BMJ Open. 2025 Feb 26;15(2):e091495. doi: 10.1136/bmjopen-2024-091495.

ABSTRACT

INTRODUCTION: Wolfram syndrome (WFS1-Spectrum Disorder) is an ultra-rare monogenic form of progressive neurodegeneration and diabetes mellitus. In common with most rare diseases, there are no therapies to slow or stop disease progression. Sodium valproate, an anticonvulsant with neuroprotective properties, is anticipated to mediate its effect via alteration of cell cycle kinetics, increases in p21cip1 expression levels and reduction in apoptosis and increase in Wolframin protein expression. To date, there have been no multicentre randomised controlled trials investigating the efficacy of treatments for neurodegeneration in patients with Wolfram syndrome.

METHODS AND ANALYSIS: TREATWOLFRAM is an international, multicentre, double-blind, placebo-controlled, randomised clinical trial designed to investigate whether 36-month treatment with up to 40 mg/kg/day of sodium valproate will slow the rate of loss of visual acuity as a biomarker for neurodegeneration in patients with Wolfram syndrome. Patients who satisfied the eligibility criteria were randomly assigned (2:1) to receive two times per day oral gastro-resistant sodium valproate tablets up to a maximum dose of 800 mg 12 hourly or sodium valproate-matched placebo. Using hierarchical repeated measures analyses with a 5% significance level, 80% power and accounting for an estimated 15% missing data rate, a sample size of 70 was set. The primary outcome measure, visual acuity, will be centrally reviewed and analysed on an intention-to-treat population.

ETHICS AND DISSEMINATION: The protocol was approved by the National Research Ethics Service (West of Scotland; 18/WS/0020) and by the Medicines and Healthcare products Regulatory Agency. Recruitment into TREATWOLFRAM started in January 2019 and ended in November 2021. The treatment follow-up of TREATWOLFRAM participants is ongoing and due to finish in November 2024. Updates on trial progress are disseminated via Wolfram Syndrome UK quarterly newsletters and at family conferences for patient support groups. The findings of this trial will be disseminated through peer-reviewed publications and international presentations.

TRIAL REGISTRATION NUMBER: NCT03717909.

PMID:40010822 | DOI:10.1136/bmjopen-2024-091495

Phytomedicine. 2025 Feb 14;139:156518. doi: 10.1016/j.phymed.2025.156518. Online ahead of print.

ABSTRACT

BACKGROUND: Drug discovery from nature has a long, ethnopharmacologically-based background. Today, natural resources are undeniably vital reservoirs of active molecules or drug leads. Advances in (bio)informatics and computational biology emphasized the role of herbal medicines in the drug discovery pipeline.

PURPOSE: This review summarizes bioinformatic approaches applied in recent drug discovery from nature.

STUDY DESIGN: It examines advancements in molecular networking, pathway analysis, network pharmacology within a systems biology framework and AI for assessing the therapeutic potential of herbal preparations.

METHODS: A comprehensive literature search was conducted using Pubmed, SciFinder, and Google Database. Obtained data was analyzed and organized in subsections: AI, systems biology integrative approach, network pharmacology, pathway analysis, molecular networking, structure-based virtual screening.

RESULTS: Bioinformatic approaches is now essential for high-throughput data analysis in drug target identification, mechanism-based drug discovery, drug repurposing and side-effects prediction. Large datasets obtained from "omics" approaches require bioinformatic calculations to unveil interactions, and patterns in disease-relevant conditions. These tools enable databases annotations, pattern-matching, connections discovery, molecular relationship exploration, and data visualisation.

CONCLUSION: Despite the complexity of plant metabolites, bioinformatic approaches assist in characterization of herbal preparations and selection of bioactive molecule. It is perceived as powerful tool for uncovering multi-target effects and potential molecular mechanisms of compounds. By integrating multiple networks that connect gene-disease, drug-target and gene-drug-target, drug discovery from natural sources is experiencing a remarkable comeback.

PMID:40010031 | DOI:10.1016/j.phymed.2025.156518

CNS Neurosci Ther. 2025 Feb;31(2):e70294. doi: 10.1111/cns.70294.

ABSTRACT

OBJECTIVE: To identify and validate causal protein targets that may serve as potential therapeutic interventions for both the onset and progression of Parkinson's disease (PD) through integrative proteomic and genetic analyses.

METHOD: We utilized large-scale plasma and brain protein quantitative trait loci (pQTL) datasets from the deCODE Health study and the Religious Orders Study/Rush Memory and Aging Project (ROS/MAP), respectively. Proteome-wide association studies (PWAS) were conducted using the OTTERS framework for plasma proteins and the FUSION tool for brain proteins, examining associations with PD onset and three progression phenotypes: composite, motor, and cognitive. Significant protein associations (FDR-corrected p < 0.05) from PWAS were further validated using summary-based Mendelian randomization (SMR), colocalization analyses, and reverse Mendelian randomization (MR) to establish causality. Phenome-wide Mendelian randomization (PheW-MR) was performed to assess potential side effects across 679 disease traits when targeting these proteins to reduce PD-related phenotype risk by 20%. Additionally, we conducted cellular distribution-based clustering using gene expression data from the Allen Brain Atlas (ABA) to explore the distribution of key proteins across brain regions, constructed protein-protein interaction (PPI) networks via the STRING database to explore interactions among proteins, and evaluated the druggability of identified targets using the DrugBank database to identify opportunities for drug repurposing.

RESULT: Our analyses identified 25 candidate proteins associated with PD phenotypes, including 16 plasma proteins linked to PD progression (10 cognitive, 4 motor, and 3 composite) and 9 plasma proteins associated with PD onset. Notably, GPNMB was implicated in both plasma and brain tissues for PD onset. PheW-MR revealed predominantly beneficial side effects for the identified targets, with 83.7% of associations indicating positive outcomes and 16.3% indicating adverse effects. Cellular clustering categorized candidate targets into three distinct expression profiles across brain cell types using ABA. PPI network analysis highlighted one key interaction cluster among the proteins for PD cognitive progression and PD onset. Druggability assessment revealed 15 out of 25 proteins had repurposing opportunities for PD treatment.

CONCLUSION: We have identified 25 causal protein targets associated with the onset and progression of PD, providing new insights into the research and development of treatment strategies for PD.

PMID:40008429 | DOI:10.1111/cns.70294

Front Pharmacol. 2025 Feb 11;16:1525029. doi: 10.3389/fphar.2025.1525029. eCollection 2025.

ABSTRACT

Computational drug repositioning, serving as an effective alternative to traditional drug discovery plays a key role in optimizing drug development. This approach can accelerate the development of new therapeutic options while reducing costs and mitigating risks. In this study, we propose a novel deep learning-based framework KGRDR containing multi-similarity integration and knowledge graph learning to predict potential drug-disease interactions. Specifically, a graph regularized approach is applied to integrate multiple drug and disease similarity information, which can effectively eliminate noise data and obtain integrated similarity features of drugs and diseases. Then, topological feature representations of drugs and diseases are learned from constructed biomedical knowledge graphs (KGs) which encompasses known drug-related and disease-related interactions. Next, the similarity features and topological features are fused by utilizing an attention-based feature fusion method. Finally, drug-disease associations are predicted using the graph convolutional network. Experimental results demonstrate that KGRDR achieves better performance when compared with the state-of-the-art drug-disease prediction methods. Moreover, case study results further validate the effectiveness of KGRDR in predicting novel drug-disease interactions.

PMID:40008124 | PMC:PMC11850324 | DOI:10.3389/fphar.2025.1525029

Heliyon. 2025 Feb 5;11(3):e42476. doi: 10.1016/j.heliyon.2025.e42476. eCollection 2025 Feb 15.

ABSTRACT

Predicting drug-target binding affinity via in silico methods is crucial in drug discovery. Traditional machine learning relies on manually engineered features from limited data, leading to suboptimal performance. In contrast, deep learning excels at extracting features from raw sequences but often overlooks essential biological context features, hindering effective binding prediction. Additionally, these models struggle to capture global and local feature distributions efficiently in protein sequences and drug SMILES. Previous state-of-the-art models, like transformers and graph-based approaches, face scalability and resource efficiency challenges. Transformers struggle with scalability, while graph-based methods have difficulty handling large datasets and complex molecular structures. In this paper, we introduce InceptionDTA, a novel drug-target binding affinity prediction model that leverages CharVec, an enhanced variant of Prot2Vec, to incorporate both biological context and categorical features into protein sequence encoding. InceptionDTA utilizes a multi-scale convolutional architecture based on the Inception network to capture features at various spatial resolutions, enabling the extraction of both local and global features from protein sequences and drug SMILES. We evaluate InceptionDTA across a range of benchmark datasets commonly used in drug-target binding affinity prediction. Our results demonstrate that InceptionDTA outperforms various sequence-based, transformer-based, and graph-based deep learning approaches across warm-start, refined, and cold-start splitting settings. In addition to using CharVec, which demonstrates greater accuracy in absolute predictions, InceptionDTA also includes a version that employs simple label encoding and excels in ranking and predicting relative binding affinities. This versatility highlights how InceptionDTA can effectively adapt to various predictive requirements. These results emphasize the promise of our approach in expediting drug repurposing initiatives, enabling the discovery of new drugs, and contributing to advancements in disease treatment.

PMID:40007773 | PMC:PMC11850134 | DOI:10.1016/j.heliyon.2025.e42476

Cell J. 2025 Feb 23;26(10):619-621. doi: 10.22074/cellj.2025.2037024.1635.

ABSTRACT

Endometriosis, a benign gynecological disorder affecting 10-15% of women during their reproductive years, is characterized by the growth of endometrial tissue outside the uterus. Despite its prevalence, the exact pathophysiology of this disease remains poorly understood. Current treatments, including surgery and hormonal therapies, often have limited efficacy and may be associated with significant side effects. In recent years, drug repurposing has emerged as a promising strategy for managing endometriosis. This approach capitalizes on the molecular similarities between endometriosis and certain cancers, particularly the role of proteins such as fibronectin. By targeting these shared molecular pathways, researchers are exploring the potential of repurposing existing drugs, especially anticancer agents, to treat endometriosis. This strategy promises to provide more effective and less invasive treatment options for patients with endometriosis. Preliminary studies have shown the potential of anticancer drugs in inhibiting disease progression and alleviating symptoms. However, further clinical trials are necessary to confirm these findings and establish the precise role of anticancer drugs in the management of endometriosis.

PMID:40007448 | DOI:10.22074/cellj.2025.2037024.1635

Pharmaceutics. 2025 Feb 14;17(2):255. doi: 10.3390/pharmaceutics17020255.

ABSTRACT

Background/Objectives: Drug repurposing explores new applications for approved medications, such as simvastatin (SV), a lipid-lowering drug that has shown anticancer potential but is limited by solubility and side effects. This study aims to enhance SV delivery and efficacy against lung cancer cells using bioactive lipid nanoparticles formulated with plant-derived monoterpenes as both nanostructuring agents and anticancer molecules. Methods: Lipid nanoparticles were produced by ultrasonication and characterized for morphology, size, zeta potential, and polydispersity index (PDI). Monoterpenes (linalool-LN-, limonene, 1,8-cineole) or Crodamol® were used as liquid lipids. Encapsulation efficiency (EE), release profiles, stability, biocompatibility, protein adsorption, cytotoxicity, and anticancer effects were evaluated. Results: The nanoparticles exhibited high stability, size: 94.2 ± 0.9-144.0 ± 2.6 nm, PDI < 0.3, and zeta potential: -4.5 ± 0.7 to -16.3 ± 0.8 mV. Encapsulation of SV in all formulations enhanced cytotoxicity against A549 lung cancer cells, with NLC/LN/SV showing the highest activity and being chosen for further investigation. Sustained SV release over 72 h and EE > 95% was observed for NLC/LN/SV. SAXS/WAXS analysis revealed that LN altered the crystallographic structure of nanoparticles. NLC/LN/SV demonstrated excellent biocompatibility and developed a thin serum protein corona in vitro. Cellular studies showed efficient uptake by A549 cells, G0/G1 arrest, mitochondrial hyperpolarization, reactive oxygen species production, and enhanced cell death compared to free SV. NLC/LN/SV more effectively inhibited cancer cell migration than free SV. Conclusions: NLC/LN/SV represents a promising nanocarrier for SV repurposing, combining enhanced anticancer activity, biocompatibility, and sustained stability for potential lung cancer therapy.

PMID:40006622 | DOI:10.3390/pharmaceutics17020255

Pharmaceutics. 2025 Feb 12;17(2):241. doi: 10.3390/pharmaceutics17020241.

ABSTRACT

Background/Objective: World Health Organization latest statistics state that 17% of infectious diseases are transmitted by vectors, causing more than 700,000 deaths each year. Particularly, dengue (DENV), Zika (ZIKV) and yellow fever (YFV) viral infections have generated international awareness due to their epidemic proportion and risks of international spread. In this framework, the repositioning strategy of Efavirenz (EFV) represents a key clinical feature to improve different antiviral therapies. Therefore, the development of Soluplus®-based nanomicelles (NMs) loaded with EFV (10 mg/mL) for optimized oral pharmacotherapy against ZIKV, DENV and YFV infections was investigated. Methods: EFV-NMs were obtained by an acetone diffusion technique. Micellar size and in vitro micellar interaction with mucin were assessed by dynamic light scattering. In vitro cytocompatibility was investigated in A549 and Vero cells and micellar in vitro antiviral activity against ZIKV, DENV and YFV was evaluated. In vivo oral bioavailability and histological studies were assessed in Wistar rats. Results: EFV encapsulation within Soluplus® NMs increased the drug's apparent aqueous solubility up to 4803-fold with a unimodal micellar size distribution and a micellar size of ~90 nm at 25 and 37 °C. Micellar in vitro interaction with mucin was also assessed in a pH range of 1.2-7.5 and its storage micellar physicochemical stability at 4 °C was confirmed over 2 years. In vitro cytocompatibility assays in A549 and Vero cells confirmed that EFV micellar dispersions resulted in safe nanoformulations. Interestingly, EFV-loaded NMs exhibited significantly higher in vitro antiviral activity compared with EFV solution for all the tested flaviviruses. In addition, the selectivity index (SI) values reveal that EFV-loaded NMs exhibited considerably more biological efficacy compared to EFV solution in A549 and Vero cell lines and for each viral infection (SI > 10). Further, the drug pharmacokinetics parameters were enhanced after the oral administration of EFV-loaded NMs, being biocompatible by not causing damage in the gastrointestinal segments. Conclusions: Overall, our EFV nanoformulation highlighted its potential as a novel drug delivery platform for optimized ZIKV, DENV and YFV antiviral therapy.

PMID:40006610 | DOI:10.3390/pharmaceutics17020241

Pharmaceuticals (Basel). 2025 Feb 7;18(2):224. doi: 10.3390/ph18020224.

ABSTRACT

Background/Objectives: Voglibose, an α-glucosidase inhibitor commonly prescribed to manage postprandial hyperglycemia in diabetes mellitus, demonstrates potential for repurposing as an anti-melanogenic agent. This study aims to explore the inhibitory effects of voglibose on melanogenesis and elucidate its molecular mechanisms, highlighting its possible applications in treating hyperpigmentation disorders. Methods: The anti-melanogenic effects of voglibose were investigated using B16F10 melanoma cells. Cell viability, melanin content, and tyrosinase activity were assessed following voglibose treatment. Western blot analysis was performed to examine changes in melanogenic proteins and transcription factors. The role of signaling pathways, including PKA/CREB, MAPK, PI3K/AKT, and GSK3β/β-Catenin, was analyzed. Primary human skin irritation tests were conducted to evaluate the topical safety of voglibose. Results: Voglibose significantly reduced melanin synthesis and tyrosinase activity in B16F10 cells in a dose-dependent manner. Western blot analysis revealed decreased expression of MITF, TRP-1, and TRP-2, indicating the inhibition of melanogenesis. Voglibose modulated key signaling pathways, including the suppression of PKA/CREB, MAPK, and AKT activation, while restoring GSK3β activity to inhibit β-catenin stabilization. Human skin irritation tests confirmed voglibose's safety for topical application, showing no adverse reactions at 50 and 100 μM concentrations. Conclusions: Voglibose demonstrates anti-melanogenic properties through the modulation of multiple signaling pathways and the inhibition of melanin biosynthesis. Its safety profile and efficacy suggest its potential as a repurposed drug for managing hyperpigmentation and advancing cosmeceutical applications.

PMID:40006038 | DOI:10.3390/ph18020224

Pathogens. 2025 Feb 1;14(2):127. doi: 10.3390/pathogens14020127.

ABSTRACT

Chagas disease, caused by the protozoan Trypanosoma cruzi, affects millions globally, with limited treatment options available. Current therapies, such as benznidazole and nifurtimox, present challenges, including their toxicity, side effects, and inefficacy in the chronic phase. This study explores the potential of drug repurposing as a strategy to identify new treatments for T. cruzi, focusing on compounds from the Medicines for Malaria Venture (MMV) COVID Box. An initial screening of 160 compounds identified eight with trypanocidal activity, with almitrine and bortezomib showing the highest efficacy. Both compounds demonstrated significant activity against the epimastigote and amastigote stages of the parasite and showed no cytotoxicity in murine macrophage cells. Key features of programmed cell death (PCD), such as chromatin condensation, mitochondrial membrane potential disruption, and reactive oxygen species accumulation, were observed in T. cruzi treated with these compounds. The potential to induce controlled cell death of these two compounds in T. cruzi suggests they are promising candidates for further research. This study reinforces drug repurposing as a viable approach to discovering novel treatments for neglected tropical diseases like Chagas disease.

PMID:40005505 | DOI:10.3390/pathogens14020127

Molecules. 2025 Feb 15;30(4):900. doi: 10.3390/molecules30040900.

ABSTRACT

Drug repurposing is a cost-effective and innovative strategy for identifying new therapeutic applications for existing drugs, thereby shortening development timelines and accelerating the availability of treatments. Applying this approach to the development of cosmeceutical ingredients enables the creation of functional compounds with proven safety and efficacy, adding significant value to the cosmetic industry. This study evaluated the potential of rifampicin, a drug widely used for the treatment of tuberculosis and leprosy, as a cosmeceutical agent. The anti-melanogenic effects of rifampicin were assessed in B16F10 melanoma cells, showing no cytotoxicity at concentrations up to 40 µM and a significant reduction in intracellular tyrosinase activity and melanin content. Mechanistically, rifampicin reduced the expression of melanogenic enzymes, including tyrosinase, tyrosinase-related protein (TRP)-1, and TRP-2, via a protein kinase A (PKA)-dependent pathway, leading to the suppression of microphthalmia-associated transcription factor (MITF), which is a key regulator of melanogenesis. Additionally, rifampicin inhibited the p38 signaling pathway but was independent of the PI3K/protein kinase B (Akt) pathway. Furthermore, it decreased Ser9 phosphorylation, enhancing glycogen synthase kinase-3β (GSK-3β) activity, promoted β-catenin phosphorylation, and facilitated β-catenin degradation, collectively contributing to the inhibition of melanin synthesis. To evaluate the topical applicability of rifampicin, primary human skin irritation tests were conducted, and no adverse effects were observed at concentrations of 20 µM and 40 µM. These findings demonstrate that rifampicin inhibits melanogenesis through multiple signaling pathways, including PKA, MAPKs, and GSK-3β/β-catenin. This study highlights the potential of rifampicin to be repurposed as a topical agent for managing hyperpigmentation disorders, offering valuable insights into novel therapeutic strategies for pigmentation-related conditions.

PMID:40005210 | DOI:10.3390/molecules30040900

Int J Mol Sci. 2025 Feb 14;26(4):1619. doi: 10.3390/ijms26041619.

ABSTRACT

Globally, bladder cancer is the sixth most frequently diagnosed cancer among men. Despite the increasing availability of immunomodulatory treatments for bladder cancer, the survival rates are still low, which calls for potential new drug-repurposing targets. This study aimed to investigate the effects of cromolyn, a mast cell (MC) stabilizer in allergic reactions, on a subcutaneous tumor model with a syngeneic mouse MB49 bladder cancer cell line. A concentration of 50 mg/kg of cromolyn was daily administered intraperitoneally in a 4-day therapeutic protocol to mice with established tumors and in a continuous 11-day protocol which started one day prior to the subcutaneous injection of tumor cells. Therapeutic treatment demonstrated a marked downregulation of genes related to angiogenesis and upregulation of genes related to cytotoxic T-cell and NK cell activity. Conversely, continuous cromolyn treatment suppressed genes involved in immune cell recruitment and activation, as well as apoptotic and necroptotic pathways, leading to a greater tumor burden (+142.4 mg [95CI + 28.42, +256.4], p = 0.0158). The same pro-tumorigenic effect was found in mast cell-deficient mice (KitW-sh/W-sh + 301.7 mg [95CI + 87.99, 515.4], p = 0.0079; Cpa3Cre/+ +107.2 mg [95CI - 39.37, +253.57], p = 0.1423), indicating that continuous cromolyn treatment mostly acts through the inhibition of mast cell degranulation. In summary, our results demonstrate the distinct effects of cromolyn on tumor progression, which depend on the protocol of cromolyn administration.

PMID:40004083 | DOI:10.3390/ijms26041619

Int J Pharm. 2025 Feb 23:125385. doi: 10.1016/j.ijpharm.2025.125385. Online ahead of print.

ABSTRACT

Psoriasis is a persistent inflammatory skin disorder characterized by hyper-proliferation and abnormal epidermal differentiation. Conventional treatments such as; topical therapies, phototherapy, systemic immune modulators, and biologics aim to relieve symptoms and improve patient quality of life. However, challenges like adverse effects, high costs, and individual response variability persist. Thus, the need for novel anti-psoriatic drugs has led to the exploration of drug repurposing, an approach that identifies new applications for existing drugs. This method is in its early stages but has gained popularity across both public and private sectors. Furthermore, artificial intelligence (AI) integration is revolutionizing the healthcare industry by enhancing efficiency, delivery, and personalization. Machine learning and deep learning algorithms have significantly impacted drug discovery, repurposing, and designing new molecules or drug delivery carriers. Nanotechnology, in addition to AI, plays a pivotal role in targeting repurposed drugs via the topical route with suitable nanocarriers. This method overcomes challenges associated with oral delivery, such as systemic toxicities, slow onset of action, first-pass effect, and poor bioavailability. This review addresses the practice of repurposing existing drugs for managing psoriasis, discussing the challenges of conventional therapy and how the incorporation of nanotechnology and AI can overcome these hurdles, facilitating the discovery of anti-psoriatic drugs and presenting promising strategies for novel therapeutics. Additionally, it discusses the general benefits of drug repurposing compared to de novo drug development and the potential drawbacks of drug repurposing.

PMID:39999900 | DOI:10.1016/j.ijpharm.2025.125385

Interdiscip Sci. 2025 Feb 25. doi: 10.1007/s12539-025-00692-9. Online ahead of print.

ABSTRACT

Predicting drug-target binding affinity (DTA) is an important step in the complex process of drug discovery or drug repositioning. A large number of computational methods proposed for the task of DTA prediction utilize single features of proteins to measure drug-protein or protein-protein interactions, ignoring multi-feature fusion between protein-related features (e.g., solvent accessibility, protein pockets, secondary structures, and distance maps, etc.). To address the aforementioned constraints, we propose a new network topology and multi-feature fusion based approach for DTA prediction (NTMFF-DTA), which deeply mines protein multiple types of data and propagates drug information across domains. Data in drug-target interactions are often sparse, and multi-feature fusion can enrich data information by integrating multiple features, thus overcoming the data sparsity problem to some extent. The proposed approach offers two main contributions: (1) constructing a relationship-aware GAT that selectively focuses on the connections between nodes and edges in the molecular graph to capture the more central roles of nodes and edges in DTA prediction and (2) constructing an information propagation channel between different feature domains of drug proteins to achieve the sharing of the importance weight of drug atoms and edges, and combining with a multi-head self-attention mechanism to capture residue-enhancing features. The NTMFF-DTA model was comparatively tested against several leading baseline technologies on commonly used datasets. Experimental show that NTMFF-DTA can effectively and accurately predict DTA and outperform existing comparative models.

PMID:39998589 | DOI:10.1007/s12539-025-00692-9

J Fungi (Basel). 2025 Feb 10;11(2):133. doi: 10.3390/jof11020133.

ABSTRACT

Invasive candidiasis is a common fungal infection associated with multiple risk factors, such as cancer, neutropenia, corticosteroid therapy, catheterization, and the use of broad-spectrum antibiotic treatment. Candida albicans is the predominant causative agent, although other Candida species have been emerging in the last years, together with a rise in a number of strains resistant to the currently available antifungal drugs, which poses a challenge when treating these infections. Drug repurposing and drug combinations are promising strategies for the treatment of invasive mycoses. In this study, we evaluated the effect of the combination of fluconazole (FLZ) and cyclosporine A (CsA) against 39 clinical isolates and reference strains of Candida. Two methods, the Loewe additivity model and Bliss independence model, were used to assess the antifungal activity of the drug combination according to CLSI and EUCAST guidelines. The results demonstrated a synergistic effect between fluconazole (FLZ) and cyclosporine A (CsA) against 15-17 Candida isolates, depending on the evaluation model used, including FLZ-resistant strains of C. albicans, C. glabrata, C. parapsilosis, and C. tropicalis. Notably, the combination significantly reduced the minimum inhibitory concentration (MIC) of FLZ in a substantial number of isolates, including those with resistance to FLZ. Additionally, time-kill curve studies confirmed the synergistic interaction, further validating the potential of this combination as an alternative therapeutic strategy for candidiasis treatment. These findings emphasize the importance of investigating innovative drug combinations to address the challenges posed by antifungal resistance and improve treatment options for invasive fungal infections.

PMID:39997427 | DOI:10.3390/jof11020133

Cells. 2025 Feb 15;14(4):287. doi: 10.3390/cells14040287.

ABSTRACT

Patients with treatment-refractory/relapsing germ cell tumors (GCTs) have a dismal prognosis due to a lack of any effective therapy. Moreover, the efficacy of newly approved targeted therapies remains unexplored for cisplatin-resistant GCTs. Previously, it was demonstrated that folate receptor α (FRα) is overexpressed in many tumor types and efficiently targeted by the antibody-drug conjugate (ADC) mirvetuximab soravtansine (MIRV) in cisplatin-resistant cancers. We hypothesized that FRα represents an attractive target for treating treatment-refractory GCTs. We determined the expression of the FOLR1 gene in a broad range of GCT cell lines and tumor xenografts. We tested the antitumor efficacy of MIRV on cisplatin-resistant GCT cells in vitro and explored the ability of MIRV treatment to induce a bystander effect in the direct coculture of FRα-high and FRα-low cells. We found that the FOLR1 gene has significantly higher expression in testicular GCTs (TGCTs) than in normal testicular tissue. FOLR1 is highly expressed in the TCam2, JEG3, JAR, and NOY1 cell lines and their respective cisplatin-resistant variants. MIRV treatment induced apoptosis and a potent antiproliferative effect in cisplatin-resistant GCT cells in adherent and 3D spheroid cultures in vitro. A significant decrease in FRα-low 2102EP_R_NL cells was observed in the presence of FRα-high NOY1_R_SK in the presence of 12.5 nM MIRV, showing a potent bystander effect in the direct coculture. Immunohistochemical analysis confirmed significantly higher Folr1 protein expression in patients with TGCTs postchemotherapy than in chemo-naïve patients, as well as in patients with an unfavorable prognosis. In this study, we present data suggesting that the FOLR1 gene is highly expressed in (T)GCT cells in vitro and in vivo, and anti-FRα-targeting therapies should be investigated as a treatment modality in a subset of patients with TGCTs. Moreover, MIRV induced significant antitumor and bystander effects, thus showing its potential in further preclinical exploration and drug repurposing for a salvage treatment regime in refractory (T)GCT disease.

PMID:39996761 | DOI:10.3390/cells14040287

Sci Rep. 2025 Feb 24;15(1):6678. doi: 10.1038/s41598-025-91187-6.

ABSTRACT

In this retrospective observational study, we aimed to investigate the potential of natural language processing (NLP) for drug repositioning by analyzing the preventive effects of cardioprotective drugs against anthracycline-induced cardiotoxicity (AIC) using electronic medical records. We evaluated the effects of angiotensin II receptor blockers/angiotensin-converting enzyme inhibitors (ARB/ACEIs), beta-blockers (BBs), statins, and calcium channel blockers (CCBs) on AIC using signals extracted from clinical texts via NLP. The study included 2935 patients prescribed anthracyclines at a single hospital, with concomitant prescriptions of ARB/ACEIs, BBs, statins, and CCBs. Upon propensity score matching, groups with and without these medications were compared, and expressions suggestive of cardiotoxicity, extracted via NLP, were considered as the outcome. The hazard ratios for ARB/ACEIs, BBs, statins, and CCBs were 0.58 [95% CI: 0.38-0.88], 0.71 [95% CI: 0.35-1.44], 0.60 [95% CI 0.38-0.95], and 0.63 [95% CI: 0.45-0.88], respectively. ARB/ACEIs, statins, and CCBs significantly suppressed AIC, whereas BBs did not demonstrate statistical significance, possibly due to limited statistical power. NLP-extracted signals from clinical texts reflected the known effects of these medications, demonstrating the feasibility of NLP-based drug repositioning. Further investigation is needed to determine if similar results can be replicated using electronic medical records from other institutions.

PMID:39994365 | DOI:10.1038/s41598-025-91187-6

Ageing Res Rev. 2025 Feb 22:102698. doi: 10.1016/j.arr.2025.102698. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is an insidious, irreversible, complex neurodegenerative disorder characterized by progressive cognitive decline and memory loss; affecting millions worldwide. Despite decades of research, no effective disease-modifying treatment exists. However, drug repurposing is a progressive step in identifying new therapeutic uses of existing drugs. It has emerged as a promising strategy in the quest to combat AD. Various classes of repurposed drugs, such as antidiabetic, antihypertensive, antimicrobial, and anti-inflammatory, have shown potential neuroprotective effects in preclinical and clinical studies. These drugs act by combating free radicals generation, neuroinflammation, amyloid-beta aggregation, and tau hyper-phosphorylation. Furthermore, repurposing offers several advantages, including reduced time and cost compared to de novo drug development. It holds immense promise as a complementary approach to traditional drug discovery. Future research efforts should focus on elucidating the underlying mechanisms of repurposed drugs in AD, optimizing drug combinations, and conducting large-scale clinical trials to validate their efficacy and safety profiles. This review overviews recent advancements and findings in preclinical and clinical fields of different repurposed drugs for AD treatment.

PMID:39993451 | DOI:10.1016/j.arr.2025.102698

J Antimicrob Chemother. 2025 Feb 24:dkaf054. doi: 10.1093/jac/dkaf054. Online ahead of print.

ABSTRACT

BACKGROUND: The rise in fungal infections caused by multidrug-resistant pathogens like Candida haemulonii sensu stricto presents a significant global health challenge. The common resistance to current treatments underscores the urgency to explore alternative therapeutic strategies, including drug repurposing.

OBJECTIVES: To assess the potential of repurposing tafenoquine, an antimalarial agent, for antifungal use against C. haemulonii sensu stricto.

METHODS: The efficacy of tafenoquine was tested using in vitro assays for minimum inhibitory concentration (MIC), minimum fungicidal concentration, biofilm inhibition, cell damage, cell membrane integrity, nucleotide leakage, sorbitol protection assay, and efflux pump inhibition. The compound's cytotoxicity was assessed through a haemolysis assay, and in vivo safety and efficacy were tested using Tenebrio molitor larvae.

RESULTS: Tafenoquine exhibited potent fungicidal activity against C. haemulonii sensu stricto with an MIC of 4 mg/L and significantly inhibited biofilm formation by 60.63%. Tafenoquine also impaired mitochondrial functionality, leading to compromised cellular respiration. Despite these effects, tafenoquine did not cause significant protein leakage, indicating a distinct mechanism from membrane-targeting agents. In vivo study confirmed tafenoquine's non-toxic profile with no observed haemolysis or acute toxicity in the T. molitor model. During antifungal treatment with tafenoquine, a survival rate of approximately 60% was observed after 3 days.

CONCLUSIONS: The findings of this study highlight tafenoquine's potential as a promising candidate for antifungal drug repurposing, especially against C. haemulonii sensu stricto. Its effectiveness in inhibiting fungal growth and biofilm formation underscores its viability for further clinical development as a novel antifungal therapy.

PMID:39992314 | DOI:10.1093/jac/dkaf054

Circulation. 2025 Feb 24. doi: 10.1161/CIRCULATIONAHA.124.071954. Online ahead of print.

ABSTRACT

BACKGROUND: To date, the only effective treatment of severe aortic stenosis is valve replacement. With the introduction of transcatheter aortic valve replacement and extending indications to younger patients, the use of bioprosthetic valves (BPVs) has considerably increased. The main inconvenience of BPVs is their limited durability because of mechanisms similar as the fibro-calcifying processes observed in native aortic stenosis. One of the major gaps of the field is to identify therapeutic targets to prevent or slow the fibro-calcifying process leading to severe and symptomatic aortic stenosis. The aim was to identify new targets for anticalcification drugs to prevent aortic and BPV calcification using an unbiased translational approach.

METHODS: Explanted valves were collected from patients and organ donor hearts. A comparative transcriptomic analysis was performed on valvular interstitial cells (VIC) obtained from calcified (bicuspid and tricuspid) versus control valves. The mechanisms and consequences of aldehyde dehydrogenase 1 family member A1 (ALDH1A1) downregulation were analyzed in VIC cultures from control human aortic valves. ALDH1A1 was inhibited or silenced and its impact on osteogenic marker expression and calcification processes assessed in VIC. The effect of all-trans retinoic acid on calcification was tested on human VIC cultures and on 2 animal models: the model of subcutaneous implantation of bovine pericardium in rats and the model of xenograft aortic valve replacement in juvenile sheep.

RESULTS: Transcriptome analysis of human VIC identified ALDHA1 as the most downregulated gene in VIC from calcified versus control valves. In human VIC, ALDH1A1 expression is downregulated by TGF-β1 in a SMAD2/3-dependent manner. ALDH1A1 inhibition promotes an osteoblast-like VIC phenotype and increases calcium deposition through inhibition of retinoic acid receptor alpha signaling. Conversely, VIC treatment with retinoids decreases calcium deposition and attenuates VIC osteoblast activity. Last, all-trans retinoic acid inhibits calcification development of aortic BPV in both in vivo models and improves aortic valve echocardiographic parameters in the xenograft sheep model.

CONCLUSIONS: These results show that ALDH1A1 is downregulated in calcified valves, hence promoting VIC transition into an osteoblastic phenotype. Retinoic acid receptor alpha agonists, including all-trans retinoic acid through a drug repositioning strategy, represent a promising and innovative pharmacological approach to prevent calcification of native aortic valves and BPV.

PMID:39989358 | DOI:10.1161/CIRCULATIONAHA.124.071954