Bioinform Biol Insights. 2025 Apr 12;19:11779322251328269. doi: 10.1177/11779322251328269. eCollection 2025.

ABSTRACT

Drug repositioning holds great promise for reducing the time and cost associated with traditional drug discovery, but it faces significant challenges related to data imbalance and noise in negative samples. In this article, we introduce a novel method leveraging high negative oversampling (HNO) to address these challenges. Our approach integrates HNO with advanced techniques such as network-based graph mining, matrix factorization, and Bayesian inference, specifically designed for imbalanced data scenarios. Constructing high-quality negative samples is crucial to mitigate the detrimental effects of noisy negative data and enhance model performance. Experimental results demonstrate the efficacy of our approach in enhancing the performance of drug discovery models by effectively managing data imbalance and refining the selection of negative samples. This methodology provides a robust framework for improving drug repositioning, with potential applications in broader biomedical domains.

PMID:40290635 | PMC:PMC12033409 | DOI:10.1177/11779322251328269

Acta Derm Venereol. 2025 Apr 28;105:adv40697. doi: 10.2340/actadv.v105.40697.

ABSTRACT

In recent years, molecular target drugs have become integral in treating malignant tumours. Multikinase inhibitors (MKIs) have been associated with serious skin disorders, including hand-foot skin reaction (HFSR), which impair patient quality of life, often disrupting activities of daily living necessitating dose reduction or discontinuation. As the pathogenic mechanisms of these skin disorders are unknown, no effective treatments have been established. Previously, by drug repurposing using an in vitro culture system, certain azole antifungal drugs (AFDs) were identified that prevented sorafenib-induced cell death of normal human epidermal keratinocytes. In this study, topical ketoconazole demonstrated clinical improvement in hyperkeratosis and pain associated with sorafenib-induced HFSR. Investigation of the mechanism using the in vitro culture system revealed sorafenib to be particularly cytotoxic among MKIs. Annexin V and TUNEL staining revealed apoptosis was mainly involved in this cytotoxicity. Antibody arrays and western blot showed increased levels of secretion of interleukin-1 receptor antagonist and macrophage migration inhibitory factor in culture supernatants. AFDs suppressed the secretion of these cytokines and reduced apoptosis in keratinocytes. This study reveals one aspect of the pathogenesis of sorafenib-induced HFSR and demonstrates that AFDs may be an effective treatment.

PMID:40289816 | DOI:10.2340/actadv.v105.40697

Methods. 2025 Apr 25:S1046-2023(25)00109-4. doi: 10.1016/j.ymeth.2025.04.012. Online ahead of print.

ABSTRACT

Drug-target interaction (DTI) prediction is critical in drug repositioning and discovery. In current metapath-based prediction methods, attention mechanisms are often used to differentiate the importance of various neighbors, enhancing the model's expressiveness. However, in biological networks with small-scale imbalanced data, attention mechanisms are prone to interference from noise and missing data, leading to instability in weight learning, reduced efficiency, and an increased risk of overfitting. To address these issues, we propose the use of average aggregation to mitigate noise, simplify model complexity, and improve stability. Specifically, we introduce a simplified mean aggregation method for DTI prediction. This approach uses average aggregation, effectively reducing noise interference, lowering model complexity, and preventing overfitting, making it especially suitable for current biological networks. Extensive testing on three heterogeneous biological datasets shows that SNADTI outperforms 12 leading methods across two evaluation metrics, significantly reducing training time and validating its effectiveness in DTI prediction. Complexity analysis reveals that our method offers a substantial computational speed advantage over other methods on the same dataset, highlighting its enhanced efficiency. Experimental results demonstrate that SNADTI excels in prediction accuracy, stability, and reproducibility, confirming its practicality and effectiveness in DTI prediction.

PMID:40288620 | DOI:10.1016/j.ymeth.2025.04.012

Int J Pharm. 2025 Apr 24:125639. doi: 10.1016/j.ijpharm.2025.125639. Online ahead of print.

ABSTRACT

The current research work explored the anti-inflammatory and antifungal activity of loratadine versus Candida albicans for treating vulvovaginal candidiasis (VVC). Loratadine was incorporated into terpene-enriched nanocarrier invasomes (IVS) using a thin-film hydration approach, where a D-optimal design was employed to investigate the lipid amount, terpene percent and type impact on the entrapment efficiency percentage (EE%), particle size (PS), polydispersity index (PDI), and zeta potential (ZP). The optimal formula was assessed regarding morphology, Fourier transform infrared (FTIR), in silico study, and differential scanning calorimetry (DSC). Subsequently, the optimal formula was incorporated into a gel base and characterized via ex vivo permeation studies. Lastly, in vivo investigations were performed to evaluate the performance of the loratadine-loaded IVS gel. The selected formula was spherical and had EE% of 91.95 ± 1.5 %, PS of 132.81 ± 2.7 nm, PDI of 0.326 ± 0.08, and ZP of -23.42 ± 0.38 mV. The FTIR and DSC studies verified the successful entrapment of the drug, while the in silico study demonstrated the thermodynamic stability of IVS. The IVS gel showed enhancement in drug deposition within vaginal tissues of 3.8 folds compared to free drug gel. Loratadine-loaded IVS gel showed remarkable improvement in eradicating candida infection by suppression of β-D-glucan. Furthermore, the IVS gel showed a significant anti-inflammatory effect reflected by marked suppression of NO, iNOS, COX-2, TNF-α, IL-1B and down-regulation in NF-κB, Src and Syk gene expressions. These results were confirmed via histopathological and immunohistological examinations. This work highlights the potential of loratadine as a promising therapy for VVC.

PMID:40287073 | DOI:10.1016/j.ijpharm.2025.125639

Drug Discov Today. 2025 Apr 24:104364. doi: 10.1016/j.drudis.2025.104364. Online ahead of print.

ABSTRACT

The human metapneumovirus (hMPV), a member of the Pneumoviridae family, is a significant respiratory pathogen that causes severe infections in infants, children, the elderly, adults with chronic illnesses, and individuals with immunocompromised conditions. Globally, hMPV is recognized as the second leading cause of bronchiolitis and pneumonia among children under five. The absence of targeted antiviral treatments or vaccines for hMPV significantly strains the global health-care system. This review summarizes recent advances and scientific findings on hMPV by reviewing the current literature on its life cycle, structure, function, prevention, and treatment options.

PMID:40286981 | DOI:10.1016/j.drudis.2025.104364

Lancet Psychiatry. 2025 Apr 23:S2215-0366(25)00066-5. doi: 10.1016/S2215-0366(25)00066-5. Online ahead of print.

ABSTRACT

Existing pharmacotherapies and psychotherapies are often inadequate, and discovery for new pharmacological treatments in psychiatry is slow. Existing pharmacotherapies are, however, often inadequate. Few truly novel pharmacotherapies have emerged in the past four decades, largely due to the absence of a known pathophysiology for each disorder. In this Personal View, we describe the platform we have adopted that enables targeted drug repurposing. With this approach, patient-derived stem cells are used to detect transcriptomic targets to identify existing drugs that address these targets. These drugs are then validated in non-human animal models and pharmacoepidemiological studies before being tested in clinical trials. Our targeted drug repurposing platform bypasses the absence of known pathophysiology. Validation steps bring greater scientific rigour and mechanistic insights to drug repurposing to allow only drug candidates with the strongest mechanistic evidence to be tested in clinical trials.

PMID:40286796 | DOI:10.1016/S2215-0366(25)00066-5

Viruses. 2025 Mar 28;17(4):491. doi: 10.3390/v17040491.

ABSTRACT

The SARS-CoV-2 proteases Mpro and PLpro are critical targets for antiviral drug development for the treatment of COVID-19. The 1,2,4-thiadiazole functional group is an inhibitor of cysteine proteases, such as papain and cathepsins. This chemical moiety is also present in ceftaroline fosamil (CF), an FDA-approved fifth-generation cephalosporin antibiotic. This study investigates the interactions between CF, its primary metabolites (M1 is dephosphorylated CF and M2 is an opened β-lactam ring) and derivatives (protonated M1H and M2H), and its open 1,2,4-thiadiazole rings derivatives (open-M1H and open-M2H) with SARS-CoV-2 proteases and evaluates CF's effects on in vitro viral replication. In silico analyses (molecular docking and molecular dynamics (MD) simulations) demonstrated that CF and its metabolites are potential inhibitors of PLpro and Mpro. Docking analysis indicated that the majority of the ligands were more stable with Mpro than PLpro; however, in vitro biochemical analysis indicated PLpro as the preferred target for CF. CF inhibited viral replication in the human Calu-3 cell model at submicromolar concentrations when added to cell culture medium at 12 h. Our results suggest that CF should be evaluated as a potential repurposing agent for COVID-19, considering not only viral proteases but also other viral targets and relevant cellular pathways. Additionally, the reactivity of sulfur in the 1,2,4-thiadiazole moiety warrants further exploration for the development of viral protease inhibitors.

PMID:40284934 | DOI:10.3390/v17040491

Pharmaceutics. 2025 Mar 26;17(4):419. doi: 10.3390/pharmaceutics17040419.

ABSTRACT

In the original publication [...].

PMID:40284534 | DOI:10.3390/pharmaceutics17040419

Pharmaceutics. 2025 Apr 19;17(4):536. doi: 10.3390/pharmaceutics17040536.

ABSTRACT

Background/Objectives: Ovarian cancer remains one of the most commonly diagnosed malignancies among women worldwide. The heterogeneity among tumor subtypes and the emergence of treatment resistance have raised significant concerns regarding the long-term efficacy of chemotherapy, radiotherapy, and immunotherapy. In response to these challenges, drug repurposing strategies-utilizing existing drugs in novel therapeutic contexts-have gained increasing attention. This study aimed to investigate the cytotoxic and apoptotic effects of the combined application of doxorubicin (DX) and thymoquinone (TQ) on ovarian adenocarcinoma cells (OVCAR3). Methods: OVCAR3 cells were cultured in RPMI medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. Cell viability and proliferation were assessed using the MTT assay following treatment with various concentrations of DX and TQ. NucBlue immunofluorescence staining was employed to examine nuclear morphology and to identify apoptosis-associated changes. Additionally, quantitative real-time polymerase chain reaction (qRT-PCR) was per-formed to evaluate the expression levels of apoptosis-related and oncogenic pathway genes, including RAF, RAS, Bcl-2, and Bax. Results: The results demonstrated that the combination of DX and TQ significantly reduced OVCAR3 cell viability and induced apoptosis in a dose-dependent manner. qRT-PCR analysis revealed a downregulation of RAS, RAF, and Bcl-2 expression, along with an upregulation of Bax, indicating activation of the intrinsic apoptotic pathway. These findings suggest that thymoquinone exerts an-ti-proliferative and pro-apoptotic effects by modulating the RAS/RAF signaling cascade. Furthermore, the co-administration of thymoquinone with doxorubicin potentiated these effects, suggesting a synergistic interaction between the two agents. Conclusions: Histopathological and molecular evaluations further confirmed the activation of apoptosis and the suppression of key oncogenic pathways. Collectively, these results underscore the therapeutic potential of thymoquinone as both a monotherapy and an adjuvant to conventional chemotherapy, warranting further validation in preclinical and clinical studies.

PMID:40284530 | DOI:10.3390/pharmaceutics17040536

Int J Environ Res Public Health. 2025 Mar 21;22(4):464. doi: 10.3390/ijerph22040464.

ABSTRACT

Data-driven approaches to clinical research are necessary for understanding and effectively treating infectious diseases. However, challenges such as issues with data validity, lack of collaboration, and difficult-to-treat infectious diseases (e.g., those that are rare or newly emerging) hinder research. Prioritizing innovative methods to facilitate the continued use of data generated during routine clinical care for research, but in an organized, accelerated, and shared manner, is crucial. This study investigates the potential of CURE ID, an open-source platform to accelerate drug-repurposing research for difficult-to-treat diseases, with COVID-19 as a use case. Data from eight US health systems were analyzed using least absolute shrinkage and selection operator (LASSO) regression to identify key predictors of 28-day all-cause mortality in COVID-19 patients, including demographics, comorbidities, treatments, and laboratory measurements captured during the first two days of hospitalization. Key findings indicate that age, laboratory measures, severity of illness indicators, oxygen support administration, and comorbidities significantly influenced all-cause 28-day mortality, aligning with previous studies. This work underscores the value of collaborative repositories like CURE ID in providing robust datasets for prognostic research and the importance of factor selection in identifying key variables, helping to streamline future research and drug-repurposing efforts.

PMID:40283693 | DOI:10.3390/ijerph22040464

J Clin Med. 2025 Apr 14;14(8):2673. doi: 10.3390/jcm14082673.

ABSTRACT

Epilepsy is a neurological disorder characterized by repeated convulsions. Antiepileptic drugs (AEDs) are the main course of therapy for epilepsy. These medications are given according to each patient's personal medical history and the types of seizures they suffer. They have been employed for decades to manage epilepsy, thus delivering relief from seizures through numerous mechanisms of action. Aside from their anticonvulsant attributes, current evidence suggests that certain AEDs may display potential inhibitory effects against cancer invasion and metastasis. This review explored the complicated interactions between the modes of action of AEDs and the pathways causing cancer, and the potential impact of AEDs on the invasion and metastasis of various forms of cancer, while addressing their associated side effects. For example, valproic acid inhibits histone deacetylase, causing hyperacetylation of genes, especially those regulating cell cycle, culminating in cell cycle arrest. Topiramate inhibits carbonic anhydrase, thus disrupting the acidic microenvironment needed for cancer cells to thrive. Lacosamide increases the slow inactivation of the voltage gated Na+ channel, thus inhibiting the growth, proliferation, and metastasis of many cancers. Although drug development is a complex task due to regulatory, intellectual property, and economic challenges, researchers are exploring drug repurposing tactics to overcome these challenges and to find new therapeutic alternatives for diseases like cancer. Thus, drug repurposing is considered among the most effective ways to develop drug candidates using novel properties and therapeutic characteristics, and this review also discusses these issues.

PMID:40283503 | DOI:10.3390/jcm14082673

Cancers (Basel). 2025 Apr 18;17(8):1357. doi: 10.3390/cancers17081357.

ABSTRACT

BACKGROUND/OBJECTIVES: Beta adrenergic signaling has been implicated in cancer progression, leading to interest in repurposing beta blockers (BBs) as adjunctive anti-cancer agents. However, clinical findings are inconsistent. This systematic review and meta-analysis evaluates the association between BB use and survival outcomes in cancer patients.

METHODS: A systematic search of OVID Medline, EMBASE, and CENTRAL was conducted through 13 September 2023, for studies comparing survival outcomes in solid tumor patients using BBs versus non-users. Eligible studies reported hazard ratios (HRs) for overall survival (OS), progression-free survival (PFS), or cancer-specific survival (CSS). Perioperative studies and those without BB-specific HRs were excluded. Data extraction and quality assessment were performed in duplicate using ROBINS-I. A random-effects model was used, with heterogeneity assessed by the I2 statistic.

RESULTS: Seventy-nine studies (492,381 patients) met the inclusion criteria; 2.5% were prospective. The most frequently studied cancers were breast (n = 33), ovarian (n = 30), and colorectal (n = 28). BB use was associated with improved PFS (HR 0.78, 95% CI: 0.66-0.92, I2 = 79.8%), with significance maintained after excluding high-bias studies (HR 0.74, 95% CI: 0.61-0.91, I2 = 36.6%). No significant associations were observed for OS (HR 0.99, 95% CI: 0.94-1.04, I2 = 84.9%) or CSS (HR 0.95, 95% CI: 0.91-1.00, I2 = 77.4%).

CONCLUSIONS: BB use may be associated with longer PFS in cancer patients, but findings are limited by study design and heterogeneity; high-quality prospective studies are needed.

PMID:40282534 | DOI:10.3390/cancers17081357

Eur J Paediatr Neurol. 2025 Apr 15;56:46-50. doi: 10.1016/j.ejpn.2025.03.016. Online ahead of print.

ABSTRACT

Leukodystrophies, a group of genetic disorders primarily affecting brain white matter, were once considered untreatable. Advances in MRI and genetic diagnostics now allow most patients to receive a genetic diagnosis, and emerging treatments are shifting the field from therapeutic nihilism to cautious optimism. Allogenic haematopoietic stem cell transplantation (HSCT), used since the 1980s, has shown efficacy in specific leukodystrophies, such as adrenoleukodystrophy and metachromatic leukodystrophy, when administered early. Gene therapy has become a viable option, with ex vivo approaches like atidarsagene autotemcel providing promising outcomes for early-onset MLD. Trials for gene replacement and antisense oligonucleotide therapies are ongoing for several leukodystrophies, including Canavan disease and Alexander disease. Certain treatments, such as guanabenz for Vanishing White Matter, target disease-specific dysregulated molecular pathways. Despite these advances, challenges remain, including the ultrarare nature of most leukodystrophies, limited natural history data, high treatment costs, and barriers to accessibility. Future developments, including newborn screening and close international collaboration, aim to enhance early diagnosis, refine treatment timing, and expand access to innovative therapies.

PMID:40279833 | DOI:10.1016/j.ejpn.2025.03.016

Sci Data. 2025 Apr 25;12(1):695. doi: 10.1038/s41597-025-04981-2.

ABSTRACT

Drug-target interactions constitute the fundamental basis for understanding drug action mechanisms and advancing therapeutic discovery. While existing drug-target databases have contributed valuable resources, they exhibit structural and functional fragmentation due to heterogeneous data sources and annotation standards. Building upon the high-confidence drug-gene interactions curated in HCDT 1.0, we present HCDT 2.0, a comprehensive and standardized resource that expands the scope through multiomics data integration. This update incorporates three-dimensional interactions including drug-gene, drug-RNA and drug-pathway interactions. The current version contains 1,284,353 curated interactions: 1,224,774 drug-gene pairs (678,564 drugs × 5,692 genes), 11,770 drug-RNA mappings (316 drugs × 6,430 RNAs), and 47,809 drug-pathway links (6,290 drugs × 3,143 pathways), alongside 16,317 drug-disease associations. To enhance biological interpretability, we further integrated pathway-gene and RNA-gene regulatory relationships. In addition, we integrated 38,653 negative DTIs covering 26,989 drugs and 1,575 genes. This integrative framework not only addresses critical gaps in cross-scale data representation but also establishes a robust foundation for systems pharmacology applications, including drug repurposing, adverse event prediction, and precision oncology strategies.

PMID:40281032 | DOI:10.1038/s41597-025-04981-2

Acta Neuropathol Commun. 2025 Apr 25;13(1):84. doi: 10.1186/s40478-025-01986-1.

ABSTRACT

Prolactinoma is the most prevalent pituitary neuroendocrine tumor and dopamine agonists (DAs) targeting dopamine D2 receptor (DRD2) are recommended as the first-line treatment. However, varying degrees of DA resistance limit patient benefit. Our study used transcriptome sequencing of surgical tumor samples and found abnormal cholesterol metabolism in prolactinoma, especially in DA-resistant tumors. We found that cholesterol significantly enhanced the resistance of prolactinoma MMQ cell lines to cabergoline in vitro and in vivo xenografts. Further, cholesterol did not affect the total protein level of DRD2, but changed the distribution of DRD2 with downregulation of its membrane abundance and upregulation of cytoplasmic localization. Mechanistically, immunoprecipitation combined with mass spectrometry revealed cholesterol increased binding affinity between DRD2 and stress granules (SGs) core proteins, such as G3BP1. Western blot experiment of G3BP1 and fluorescent probe were used to confirm the formation of SGs after cholesterol treatment in MMQ cells and tumor xenografts, as well as in surgical tumor samples. Interfering the formation of SGs by overexpressing of USP10 and using the small molecule ISRIB reversed cholesterol's effect on DRD2 cellular distribution and DA resistance in MMQ cells. Finally, a non-specificity inhibitor of SGs, anisomycin identified by drug repositioning analysis, could attenuate cholesterol-induced cabergoline resistance in vitro. Taken together, our findings suggest that abnormal cholesterol metabolism reduces DRD2 membrane localization via stress granules formation, which may be an important reason for the DA resistance of prolactinoma patients.

PMID:40281543 | DOI:10.1186/s40478-025-01986-1

Sci Rep. 2025 Apr 25;15(1):14436. doi: 10.1038/s41598-025-98894-0.

ABSTRACT

Extracellular vesicles (EVs) are important mediators of intercellular communication and play key roles in the regulation of pathophysiological processes. In diabetic kidney disease (DKD), it has been reported that macrophages recruited in the mesangial region may play pathogenic roles through inducing local inflammation in glomeruli. We focused on EV-mediated crosstalk between mesangial cells (MC) and macrophages as a novel therapeutic target for DKD. EVs released from MC induced inflammation in macrophages and the effect was enhanced under high-glucose conditions. For discovering novel therapeutic agents which can inhibit such EV-mediated mechanisms, drug repositioning is considered as an effective tool. We established a unique screening strategy and screened agents to aim at maximizing their specificity and potency to inhibit EV mechanisms, along with minimizing their toxicity. We succeeded in identifying alvespimycin, an HSP90 inhibitor. Treatment of diabetic rats with alvespimycin significantly suppressed mesangial expansion, inflammatory gene activation including macrophage markers, and proteinuria. The inhibitory effect on EV uptake was specific to alvespimycin compared with other known HSP90 inhibitors. MC-derived EVs are crucial for inflammation by intercellular crosstalk between MC and macrophages in DKD, and alvespimycin effectively ameliorated the progression of DKD by suppressing EV-mediated actions, suggesting that EV-targeted agents can be a novel therapeutic strategy.

PMID:40281012 | DOI:10.1038/s41598-025-98894-0

Biomed Pharmacother. 2025 Apr 24;187:118079. doi: 10.1016/j.biopha.2025.118079. Online ahead of print.

ABSTRACT

This study investigated a novel immunization therapy for pre-clinical aggressive metastatic breast cancer using immunogenic cell lysates derived from 4T1-luc cells treated with cisplatin and methotrexate, addressing the critical need for improved treatments given the poor prognosis associated with breast cancer metastasis and its significant mortality rate. Methotrexate, a conventional cytotoxic agent, demonstrated a previously unrecognized capacity to induce immunogenic cell lysates, presenting a potential drug repositioning opportunity. In a murine model of stage IV metastatic breast cancer, immunization with these lysates significantly reduced primary tumor growth and lung metastasis, as assessed by bioluminescence imaging. Immunization also modulated immune cell populations, reducing splenomegaly and hepatomegaly, and partially reversing the immunosuppressive phenotype associated with 4T1-luc tumor growth, as evidenced by cytokine profiling (IL-6 and IFN-γ) and flow cytometry analysis of CD4 + and CD8 + T cell subpopulations. Specifically, methotrexate-treated lysates induced a significant shift in CD4 + T cells towards an effector phenotype. These findings highlight the potential of this immunotherapy approach to improve breast cancer treatment outcomes and warrant further investigation.

PMID:40280032 | DOI:10.1016/j.biopha.2025.118079

IEEE J Biomed Health Inform. 2025 Apr 25;PP. doi: 10.1109/JBHI.2025.3564360. Online ahead of print.

ABSTRACT

Drug repositioning (DR) has emerged as an effective method of identifying new indications for existing drugs. Many DR methods have demonstrated superior performance. However, most of them utilize a limited number of biological entities, ignoring the critical role of other entities in addressing data sparsity as well as improving model generalization capabilities. In addition, fully capturing high-order information of biological data still needs to be fully explored. To address above issues, a model based on transformer and enhanced multi-view contrastive learning (TEMCL) is proposed for predicting drug-disease associations (DDAs). Firstly, transformer is employed to obtain high-order features of nodes from similarity information. Secondly, based on similarity matrices and association matrices of nodes, two different types of views are constructed, i.e., homogeneous hypergraphs and heterogeneous association graphs. Among them, to alleviate sparsity problem existing in heterogeneous graphs, protein nodes as well as meta-path enhancement strategy are introduced. Thirdly, hypergraph convolutional network and heterogeneous graph transformer are used to extract node features on above two types of views, respectively. Contrastive learning is applied to obtain more representative features. Finally, multilayer perceptron (MLP) is used for predicting DDAs. Experiments show that TEMCL outperforms existing methods on DR task, exhibiting superior performance. In addition, case studies further demonstrate the effectiveness of this model. TEMCL provides new insights for identifying novel DDAs.

PMID:40279215 | DOI:10.1109/JBHI.2025.3564360

Adv Exp Med Biol. 2025 Apr 26. doi: 10.1007/5584_2025_863. Online ahead of print.

ABSTRACT

Despite advances in cancer research, treating malignancies remains challenging due to issues like drug resistance, disease heterogeneity, and the limited efficacy of current therapies, particularly in relapsed or refractory cases. In recent years, several drugs originally approved for non-cancer indications have shown potential in cancer treatment, demonstrating anti-proliferative, anti-metastatic, and immunomodulatory effects. Drug repurposing has shown immense promise due to well-established safety profiles and mechanisms of action of the compounds. However, the implementation is fraught with clinical, logistical, regulatory, and ethical challenges, especially in diseases such as leukaemia and multiple myeloma. This chapter examines the treatment challenges in leukaemia and multiple myeloma, focusing on the role of drug repurposing in addressing therapeutic resistance and disease variability. It highlights the potential of personalized, tailored combination therapies, using repurposed drug components, to offer more effective, targeted, and cost-efficient treatment strategies, overcoming resistance and improving patient outcomes.

PMID:40279000 | DOI:10.1007/5584_2025_863

Neurochem Res. 2025 Apr 25;50(3):154. doi: 10.1007/s11064-025-04404-z.

ABSTRACT

Parkinson's disease (PD) is one of neurodegenerative diseases characterized by the progressive loss of dopaminergic neurons in the substantia nigra. The development of a neuroprotective therapy is crucial for mitigating features and progression of PD. Since autophagy induction has recently emerged as a promising neuroprotective strategy, this study aimed to identify autophagy-inducing compounds and evaluate their neuroprotective activity. Among 3,200 compounds consisting of FDA-approved drugs or are under active development, 547 compounds targeting neurological diseases were filtered in, and three compounds (sertraline, tiagabine and bicifadine) were finally identified to exhibit the autophagy-inducing activity and also demonstrated the autophagy-dependent neuroprotective action by inhibiting the mammalian target of rapamycin (mTOR) in 6-hydroxydopamine (6-OHDA)-induced neurotoxicity in PC12 cells. Furthermore, the analysis of neurochemical changes suggested that the ability of those compounds to restore the quantity of cellular neurotransmitters such as betaine, 5-hydroxyindoleacetic acid and kynurenine might be linked to their neuroprotective function. In conclusion, compounds like sertraline, tiagabine, and bicifadine that have the ability to induce autophagy and inhibit mTOR might be repurposed as PD treatment to protect the neuronal cells.

PMID:40278973 | DOI:10.1007/s11064-025-04404-z