Front Cell Dev Biol. 2025 Jul 1;13:1551010. doi: 10.3389/fcell.2025.1551010. eCollection 2025.

ABSTRACT

INTRODUCTION: Drug repurposing is gaining consideration in cancer due to the challenges of poor outcomes and resistance associated with the current conventional modalities. Non-steroidal anti-inflammatory drugs (NSAIDs), widely used for treating inflammation, are being explored for their potential efficacy in cancer treatment, including prostate cancer (PCa). This study aims to evaluate the efficacy of Piroxicam (PXM), an NSAID, in enhancing the sensitivity of PCa cells to chemotherapy and hormonal drugs.

METHODS: Computational analysis was conducted to identify differentially expressed genes between our established murine PCa cell models, PLum-AD (androgen-dependent) and PLum-AI (androgen-independent), to uncover potential therapeutic targets. In two-dimensional (2D) cell culture, cell proliferation, viability, and migration assays were performed on PLum-AD and PLum-AI cells treated with PXM alone or in combination with docetaxel (Doc) or enzalutamide (Enz). Additionally, the impact of these treatments on stem-like progenitor cells was assessed using three-dimensional (3D)-Matrigel™-based sphere-forming and organoid formation assays.

RESULTS: Transcriptomic analysis revealed that inflammatory pathways are enriched during PCa progression, making them viable targets for NSAID-based interventions. Single treatment of PXM demonstrated significant anti-cancer effects on PLum-AD and PLum-AI cells, evidenced by reduced cell proliferation, viability, migration, sphere growth, and organoid growth.

DISCUSSION: Importantly, PXM treatment in combination with Doc or Enz resulted in more pronounced antineoplastic effects compared to single-drug exposure. Our work suggests PXM as a potential adjunctive therapy to enhance the efficacy of conventional treatments in PCa patients.

PMID:40666288 | PMC:PMC12259556 | DOI:10.3389/fcell.2025.1551010

Iran J Basic Med Sci. 2025;28(5):647-654. doi: 10.22038/ijbms.2025.83856.18143.

ABSTRACT

OBJECTIVES: Glycation is one of the primary underlying processes attributed to senescence and related diseases. No medicine currently targets this harmful manifestation. Drug repurposing is an efficient and cost-effective way of developing drugs. The present study evaluated meloxicam, a clinically used NSAID, for its ability to offer protection against glycative stress.

MATERIALS AND METHODS: Methylglyoxal (MGO; 17.25 mg/kg) was administered for two weeks to create a rat model of glycative stress. Aminoguanidine (AG; 50 mg/kg) and Meloxicam (MEL; 0.15, 0.3, and 0.6 mg/kg) were used as standard and test agents, respectively. Afterward, the cognitive (Morris Water Maze), liver (LFT), and kidney (Creatinine) functioning were evaluated. The expression of genes of interest (TNF-α, RAGE, BACE, Glyoxalase, and VEGF) were estimated (qPCR) in the liver, brain, and kidney along with histopathology (H&E staining). Carboxymethyllysine (CML) levels in rat plasma were evaluated via ELISA.

RESULTS: MEL treatment has significantly (P<0.05) protected the MGO-induced cognitive (duration in target quadrant, time taken to get to target quadrant, and the frequency of crossings via platform location), hepatic, and renal impairment. The qPCR data revealed that MEL prevented MGO-induced enhancement in the expression of genes of interest. Additionally, the CML levels were significantly (P<0.005) normalized by concomitant administration of MEL. Histopathological examination did not reveal any remarkable outcomes.

CONCLUSION: MEL has significantly mitigated the rats' MGO-induced cognitive, liver, and kidney impairments. Hence, it appears to be a potential molecule for repurposing as an antiglycation agent.

PMID:40666177 | PMC:PMC12258788 | DOI:10.22038/ijbms.2025.83856.18143

Respir Res. 2025 Jul 15;26(1):247. doi: 10.1186/s12931-025-03320-8.

ABSTRACT

RATIONALE: Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterogeneity in COPD risk. COPD occurrence in non-smokers with AAT deficiency (AATD) suggests that inflammatory processes may contribute to COPD risk independently of smoking. We hypothesized that inflammatory protein biomarkers in non-AATD COPD are associated with moderate-to-severe COPD in AATD individuals, after accounting for clinical factors.

METHODS: Participants from the COPDGene (Pi*MM) and AAT Genetic Modifiers Study (Pi*ZZ) were included. Proteins associated with FEV1/FVC were identified, adjusting for confounders and familial relatedness. Lung-specific protein-protein interaction (PPI) networks were constructed. Proteins associated with AAT augmentation therapy were identified, and drug repurposing analyses performed. A protein risk score (protRS) was developed in COPDGene and validated in AAT GMS using AUROC analysis. Machine learning ranked proteomic predictors, adjusting for age, sex, and smoking history.

RESULTS: Among 4,446 Pi*MM and 352 Pi*ZZ individuals, sixteen blood proteins were associated with airflow obstruction, fourteen of which were highly expressed in lung. PPI networks implicated regulation of immune system function, cytokine and interleukin signaling, and matrix metalloproteinases. Eleven proteins, including IL4R, were linked to augmentation therapy. Drug repurposing identified antibiotics, thyroid medications, hormone therapies, and antihistamines as potential adjunctive AATD treatments. Adding protRS improved COPD prediction in AAT GMS (AUROC 0.86 vs. 0.80, p = 0.0001). AGER was the top-ranked protein predictor of COPD.

CONCLUSIONS: Sixteen proteins are associated with COPD and inflammatory processes that predict airflow obstruction in AATD after accounting for age and smoking. Immune activation and inflammation are modulators of COPD risk in AATD.

PMID:40665347 | DOI:10.1186/s12931-025-03320-8

IEEE J Biomed Health Inform. 2025 Jul 15;PP. doi: 10.1109/JBHI.2025.3589290. Online ahead of print.

ABSTRACT

Accurate prediction of drug-disease associations (DDAs) is essential for drug repositioning and the development of novel therapeutic strategies. However, existing methods often suffer from limited prior knowledge and the use of oversimplified negative sampling techniques, which hinder their ability to capture the complex relationships between drugs and diseases. To break through these limitations, we propose a new model, Hierarchical Attention Mechanism-Based Negative Sampling (HA-NegS), which aims to enhance the prediction of potential DDAs. In this study, HA-NegS further computes the similarity information between drugs and diseases and constructs heterogeneous and homogeneous networks based on it. For the similarity network, HA-NegS fuses Graph Convolutional Network (GCN) and Graph Attention Network (GAT) to effectively capture the neighborhood features of the target nodes. Subsequently, the model incorporates a hierarchical sampling strategy using the PageRank algorithm to rank nodes in descending order of global importance. The attention mechanism is then used to calculate the attention score and re-rank the nodes accordingly. This approach ensures the reliability of the negative sample selection. In order to obtain optimized representations, we use graph contrastive learning methods to refine drug and disease features with homogeneous and heterogeneous neighborhood information. Experimental results on a benchmark dataset show that HA-NegS outperforms existing baseline methods in predicting DDA. In addition, case studies for Alzheimer's disease and Parkinson's disease highlight the effectiveness of HA-NegS in discovering new therapeutic applications for existing drugs.

PMID:40663664 | DOI:10.1109/JBHI.2025.3589290

OMICS. 2025 Jul 15. doi: 10.1177/15578100251359275. Online ahead of print.

ABSTRACT

Head and neck squamous cell carcinoma (HNSCC) displays significant molecular heterogeneity, which hinders effective and safe treatments and clinical outcomes. This predicament also points to the need for an individually tailored personalized/precision medicine approach in HNSCC that includes the oral, hypopharyngeal, nasopharyngeal, and laryngeal subtypes. This study, with the overarching aim of personalized/precision medicine, attempted to identify (1) a molecular target shared by the HNSCC subtypes and (2) screen for potential anticancer drugs for repurposing that may work across the HNSCC subtypes. The National Center for Biotechnology Information-Gene Expression Omnibus database was used to select the datasets (GSE127165, GSE2379, GSE37991, and GSE12452) for the analyses of differentially expressed genes in HNSCC subtypes. Our transcriptome analyses of the HNSCC subtypes revealed 305 upregulated genes. Subsequently, protein network construction with 305 genes showed three closely interconnected high-risk HNSCC prognostic clusters. Importantly, COL1A1 was identified as the pivotal target regulating the pathogenic cluster protein implicated in cancer pathways. Molecular docking with 1040 anticancer drugs identified bleomycin as a potential candidate, exhibiting a binding affinity of -12.425 kcal/mol and a favorable binding free energy of -92.05 kcal/mol. The dynamic simulations confirmed the stability of the system, with stable interactions over 200 ns. Quantum calculations provided insights into bleomycin's chemical and electronic properties, revealing crucial interactions with COL1A1. In conclusion, our study proposes COL1A1 as a promising potential therapeutic target among HNSCC subtypes, with bleomycin demonstrating notable repurposing potential for HNSCC.

PMID:40662975 | DOI:10.1177/15578100251359275

Bioinformatics. 2025 Jul 1;41(Supplement_1):i77-i85. doi: 10.1093/bioinformatics/btaf184.

ABSTRACT

MOTIVATION: Drug repositioning, identifying new therapeutic applications for existing drugs, can significantly reduce the time and cost involved in drug development. Recent studies have explored the use of Anatomical Therapeutic Chemical (ATC) codes in drug repositioning, offering a systematic framework to predict ATC codes for a drug. The ATC classification system organizes drugs according to their chemical properties, pharmacological actions, and therapeutic effects. However, its complex hierarchical structure and the limited scalability at higher levels present significant challenges for achieving accurate ATC code prediction.

RESULTS: We propose a novel approach to predict ATC codes of drugs, named Feature Aggregation and Convolution with Transformer models (FACT). This method computes three types of drug similarities, incorporating ATC code similarity with hierarchical weights and masked drug-ATC code associations. These features are then aggregated for each target drug-ATC code pair and processed through a convolution-transformer encoder to generate three embeddings. The embeddings are finally used to estimate the probability of an association between the target pair. The experimental results demonstrate that the proposed method achieves an area under the receiver operating characteristic curve (AUROC) of 0.9805 and an area under the precision-recall curve of 0.9770 at level 4 of the ATC codes, outperforming the previous methods by 15.05% and 18.42%, respectively. This study highlights the effectiveness of integrating diverse drug features and the potential of transformer-based models in ATC code prediction.

AVAILABILITY AND IMPLEMENTATION: Source code of FACT is freely available at https://github.com/knhc1234/FACT.

PMID:40662799 | DOI:10.1093/bioinformatics/btaf184

Curr Alzheimer Res. 2025 Jul 14. doi: 10.2174/0115672050393875250626065205. Online ahead of print.

ABSTRACT

INTRODUCTION: Type 2 diabetes mellitus (T2D) is a known risk factor for developing Alzheimer's disease (AD). Recent research shows that both diseases share complex and related pathophysiological processes. Network medicine approaches can help to elucidate common dysregulated processes among different diseases, such as AD and T2D. Thus, the aim of this work was to determine differentially expressed genes (DEGs) in AD and T2D and to apply a network medicine approach to identify the microRNAs (miRNAs) involved in the AD-T2D association.

METHODS: Gene expression microarray data sets consisting of 384 control samples and 399 samples belonging to AD and T2D disease were analyzed to obtain DEGs shared by both diseases; the miRNAs associated with these DEGs were predicted using a network medicine approach. Finally, potential small molecules targeting these potentially deregulated miRNAs were identified.

RESULTS: AD and T2D shared a small subset of 82 downregulated DEGs. These genes were significantly associated (p < 0.01) with the ontology terms of chemical synaptic deregulation. DEGs were associated with 12 miRNAs expressed in specific tissues for AD and T2D. Such miRNAs were also primarily associated with the ontology terms related to synaptic deregulation and cancer, and AKT signaling pathways. Steroid anti-inflammatory drugs, antineoplastics, and glucose metabolites were predicted to be potential regulators of the 12 shared miRNAs.

DISCUSSION: The network medicine approach integrating DEGs and miRNAs enabled the identification of shared, potentially deregulated biological processes and pathways underlying the pathophysiology of AD and T2D. These common molecular mechanisms were also linked to drugs currently used in clinical practice, suggesting that this strategy may inform future drug repurposing efforts. Nonetheless, further in-depth biological validation is required to confirm these findings.

CONCLUSION: Network medicine allowed identifying 12 miRNAs involved in the AD-T2D association, and these could be drug targets for the design of new treatments; however, the identified miRNAs need further experimental confirmation.

PMID:40662549 | DOI:10.2174/0115672050393875250626065205

Medicine (Baltimore). 2025 Jul 11;104(28):e42975. doi: 10.1097/MD.0000000000042975.

ABSTRACT

With the aging population, the prevalence of sarcopenia and primary osteoporosis is increasing. However, the underlying mechanisms linking these 2 diseases remain unclear. The study aims to identify potential genes and pharmacological targets associated with both diseases through bioinformatics analysis. Datasets GSE35958 (primary osteoporosis) and GSE1428 (sarcopenia) were sourced from the gene expression omnibus database. Differentially expressed genes common to both conditions were identified, and functional roles were elucidated using gene ontology and Reactome pathway analyses. Protein-protein interaction networks and hub genes were analyzed using Cytoscape with the molecular complex detection plugin. Key gene expression profiles were validated by quantitative real-time PCR, and potential gene-drug interactions were explored using the drug-gene interaction database. The identified pharmacological agents contributed to the formulation of therapeutic strategies for both diseases. Our study identified 80 commonly expressed genes through the gene expression omnibus database. Gene ontology enrichment analysis was employed to categorize these genes into biological processes, cellular components, and molecular functions. Additionally, 6 Reactome pathways were identified (P < .05), leading to the characterization of 65 genes. The study conducted a protein-protein interaction analysis and employed molecular complex detection to evaluate a set of 65 genes, ultimately identifying 5 central genes. In this investigation, cancellous bone and muscle tissues from elderly individuals with osteoporosis and sarcopenia were subjected to quantitative real-time PCR validation. The analysis revealed that 5 genes were down-regulated in muscle tissue, whereas AXL, ERBB2, and GAB1 were up-regulated in bone tissue. Subsequently, these 5 genes were analyzed for drug-gene interactions, resulting in the identification of 13 Food and Drug Administration-approved drugs with potential therapeutic applications for osteoporosis and sarcopenia. The aforementioned 5 genes (AXL, GAB1, ERBB2, NRP2, and ESR1) along with 13 pharmacological agents represent promising candidates for enhancing the treatment of osteoporosis and sarcopenia. Investigations into gene-drug correlations and analyses of potential pharmacotherapies offer novel insights for drug repurposing and the exploration of therapeutic pathways.

PMID:40660573 | DOI:10.1097/MD.0000000000042975

Ageing Res Rev. 2025 Jul 12:102835. doi: 10.1016/j.arr.2025.102835. Online ahead of print.

ABSTRACT

Aging is a complex biological process driven by genetic and immune-mediated mechanisms, yet the causal roles of immune-cell-specific gene regulation remain unclear. In this study, we integrate single-cell expression quantitative trait loci (sc-eQTL) data with Mendelian randomization (MR) and colocalization analyses to identify immune-mediated regulatory mechanisms and therapeutic targets for aging. Using data from 14 immune cell types, we systematically evaluated 8,733 eGenes for causal effects on telomere length (TL), facial aging (FA), and frailty index (FI). We identified 27 immune-cell-specific eGenes with significant causal associations and strong colocalization evidence (posterior probability for a shared causal variant, PP.H4 > 50%). Key regulators include FUBP1, TUFM, ATIC, and SLC22A5, with distinct effects across cell types and aging traits. Phenome-wide association studies (PheWAS) demonstrated minimal off-target associations for most genes, supporting their safety as therapeutic targets. Drug repurposing analysis revealed several approved or investigational compounds, such as Irofulven, zinc-based agents, and acetylcarnitine, with potential for aging-related interventions. Our findings provide new insights into the immune-genetic architecture of aging and establish a scalable framework for identifying cell-type-specific causal genes and repurposable drug targets. This approach enhances precision medicine strategies aimed at promoting healthy aging and delaying age-related decline.

PMID:40659289 | DOI:10.1016/j.arr.2025.102835

Nano Lett. 2025 Jul 14. doi: 10.1021/acs.nanolett.5c02826. Online ahead of print.

ABSTRACT

Prostate cancer is the second leading cause of cancer-related deaths in men worldwide, with bone metastasis being the predominant driver of morbidity and mortality in advanced stages. This underscores the urgent need for innovative therapeutic strategies to address skeletal metastasis and improve patient outcomes. Niclosamide, a long-standing anthelminthic drug, has emerged as a promising multipathway modulator against cancer hallmarks. Here, we propose a nanotechnology-enabled repurposing of niclosamide, hypothesizing that its formulation into smart, targeted nanohybrids could not only suppress prostate tumor growth but also inhibit its dissemination to the skeletal system. We discuss the molecular rationale, design considerations, and translational outlook for nanoengineered niclosamide in the context of metastatic prostate cancer.

PMID:40657731 | DOI:10.1021/acs.nanolett.5c02826

Int J Med Sci. 2025 Jun 12;22(12):2896-2905. doi: 10.7150/ijms.111050. eCollection 2025.

ABSTRACT

Objective: Gangrene has been a problem for many people with diabetes. Besides, the relationship and pathomechanism of diabetes-induced gangrene (DG) are still unclear. The aim of this study was to investigate the causal relationship between diabetes and gangrene through Mendelian randomization (MR) and to identify potential therapeutic agents using bioinformatics analysis. Method: Summary data from genome-wide association studies (GWAS) were utilized to evaluate the connection between two types of diabetes and gangrene risk using a two-sample MR design. Single nucleotide polymorphisms (SNPs) that were significantly associated with diabetes were selected as instrumental variables, and their validity was verified by F-statistics and other methods. Next, we used text mining and protein-protein interaction (PPI) networks to filtrate significant genes for drug-gene interaction (DGI) to identify prospective medications for the therapy of DG. Results: Through multiple methods analysis (IVW, MR-Egger and MR-PRESSO etc.), MR analysis showed that genetic susceptibility to type 1 diabetes was related to a higher risk of gangrene risk (OR: 1.19, 95% CI: 1.04-1.36, P-value: 0.0134), while type 2 diabetes mellitus (T2DM) could also increase the gangrene risk (OR: 1.57, 95% CI: 1.05-2.33, P-value: 0.0269). The outcomes of text mining disclosed 50 genes enriched in NOD-like receptor and RAGE signaling pathways commonly associated with both diabetes and gangrene for PPI analysis. Subsequent DGI analysis revealed six genes targeted by 12 drugs (DGI score > 5), presenting them as candidates for treating DG. Conclusion: In conclusion, this study not only validates the causal effect of diabetes on gangrene risk but also identifies several potential therapeutic agents (CILAZAPRIL, RESATORVID, SILTUXIMAB, and OLOKIZUMAB) by integrating bioinformatics analysis, providing new directions for future clinical interventions.

PMID:40657379 | PMC:PMC12243868 | DOI:10.7150/ijms.111050

ACS Omega. 2025 Jun 26;10(26):28446-28465. doi: 10.1021/acsomega.5c04340. eCollection 2025 Jul 8.

ABSTRACT

ROCK kinases are key players in neurodegenerative diseases such as Alzheimer's disease (AD), making them attractive therapeutic targets. In this study, we developed a pharmacophoric map of ROCK inhibitors and highlighted the key affinity sites in ROCK1/2 through molecular modeling. Virtual screening led to the identification of six approved drugs as ROCK inhibitors: ruxolitinib (36), baricitinib (37), ponatinib (38), tivozanib (39), nialamide (40), and tucatinib (41). Ruxolitinib (36) (hROCK1 IC50 = 0.025 μM; hROCK2 IC50 = 0.007 μM) and baricitinib (37) (hROCK1 IC50 = 0.019 μM; hROCK2 IC50 = 0.011 μM) showed the highest potency, while tivozanib (39) displayed 15-fold selectivity for ROCK2 over ROCK1. Molecular dynamics revealed that ruxolitinib (36) forms stable bidentate hydrogen bonds with the ROCK hinge region and has selectivity across the AGC kinase family. Biological assays confirmed ruxolitinib's (36) safety in neuronal and glial cells and its ability to reduce C3 immunolabeling, a glial inflammation marker, in LPS-treated astrocytes. These findings not only highlight ruxolitinib (36) as a promising candidate for AD but also provide a structural basis for designing novel dual JAK-ROCK inhibitors and pave the way for further in vitro and in vivo studies. Moreover, the validated pharmacophoric map for ROCK inhibition highlights the identification of an affinity pocket that can be useful for the design of new ROCK inhibitors.

PMID:40657111 | PMC:PMC12242638 | DOI:10.1021/acsomega.5c04340

Indian J Microbiol. 2025 Jun;65(2):798-819. doi: 10.1007/s12088-024-01439-8. Epub 2025 Jan 7.

ABSTRACT

Pseudomonas aeruginosa is a major cause of nosocomial infection which at times causes a grim situation in clinical setups. There is a dire need to develop strategies to overcome the increasing incidence of drug resistance in this organism. The protective outer membrane and over expressed efflux pumps serve as a major survival weapon for this pathogen, making it to resist present day antibiotics. The present review dwells on some of these strategies, with emphasis on tagging to existing antibiotics with siderophore as a carrier employing a Trojan horse strategy so that an antibiotic can creep into bacterial cell through the iron acquisition pathway. These hybrid drugs, defined as synthetic structures are likely to overcome drug resistance due to their ability to evade resistance mediated by multiple antibiotic resistance operon. The advances and challenges of siderophore-antibiotic conjugates are elaborated in this article. Moreover, several xeno-siderophore-antibiotic conjugates, currently in clinical trials, have been discussed. The present review provides insights into repurposing of fluroquinolones through siderophore targeted delivery to increase the biological activity of antibiotics. In the near future, siderophore-based Trojan horse antibiotics indeed will not only help in altering the potency of antibiotics, hence decreasing antimicrobial resistance, but also will lead to disarming the pathogen of its virulence.

PMID:40655352 | PMC:PMC12246312 | DOI:10.1007/s12088-024-01439-8

J Transl Med. 2025 Jul 13;23(1):788. doi: 10.1186/s12967-025-06739-1.

ABSTRACT

BACKGROUND: Analyzing disease-linked genetic variants via expression quantitative trait loci (eQTLs) helps identify potential disease-causing genes. Previous research prioritized genes by integrating Genome-Wide Association Study (GWAS) results with tissue-level eQTLs. Recent studies have explored brain cell type-specific eQTLs, but a systematic analysis across multiple Alzheimer's disease (AD) genome-wide association study (GWAS) datasets or comparisons between tissue-level and cell type-specific effects remain limited. Here, we integrated brain cell type-level and bulk-level eQTL datasets with AD GWAS datasets to identify potential causal genes.

METHODS: We used Summary Data-Based Mendelian Randomization (SMR) and Bayesian Colocalization (COLOC) to integrate AD GWAS summary statistics with eQTLs datasets. Combining data from five AD GWAS, two single-cell eQTL datasets, and one bulk eQTL dataset, we identified novel candidate causal genes and further confirmed known ones. We investigated gene regulation through enhancer activity using H3K27ac and ATAC-seq data, performed protein-protein interaction (PPI) and pathway enrichment, and conducted a drug/compound enrichment analysis with Drug Signatures Database (DSigDB) to support drug repurposing for AD.

RESULTS: We identified 28 candidate causal genes for AD, of which 12 were uniquely detected at the cell-type level, 9 were exclusive to the bulk level and 7 detected in both. Among the 19 cell-type level candidate causal genes, microglia contributed the highest number of candidate genes, followed by excitatory neurons, astrocytes, inhibitory neurons, oligodendrocytes, and oligodendrocyte precursor cells (OPCs). PABPC1 emerged as a novel candidate causal gene in astrocytes. We generated PPI networks for the candidate causal genes and found that pathways such as membrane organization, cell migration, and ERK1/2 and PI3K/AKT signaling were enriched. The AD-risk variant associated with candidate causal gene PABPC1 is located near or within enhancers only active in astrocytes. We classified the 28 genes into three drug tiers and identified druggable interactions, with imatinib mesylate emerging as a key candidate. A drug-target gene network was created to explore potential drug targets for AD.

CONCLUSIONS: We systematically prioritized AD candidate causal genes based on cell type-level and bulk level molecular evidence. The integrative approach enhances our understanding of molecular mechanisms of AD-related genetic variants and facilitates interpretation of AD GWAS results.

PMID:40653482 | DOI:10.1186/s12967-025-06739-1

Bioorg Med Chem Lett. 2025 Jul 11:130330. doi: 10.1016/j.bmcl.2025.130330. Online ahead of print.

ABSTRACT

Mpox, a viral illness caused by the monkeypox virus (MPXV), has gained global attention due to its outbreaks worldwide in recent years. MPXV infections pose significant public health threats with notable transmission risks, yet specific antiviral treatments remain limited. Current therapeutic approaches primarily rely on smallpox vaccines and a limited number of broad-spectrum antiviral agents, such as tecovirimat, lacking specific drugs against MPXV. Thus, it remains a significant clinical need to develop anti-MPXV agents for the prevention and control of mpox outbreaks. In this review, we summarized the characteristics of MPXV in terms of viral structure, genome, and replication while reporting the recent progress in the development of small molecule anti-MPXV agents. Additionally, we discussed major obstacles in anti-MPXV drug development, including insufficient understanding of virus biology, the lack of reliable disease models, and limited resources for conducting large-scale clinical evaluations, and provided insights and perspectives for anti-MPXV therapies, with the aims of accelerating the development of effective treatments and contributing to preparedness against emerging orthopoxvirus threats.

PMID:40652991 | DOI:10.1016/j.bmcl.2025.130330

Trends Immunol. 2025 Jul 11:S1471-4906(25)00169-3. doi: 10.1016/j.it.2025.07.002. Online ahead of print.

ABSTRACT

Pharmacological activation of the stimulator of interferon genes (STING) pathway triggers inflammatory innate immune responses to potentially reinvigorate tumor immunogenicity. Recent work by Dang et al. revealed an alternative paradigm: a clinically approved old drug was repurposed to boost STING signaling and immune activation via a mode of action distinct from that of conventional STING agonists.

PMID:40651881 | DOI:10.1016/j.it.2025.07.002

Int J Pharm. 2025 Jul 10:125935. doi: 10.1016/j.ijpharm.2025.125935. Online ahead of print.

ABSTRACT

Treatment of glioblastoma (GBM) presents significant challenges due to its high degree of heterogeneity and poor prognosis. Recurrence of the malignancy is frequent even after the standard treatment, including surgery, radiotherapy, and chemotherapy with temozolomide. Drug repurposing offers a cost-effective strategy to identify new treatments, while affinity-based local delivery systems could provide controlled release of therapeutics within the tumor resection cavity. The aims of this study are two-fold. Firstly, to categorize currently available neurological therapeutics according to their charge and suitability for use with affinity-based drug delivery systems. Secondly, to systematically search and evaluate the evidence for anticancer and/or anti-glioblastoma activity for potentially being repurposed/repositioned. The 'neurology/psychiatry' category of the Broad Institute Drug Repurposing Hub (468 compounds) was screened for chemical suitability and anticancer efficacy. Charge, lipophilicity, solubility at pH 7.4 were calculated using Chemicalize. A systematic search for the anticancer efficacy of the charged compounds was carried out via the following databases: PubMed, Scopus, Sci-Finder, Ovid via Medline, Cochrane and ClinicalTrial.gov. Among the 468 compounds, 283 were identified as charged at physiological pH. Notably, 146 charged candidates were found to have anticancer activity, of which 91 showed promising activity against at least one type of brain neoplasm. A few compounds, such as chlorpromazine, valproic acid and sertraline were investigated in clinical settings, while most were assessed through in vitro viability studies. The data complied herein should serve as a repository and starting point for future research on repurposing neurological drugs with anticancer properties via electrostatic affinity-based drug delivery systems.

PMID:40651674 | DOI:10.1016/j.ijpharm.2025.125935

Expert Opin Drug Discov. 2025 Jul 12:1-14. doi: 10.1080/17460441.2025.2530589. Online ahead of print.

ABSTRACT

INTRODUCTION: Leishmaniasis is a devastating and complex parasitic disease caused by different species of protozoan members of the genus Leishmania. Unfortunately, available drugs are far from ideal and no vaccines are available. Under these circumstances, new effective antileishmanial drugs with reduced host toxicity and improved dosing protocols are urgently needed. The sterol biosynthesis pathway (SBP) is a promising focus for combating Leishmania infections. Thus, various strategies have been documented, such as drug repurposing, combined therapy, rational drug design, and the use of synergistic effects to develop the metallodrugs that can act on essential parasite targets.

AREAS COVERED: This article reviews the critical enzymes participating in the ergostane-based sterol biosynthesis pathway (SBP) of Leishmania species, as well as recent progress in rational drug design, repurposing drugs, combined therapies, and the development of metallodrugs for use as antileishmanial agents. This review is based on literature searchers using SciFinder, Lens.org, Google Scholar, Web of Science, Pub Med, and DrugBank.

EXPERT OPINION: The limited focus on human leishmaniasis has resulted in a shortfall in effective treatments for this parasitic disease. The post-squalene segment of the sterol biosynthetic pathway is a promising target for treating Leishmania infections, particularly effective drugs or metallodrugs that inhibit the CYP51 or 24-SMT enzymes.

PMID:40650542 | DOI:10.1080/17460441.2025.2530589

Int J Mol Sci. 2025 Jul 7;26(13):6539. doi: 10.3390/ijms26136539.

ABSTRACT

Adrenocortical carcinoma (ACC) is an aggressive cancer with a poor prognosis. Mitotane, the only FDA-approved treatment for ACC, targets adrenocortical cells and reduces cortisol levels. Although it remains the cornerstone of systemic therapy, its overall impact on long-term outcomes is still a matter of ongoing clinical debate. Drug repurposing is a cost-effective way to identify new therapies, and defactinib, currently in clinical trials as part of combination therapies for various solid tumours, may enhance ACC treatment. We aimed to assess its efficacy in combination with mitotane. We tested the combination of mitotane and defactinib in H295R, SW13, and mitotane-sensitive and -resistant HAC15 cells, using functional assays, transcriptomic profiling, 2D and 3D cultures, bioprinted tissues, and xenografts. We assessed drug interactions with NMR and toxicity in vivo, as mitotane and defactinib have never been previously administered together. Genomic data from 228 human ACC and 158 normal adrenal samples were also analysed. Transcriptomic analysis revealed dysregulation of focal adhesion along with mitotane-related pathways. Focal adhesion kinase (FAK) signalling was enhanced in ACC compared to normal adrenal glands, with PTK2 (encoding FAK) upregulated in 44% of tumour samples due to copy number alterations. High FAK signature scores correlated with worse survival outcomes. FAK inhibition by defactinib, both alone and in combination with mitotane, showed effective anti-tumour activity in vitro. No toxicity or drug-drug interactions were observed in vivo. Combination treatment significantly reduced tumour volume and the number of macrometastases compared to those in the mitotane and control groups, with defactinib-treated tumours showing increased necrosis in xenografts. Defactinib combined with conventionally used mitotane shows promise as a novel combination therapy for ACC and warrants further investigation.

PMID:40650315 | DOI:10.3390/ijms26136539

Int J Mol Sci. 2025 Jun 27;26(13):6201. doi: 10.3390/ijms26136201.

ABSTRACT

Coronary atherosclerosis (CAS) is a major cause of cardiovascular morbidity worldwide. The understanding of atherosclerosis has shifted from a cholesterol deposition disorder to an inflammation-driven disease, with anti-inflammatory therapies demonstrating clinical efficacy. Identifying inflammatory protein targets is crucial for developing targeted therapies. A proteome-wide Mendelian randomization (MR) analysis was performed to explore therapeutic targets for CAS by integrating inflammatory proteomics data from the UK-PPP (54,219 participants, 2923 proteins) and Iceland cohorts (35,559 participants, 4907 proteins) as exposures and outcome data for CAS, atherosclerosis, and carotid atherosclerosis from FinnGen. Replication MR employed meta-analysis of six proteomics datasets and CAS data from three sources, while the impact of the identified proteins on four cardiovascular diseases was also investigated. Colocalization analysis (PPH4 > 0.9), reverse MR, and SMR were used to ensure robust causal inference. Proteome-wide MR identified 11 proteins significantly associated with CAS (p < 3.52 × 10-5), with all but CD4 linked to cardiovascular disease risk. Notably, colocalization confirmed the causal roles of PCSK9, IL6R, CELSR2, FN1, and SPARCL1 in CAS, and single-cell RNA-seq analysis revealed that five genes (TGFB1, SPARCL1, IL6R, FN1, and CELSR2) were exclusively expressed in smooth muscle cells of either coronary plaques or healthy vasculature. Druggability assessments were subsequently conducted for these targets. The three most promising targets (CELSR2, FN1, and SPARCL1), along with the other identified proteins and their biological functions, exhibit robust causal associations with CAS. FN1 and TGFB1 have the potential for drug repurposing in atherosclerosis treatment.

PMID:40649979 | DOI:10.3390/ijms26136201