clinical trial costs. This study investigates the neuroprotective properties of pomalidomide, an immunomodulatory drug, in a male rat model of pentylenetetrazol-induced seizures. Pomalidomide pretreatment significantly decreased the frequency and severity of seizures and delayed their onset. It elevated glutathione peroxidase (GPX) and superoxide dismutase (SOD) levels while lowering malondialdehyde (MDA), showcasing its antioxidant effects. Furthermore, it activated the Nrf2/HO-1 signaling pathway by increasing gene expression in the hippocampus, providing neuroprotection in the CA1 and CA3 regions. These findings suggest that pomalidomide may enhance the antioxidant defense system, support the Nrf2/HO-1 pathway, and protect the hippocampus, indicating its potential for treating patients with seizures, particularly intractable ones.

PMID:40310605 | DOI:10.1007/s11481-025-10205-6

Clin Pharmacol Ther. 2025 May 1. doi: 10.1002/cpt.3682. Online ahead of print.

ABSTRACT

Although attractive for relevance to real-world scenarios, real-world data (RWD) is typically used for drug repurposing and not therapeutic target discovery. Repurposing studies have identified few effective options in neurological diseases such as the rare disease, amyotrophic lateral sclerosis (ALS), which has no disease-modifying treatments available. We previously reclassified drugs by their simulated effects on proteins downstream of drug targets and observed class-level effects in the EHR, implicating the downstream protein as the source of the effect. Here, we developed a novel ALS-focused network medicine model using data from patient samples, the public domain, and consortia. With this model, we simulated drug effects on ALS and measured class effects on overall survival in retrospective EHR studies. We observed an increased but non-significant risk of death for patients taking drugs with complement system proteins downstream of their targets and experimentally validated drug effects on complement activation. We repeated this for six protein classes, three of which, including multiple chemokine receptors, were associated with a significantly increased risk for death, suggesting that targeting proteins such as CXCR5, CXCR3, chemokine signaling generally, or neuropeptide Y (NPY) could be advantageous therapeutic targets for these patients. We expanded our analysis to the neuroinflammatory condition, myasthenia gravis, and neurodegenerative disease, Parkinson's, and recovered similar effect sizes. We demonstrated the utility of network medicine for testing novel therapeutic effects using RWD and believe this approach may accelerate target discovery in neurological diseases, addressing the critical need for new therapeutic options.

PMID:40310263 | DOI:10.1002/cpt.3682

Nucleic Acids Res. 2025 May 1:gkaf373. doi: 10.1093/nar/gkaf373. Online ahead of print.

ABSTRACT

As part of the Library of Integrated Network-Based Cellular Signatures (LINCS) NIH initiative, 248 human cell lines were profiled with the L1000 assay to measure the effect of 33 621 small molecules and 7508 single-gene CRISPR knockouts. From this massive dataset, we computed 1.678 million sets of up- and down-regulated genes. These gene sets are served for search by the LINCS L1000 Signature Search (L2S2) web server application. With L2S2, users can identify small molecules and single gene CRISPR KOs that produce gene expression profiles similar or opposite to their submitted single or up/down gene sets. L2S2 also includes a consensus search feature that ranks perturbations across all cellular contexts, time points, and concentrations. To demonstrate the utility of L2S2, we crossed the L2S2 gene sets with gene sets collected for the RummaGEO resource. The analysis identified clusters of differentially expressed genes that match drug classes, tissues, and diseases, pointing to many opportunities for drug repurposing and drug discovery. Overall, the L2S2 web server application can be used to further the development of personalized therapeutics while expanding our understanding of complex human diseases. The L2S2 web server application is available at https://l2s2.maayanlab.cloud.

PMID:40308216 | DOI:10.1093/nar/gkaf373

BMC Bioinformatics. 2025 Apr 30;26(1):117. doi: 10.1186/s12859-025-06132-1.

ABSTRACT

Accelerating drug discovery for glucocorticoid receptor (GR)-related disorders, including innovative machine learning (ML)-based approaches, holds promise in advancing therapeutic development, optimizing treatment efficacy, and mitigating adverse effects. While experimental methods can accurately identify GR antagonists, they are often not cost-effective for large-scale drug discovery. Thus, computational approaches leveraging SMILES information for precise in silico identification of GR antagonists are crucial, enabling efficient and scalable drug discovery. Here, we develop a new ensemble learning approach using a multi-step stacking strategy (M3S), termed M3S-GRPred, aimed at rapidly and accurately discovering novel GR antagonists. To the best of our knowledge, M3S-GRPred is the first SMILES-based predictor designed to identify GR antagonists without the use of 3D structural information. In M3S-GRPred, we first constructed different balanced subsets using an under-sampling approach. Using these balanced subsets, we explored and evaluated heterogeneous base-classifiers trained with a variety of SMILES-based feature descriptors coupled with popular ML algorithms. Finally, M3S-GRPred was constructed by integrating probabilistic feature from the selected base-classifiers derived from a two-step feature selection technique. Our comparative experiments demonstrate that M3S-GRPred can precisely identify GR antagonists and effectively address the imbalanced dataset. Compared to traditional ML classifiers, M3S-GRPred attained superior performance in terms of both the training and independent test datasets. Additionally, M3S-GRPred was applied to identify potential GR antagonists among FDA-approved drugs confirmed through molecular docking, followed by detailed MD simulation studies for drug repurposing in Cushing's syndrome. We anticipate that M3S-GRPred will serve as an efficient screening tool for discovering novel GR antagonists from vast libraries of unknown compounds in a cost-effective manner.

PMID:40307679 | DOI:10.1186/s12859-025-06132-1

IUBMB Life. 2025 May;77(5):e70020. doi: 10.1002/iub.70020.

ABSTRACT

Chemotherapeutic treatments for breast cancer are often associated with severe toxicity due to the requirement of high concentrations of the drugs for efficacy. The combination of chemotherapy drugs along with repurposed drugs offers a promising strategy to enhance efficacy while reducing toxicity. However, the effectiveness of such combinations is likely to be hindered by improper metabolism of the drugs due to the sharing of the same metabolizing enzymes. In this study, we explored a novel approach to enhance the efficacy of Pimozide (repurposed drug) by combining it with chemotherapeutic drugs that utilize different metabolizing enzymes than Pimozide, thereby reducing metabolic load and toxicity. The Epirubicin-SAHA(Vorinostat)-Pimozide (ESP) combination emerged as highly synergistic, reducing the IC50 of Pimozide from 16.54 to 0.57 μM in MCF-7 cells and from 17.5 to 3.35 μM in MDA-MB-231 cells, representing a significant enhancement in efficacy. Mechanistic studies revealed increased intracellular reactive oxygen species (ROS) generation and activation of the intrinsic apoptosis pathway, as indicated by a 10-fold increase in the cleaved PARP levels. In MDA-MB-231 cells, there was also a 2-fold increase in p53 and a 10-fold increase in p21 expression, with a concomitant reduction in AKT signaling. Furthermore, the ESP combination reduced cancer stemness, invasiveness, fatty acid uptake, and lipid droplet accumulation, pointing to its broad impact on cancer cell survival and metabolism. These findings suggest that the ESP combination holds promise as an effective therapeutic strategy for breast cancer, with reduced toxicity and enhanced efficacy.

PMID:40305333 | DOI:10.1002/iub.70020

Biomolecules. 2025 Apr 11;15(4):565. doi: 10.3390/biom15040565.

ABSTRACT

Beta-hemoglobinopathies such as beta-thalassemia and sickle cell disease are severe genetic blood disorders affecting the beta globin chain of haemoglobin A (α2β2). Activation of delta globin, the non-alpha globin of HbA2 (α2δ2), could represent a possible approach to improve the clinical severity of these pathologies. Notably, the therapeutic potential of delta globin has been demonstrated in previous studies using a mouse model of beta-thalassemia and sickle cell disease. The present study evaluated delta globin gene activation by small molecules in erythroid cells isolated from transgenic murine foetal liver. A screening of 119 molecules, selected for their potential in drug repurposing, was performed without prior selection based on specific pathways of interest. Three candidates-Nexturastat, Stattic and Palbociclib-were found to have high efficacy on delta globin expression. Palbociclib also proved effective in increasing gamma globin expression. All of these compounds have pharmacokinetic profiles that are beneficial for clinical application, providing potential inducer agents of HbA2 that could have therapeutic effects in the treatment of beta-hemoglobinopathies.

PMID:40305292 | DOI:10.3390/biom15040565

Cell Biochem Biophys. 2025 Apr 30. doi: 10.1007/s12013-025-01762-x. Online ahead of print.

ABSTRACT

Acute Respiratory Distress Syndrome (ARDS) is a severe lung disease with a high fatality rate and few treatment options. Targeting certain signalling pathways, notably the Transforming Growth Factor-beta (TGF-beta) signalling pathway, has emerged as a promising option for ARDS therapy. We identified TGF-beta Receptor 1 (TGFBR1) as a major target for ARDS treatment using the STRING and KEGG databases and validated TGFBR1's critical function in the TGF-beta signalling pathway, which is important in ARDS pathogenesis. To find prospective TGFBR1 inhibitors, we selected two FDA-approved medicines, Galunisertib and Vactosertib, which are established pharmacological profiles in cancer and fibrotic illnesses. Furthermore, the SwissSimilarity platform's ligand-based virtual screening revealed structurally related drugs in the DrugBank and ChEMBL databases. Among these, seven candidates were selected for further consideration. Molecular docking experiments found that DB08387 and CHEMBL14297639 had the strongest affinity for TGFBR1, creating strong hydrogen bonds at key sites. These findings point to their potential as TGFBR1 inhibitors in ARDS treatment. The pharmacokinetic screening revealed that most of the chosen compounds had favourable ADME features, with CHEMBL14297639 standing out for its low gastrointestinal absorption and limited cytochrome P450 inhibition. This study demonstrates the possibility of targeting TGFBR1 with Galunisertib, Vactosertib, and other prospective ARDS treatments. The findings lay the groundwork for additional experimental validation and the development of innovative therapeutics aimed at reducing ARDS severity.

PMID:40304856 | DOI:10.1007/s12013-025-01762-x

Clin Transl Sci. 2025 May;18(5):e70237. doi: 10.1111/cts.70237.

ABSTRACT

Clinical trials with investigator sponsors at academic sites have increased, in part due to studies involving drug repurposing, the process of identifying new uses for existing drugs that are initially conducted in patients rather than healthy participants. In contrast to industry- or government-sponsored trials, investigator-sponsored clinical studies, also known as investigator-initiated trials, are typically conducted at one or several academic centers and are resource-limited by finances and patient numbers. These studies can serve as crucial pilot studies to inform the design of larger, more definitive clinical trials. Drawing from the experience of working with clinical researchers in academic settings, this tutorial presents guidelines for writing clinical protocols for resource-limited investigator-sponsored studies that meet international standards and optimize the detection of meaningful signals or outcomes that can lead to investigation in larger well-controlled trials.

PMID:40304394 | DOI:10.1111/cts.70237

Front Pharmacol. 2025 Apr 15;16:1546836. doi: 10.3389/fphar.2025.1546836. eCollection 2025.

ABSTRACT

Vitiligo is a chronic autoimmune condition characterized by the destruction of melanocytes, leading to patchy loss of skin depigmentation. Although its precise cause remains unclear, recent evidence suggests that metabolic disturbances, particularly oxidative stress and mitochondrial dysfunction, may play a significant role in the pathogenesis of the disease. Oxidative stress is thought to damage melanocytes and trigger inflammatory responses, culminating in melanocyte immune-mediate destruction. Additionally, patients with vitiligo often exhibit extra-cutaneous metabolic abnormalities such as abnormal glucose metabolism, dyslipidemia, high fasting plasma glucose levels, high blood pressure, out of range C-peptide and low biological antioxidant capacity, suggesting a potential link between metabolic impairment and vitiligo development. This implies that the loss of functional melanocytes mirrors a more general systemic targetable dysfunction. Notably, therapies targeting metabolic pathways, particularly those involving mitochondrial metabolism, such as the peroxisome proliferator-activated nuclear receptor γ (PPARγ) agonists, are currently being investigated as potential treatments for vitiligo. PPARγ activation restores mitochondrial membrane potential, mitochondrial DNA copy number and, consequently, ATP production. Moreover, PPARγ agonists counteract oxidative stress, reduce inflammation, inhibit apoptosis, and maintain fatty acid metabolism, in addition to the well-known capability to enhance insulin sensitivity. Additionally, increasing evidence of a strong relationship between metabolic alterations and vitiligo pathogenesis suggests a role for other approved anti-diabetic treatments, like metformin and fibrates, in vitiligo treatment. Taken together, these data support the use of approaches alternative to traditional immune-suppressive treatments for the treatment of vitiligo.

PMID:40303919 | PMC:PMC12037623 | DOI:10.3389/fphar.2025.1546836

J Neuroinflammation. 2025 Apr 29;22(1):125. doi: 10.1186/s12974-025-03455-x.

ABSTRACT

BACKGROUND: Epalrestat (EPS), an aldose reductase inhibitor, is used to alleviate peripheral nerve disorder of diabetic patients in clinical therapy. Even though EPS exerted effects in central nervous system diseases, the neuroprotection and underlying molecular mechanism in neurodegenerative diseases, especially Parkinson's disease (PD), remains obscure. Our study aimed to investigate the potential of EPS suppressed PD progression both in vivo and in vitro.

METHODS: We used 1-methyl-4-phenylpyridillium ion (MPP+)-treated PD cells and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated PD mice to investigate the protective function and molecular mechanism of EPS in PD. EPS was administered three times daily through oral route 3 days before model establishment for 5 consecutive days. Behavioral manifestation of mice was conducted using open field test, rotarod test and CatWalk gait analysis. Immunofluorescence was used to detect dopaminergic (DAergic) neurons survival in the substantia nigra. Subsequently, oxidative stress, mitochondrial function and KEAP1/Nrf2 signaling pathway in PD models were detected through molecular biology methods to assess the effect and downstream mechanisms of EPS on PD. Molecular docking, surface plasmon resonance and cellular thermal shift assay were used to verify the direct binding of EPS and KEAP1.

RESULTS: We found that EPS exhibited potent antiparkinsonian activity in PD models both in vivo and in vitro. PD models treated with EPS manifested alleviated oxidative stress and mitochondrial dysfunction. Furthermore, we found EPS activated the Nrf2 signaling pathway which contributed to DAergic neurons survival in PD models. Particularly, we firstly confirmed that EPS competitively binds to KEAP1 and enhanced its degradation, thereby activating the Nrf2 signaling pathway.

CONCLUSIONS: Collectively, EPS attenuates oxidative stress and mitochondrial dysfunction by directly binding KEAP1 to activate the KEAP1/Nrf2 signaling pathway, further reducing DAergic neurons damage. These findings suggest that EPS has great potential to become a therapeutic for PD as a clinically effective and safe medicine.

PMID:40301912 | DOI:10.1186/s12974-025-03455-x

Biomed Pharmacother. 2025 Apr 28;187:118104. doi: 10.1016/j.biopha.2025.118104. Online ahead of print.

ABSTRACT

Dengue virus (DENV) threatens global health; specific antiviral drugs are required to combat it. Such anti-DENV therapeutics can be rapidly developed by repositioning the drugs approved for other indications. This study investigated six medications of different classes drawn from a library of molecules. In silico analyses were performed to determine potential binding affinity for the DENV non-structural protein NS3 protease and NS5 RNA-dependent RNA polymerase (RdRp). Of the six candidates, galidesivir and tadalafil showed the highest binding affinities for the DENV NS3 protease and NS5 RdRp, with tadalafil demonstrating the highest binding affinity. Galidesivir and tadalafil substantially suppressed viral replication in DENV replicon cells without inducing cytotoxicity and showed half-maximal inhibitory concentrations of 10 μM and 2.56 μM, respectively. Both galidesivir and tadalafil effectively suppress DENV infection in human hepatoma and baby hamster kidney cells, and tadalafil demonstrates protease-inhibitory activity. In an AG129 mouse model of DENV infection, both galidesivir and tadalafil reduced viral loads in the serum, with tadalafil producing a notable reduction by day four. Both drugs markedly suppressed DENV replication in the hepatic tissue. Histopathologically, both galidesivir- and tadalafil-treated mice showed alleviation of DENV-induced lesions in the spleen and liver, indicating the potential therapeutic effects of these drugs. These findings highlight the potential of repositioning galidesivir and tadalafil as effective anti-DENV therapies with low cytotoxicity, meeting the urgent global need for new therapeutic agents against this pathogen.

PMID:40300391 | DOI:10.1016/j.biopha.2025.118104

IEEE J Biomed Health Inform. 2025 Apr 29;PP. doi: 10.1109/JBHI.2025.3565721. Online ahead of print.

ABSTRACT

As an effective and low-risk approach to identify new therapeutic pathways for existing drugs, drug repositioning has been extensively utilized to expedit drug discovery processes. However, current knowledge graph (KG)-based methodologies encounter several hurdles in this context. Firstly, most graph neural network (GNN)- based approaches fail to adequately capture the intricate relationships between drug-drug, drug-disease, or diseasedisease. Secondly, the subtle synergistic mechanisms between drugs and diseases remain underexplored. Lastly, the training of knowledge graph embedding (KGE) methods is susceptible to noise, leading to unstable model optimization. To address these challenges, we intruduce KRANE, a knowledge-driven and relation-aware synergistic learning method for drug repositioning. KRANE addresses these issues through three innovative modules. Firstly, we design a relation-aware feature extractor (RAFE), which utilizes the contextual triples attention scores in KG to effectively integrate drug-related knowledge and enhance the representation of complex relational features. Secondly, we adopt a synergistic feature reconstruction module as a decoder to extract synergistic heterogeneous feature interactions between drugs and diseases from entity and relation representations. Finally, we propose a knowledgeregulated loss function to mitigate the impact of noise on model training. Experiments conducted on three publicly available datasets demonstrate that KRANE significantly outperforms existing methods. The source code and datasets are available at https://github.com/qifen37/KRANE.

PMID:40299742 | DOI:10.1109/JBHI.2025.3565721