Transl Psychiatry. 2025 Jun 20;15(1):207. doi: 10.1038/s41398-025-03418-z.

ABSTRACT

Serum lipid levels, which are influenced by both genetic and environmental factors, are key determinants of cardiometabolic health and are influenced by both genetic and environmental factors. Improving our understanding of their underlying biological mechanisms can have important public health and therapeutic implications. Although psychosocial factors, including depression, anxiety, and perceived social support, are associated with serum lipid levels, it is unknown if they modify the effect of genetic loci that influence lipids. We conducted a genome-wide gene-by-psychosocial factor interaction (G×Psy) study in up to 133,157 individuals to evaluate if G×Psy influences serum lipid levels. We conducted a two-stage meta-analysis of G×Psy using both a one-degree of freedom (1df) interaction test and a joint 2df test of the main and interaction effects. In Stage 1, we performed G×Psy analyses on up to 77,413 individuals and promising associations (P < 10-5) were evaluated in up to 55,744 independent samples in Stage 2. Significant findings (P < 5 × 10-8) were identified based on meta-analyses of the two stages. There were 10,230 variants from 120 loci significantly associated with serum lipids. We identified novel associations for variants in four loci using the 1df test of interaction, and five additional loci using the 2df joint test that were independent of known lipid loci. Of these 9 loci, 7 could not have been detected without modeling the interaction as there was no evidence of association in a standard GWAS model. The genetic diversity of included samples was key in identifying these novel loci: four of the lead variants displayed very low frequency in European ancestry populations. Functional annotation highlighted promising loci for further experimental follow-up, particularly rs73597733 (MACROD2), rs59808825 (GRAMD1B), and rs11702544 (RRP1B). Notably, one of the genes in identified loci (RRP1B) was found to be a target of the approved drug Atenolol suggesting potential for drug repurposing. Overall, our findings suggest that taking interaction between genetic variants and psychosocial factors into account and including genetically diverse populations can lead to novel discoveries for serum lipids.

PMID:40537477 | DOI:10.1038/s41398-025-03418-z

J Cancer. 2025 Jun 12;16(8):2690-2705. doi: 10.7150/jca.110850. eCollection 2025.

ABSTRACT

Background: Antihypertensive drugs represent the most widely used drugs worldwide. However, the association between antihypertensive drugs and the risk of kidney cancer remains unclear. This study innovatively integrates multi-omics and causal inference approaches to investigate the long-term effects and potential mechanisms of 12 antihypertensive drug classes on kidney cancer risk. Methods: In this study, novel approaches including two-sample mendelian randomization (MR), summary-data-based mendelian randomization (SMR), two-step network MR, and single-cell transcriptomic analysis were employed. Single nucleotide polymorphisms (SNPs) were obtained from genome-wide association studies (GWASs) to proxy exposures and outcomes. The cis-expression quantitative trait loci (cis-eQTL) as the proxies of exposure were also obtained. MR estimates were generated using the inverse-variance weighted method or Wald ratio method. Sensitivity analyses were undertaken to interrogate the robustness of the main findings. Two-step network MR and single-cell analysis were specifically designed to dissect pathway-level mediation and expression patterns of identified targets. Results: In the main analysis, genetically proxied calcium-channel blockers (odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.91-0.99, p=0.021) and vasodilator antihypertensives (OR: 0.86, 95% CI: 0.76-0.97, p=0.018) were suggestively associated with decreased risk of kidney cancer, whereas genetically proxied angiotensin-converting enzyme inhibitors (OR: 1.13, 95% CI: 1.00-1.27, p=0.043) was suggestively associated with increased risk of kidney cancer. Genetically proxied antiadrenergic agents (OR=0.94, 95% CI: 0.90-0.99, p=0.021) and centrally acting antihypertensives (OR=0.93, 95% CI: 0.88-0.98, p=0.010) were suggestively associated with a decreased risk of clear cell renal cell carcinoma. SMR analysis revealed that these suggestively significant associations might be driven by CACNA1C, CALM1, ACE, and LTA4H. Upon two-step network MR analyses, 10 pathways with directional consistency were identified, and the mediation proportion ranged from 3.22% to 7.12%. The influence of antihypertensive drugs on kidney cancer risk might be associated with their regulation of levels of blood cells and lipids. Single-cell analysis further revealed the expression patterns of the four identified targets in peripheral blood and tumor infiltrating immune cells. Conclusion: This study pioneers the integration of causal inference and single-cell omics to demonstrate that antihypertensive drugs modulate kidney cancer risk through target-specific mechanisms involving blood cell and lipid pathways. Our findings provide actionable targets (CACNA1C, CALM1, ACE, and LTA4H) for drug repurposing trials and underscore the clinical importance of personalized antihypertensive therapy in cancer prevention.

PMID:40535814 | PMC:PMC12170992 | DOI:10.7150/jca.110850

Front Immunol. 2025 Jun 4;16:1575490. doi: 10.3389/fimmu.2025.1575490. eCollection 2025.

ABSTRACT

BACKGROUND: Autoimmune and autoinflammatory diseases (AIIDs) are characterized by significant heterogeneity and comorbidities, complicating their mechanisms and classification. Disease associations studies, or diseasome, facilitate the exploration of disease mechanisms and development of novel therapeutic strategies. However, the diseasome for AIIDs is still in its infancy. To address this gap, we developed a novel framework that utilizes multi-modal data and biomedical ontologies to explore AIID associations.

METHODS: We curated disease terms from Mondo/DO/MeSH/ICD, and three specialized AIID knowledge bases, creating an integrated repository of 484 autoimmune diseases (ADs), 110 autoinflammatory diseases (AIDs), and 284 associated diseases. By leveraging genetic, transcriptomic (bulk and single-cell), and phenotypic data, we built multi-layered AIID association networks and an integrated network supported by cross-scale evidence. Our ontology-aware disease similarity (OADS) strategy incorporates not only multi-modal data, but also continuous biomedical ontologies.

RESULTS: Network modularity analysis identified 10 robust disease communities and their representative phenotypes and dysfunctional pathways. Focusing on 10 highly concerning AIIDs, such as Behçet's disease and Systemic lupus erythematosus, we provide insights into the information flow from genetic susceptibilities to transcriptional dysregulation, alteration in immune microenvironment, and clinical phenotypes, and thus the mechanisms underlying comorbidity. For instance, in systemic sclerosis and psoriasis, dysregulated genes like CCL2 and CCR7 contribute to fibroblast activation and the infiltration of CD4+ T and NK cells through IL-17 signaling pathway, PPAR signaling pathway, leading to skin involvement and arthritis.

CONCLUSION: These findings enhance our understanding of AIID pathogenesis, improving disease classification and supporting drug repurposing and targeted therapy development.

PMID:40534874 | PMC:PMC12174166 | DOI:10.3389/fimmu.2025.1575490

Biomed Pharmacother. 2025 Jun 17;189:118261. doi: 10.1016/j.biopha.2025.118261. Online ahead of print.

ABSTRACT

Fluoroquinolones (FQs), potent antimicrobials, have shown potential in curbing cancer invasion and metastasis by affecting cell migration and extracellular matrix reshaping. However, the molecular mechanisms behind their impact remain unclear. The type III TGF-β receptor (TβR3, also called betaglycan), a co-receptor in the TGF-β superfamily, is often found to be downregulated in various human cancers. This receptor plays a crucial role in suppressing cancer progression and metastasis, independent of TGF-β signaling. In this study, we investigated the effects of ciprofloxacin (a member of FQs) on TβR3 production in cancer cells and their subsequent impact on cancer cell migration and invasion. Our results demonstrated that ciprofloxacin and other FQs dose-dependently elevated TβR3 levels, which was associated with reduced cell migration and invasion. Gene silencing and pharmacological approaches confirmed that exchange protein directly activated by cAMP (Epac) and JNK/AP1 pathways are critical for FQ-induced TβR3 expression. In vivo studies showed that mice receiving clinically relevant doses of ciprofloxacin exhibited elevated TβR3 levels in the liver and lung, which were associated with inhibited tumor progression. Furthermore, histological analysis of human non-small cell lung cancer (NSCLC) tissues revealed that metastatic lung cancers had lower TβR3 protein expression compared to matched normal lung tissues. Overall; our findings indicate that cancer invasion and malignancy are associated with reduced TβR3 levels, and that FQs can inhibit cancer cell migration and invasion by upregulating TβR3 expression. These results elucidate the potential for repositioning FQs as a supplemental therapeutic strategy in cancer treatment.

PMID:40532572 | DOI:10.1016/j.biopha.2025.118261

Front Pharmacol. 2025 Jun 3;16:1566622. doi: 10.3389/fphar.2025.1566622. eCollection 2025.

ABSTRACT

BACKGROUND: Currently, there is a paucity of clinically effective medications for the treatment of diabetic cardiomyopathy (DCM), while the strategy of drug repurposing offers a promising avenue for advancing therapeutic development.

METHODS: The investigation explored the ameliorative effects and uncovered underlying mechanisms of trapidil (TRA), a drug commonly employed in the management of coronary heart disease, on DCM by inhibiting myocardial pyroptosis. Type 1 DCM models were established utilizing C57BL/6 mice and primary neonatal mouse cardiomyocytes (NMCMs), which were subsequently treated with TRA.

RESULTS: Results demonstrated that in DCM mice, TRA significantly enhanced cardiac function, effectively alleviated pathological changes in myocardial tissue, reversed ultrastructural alterations, and reduced pyroptosome formation in myocardial cells. TRA significantly increased the body weight of the mice in the DCM model group, whereas there was no significant alteration in blood glucose levels following TRA treatment. In the myocardial tissue of DCM mice and high-glucose (HG)-treated NMCMs, TRA was found to correct the aberrant expression of key proteins involved in pyroptosis, including cleaved-caspase1, NLRP3, phospho-NF-κB cyclooxygenase-2, interleukin Cleaved-IL-1β, Cleaved-IL-18, and gasdermin D. Furthermore, TRA effectively curtailed the excessive production of ROS and augmented the mitochondrial membrane potential in NMCMs under the HG environment. Proteomics analysis identified 90 differentially expressed proteins between DCM mice and TRA-treated mice, with glutathione peroxidase 3 (GPX3) emerging as a standout due to its critical role in the cellular antioxidant defense system. Further investigations revealed that the protein and mRNA levels of GPX3, as well as the activated Nrf2 protein levels, were significantly downregulated in the myocardial tissue of DCM mice and HG-treated NMCMs cells. However, these levels were notably upregulated following TRA treatment. Upon knocking down GPX3 mRNA expression using siRNA technology, the anti-pyroptotic effect of TRA in cardiomyocytes was markedly diminished, and the level of activated Nrf2 protein also significantly decreased.

CONCLUSION: In conclusion, TRA holds potential for improving DCM, with the inhibition of myocardial pyroptosis via the GPX3/Nrf2 pathway playing a pivotal role. HG-induced Downregulation of the GPX3/Nrf2 pathway is a critical mechanism underlying pyroptosis in DCM. This pathway can be targeted for the design of DCM-related therapeutics, utilizing the aforementioned signaling mechanisms.

PMID:40529489 | PMC:PMC12170559 | DOI:10.3389/fphar.2025.1566622

Biomed Pharmacother. 2025 Jun 16;189:118272. doi: 10.1016/j.biopha.2025.118272. Online ahead of print.

ABSTRACT

Oxaliplatin (L-OHP) is a platinum-based anticancer drug used to treat various malignant tumors. However, L-OHP-induced peripheral neuropathy (OIPN) is a major clinical problem that often limits treatment. As OIPN occurs when L-OHP accumulates in the dorsal root ganglion (DRG) via organic cation transporter 2 (OCT2/SLC22A2), drugs with OCT2 inhibitory properties may serve as prophylactic agents for OIPN. This study aimed to explore the potential prophylactic agents for OIPN using integrated model with the quantitative structure-activity relationship screening for human organic cation transporter 2 (hOCT2) inhibitors and two real-world data analyses of the Food and Drug Administration Adverse Event Reporting System and Japanese Adverse Drug Event Report, and subsequently evaluate the protective effects of the identified drugs against OIPN. Our integrated model identified lansoprazole, a proton pump inhibitor, as a potential prophylactic agent. In vitro uptake study using hOCT2-expressing HEK293 cells demonstrated that lansoprazole significantly inhibited the hOCT2-mediated transport of L-OHP. In the OIPN mouse model, concomitant lansoprazole drastically suppressed mechanical allodynia and cold hypersensitivity after repeated L-OHP administration. Moreover, the concentration of L-OHP in the DRG was significantly decreased by the concomitant administration of lansoprazole. In primary cultured mouse DRG neurons, cotreatment with lansoprazole significantly inhibited L-OHP uptake and restored the L-OHP-induced decrease in neurite length. These findings suggest that the concomitant administration of lansoprazole ameliorates OIPN by inhibiting OCT2-mediated L-OHP uptake in the mouse DRG. Our findings provide important insights for the establishment of novel protective approaches against OIPN.

PMID:40527038 | DOI:10.1016/j.biopha.2025.118272

Biomed Pharmacother. 2025 Jun 16;189:118241. doi: 10.1016/j.biopha.2025.118241. Online ahead of print.

ABSTRACT

Triple Negative Breast Cancer (TNBC) is the most aggressive subtype of breast cancer, marked by intrinsic and acquired chemoresistance and a lack of response to endocrine therapy and chemotherapy. This necessitates the development of novel, safe, and cost-effective treatment strategies. Recent advances include small molecules, drug repositioning, dual-targeting agents, combinatorial therapies, and splicing inhibitors. Comprehensive molecular profiling, including transcriptomic comparisons between primary and secondary tumors, is crucial for identifying chemoresistance mechanisms and revealing therapeutic vulnerabilities. ceRNA networks (lncRNA-miRNA-mRNA) provide insights into tumorigenesis and progression, facilitating the identification of subtype-specific biomarkers in the heterogeneous landscape of TNBC. lncRNAs, with their complex structure and tissue-specific expression, are promising both as biomarkers and therapeutic targets. Liquid biopsies and next-generation sequencing are paving the way for personalized lncRNA-based treatments by enabling real-time monitoring of tumor heterogeneity and therapeutic response. While miRNA-mRNA interactions have been extensively studied, the involvement of lncRNA within the ceRNA network remains poorly understood. Elucidating these interactions and their modulation by small molecules may lead to more effective, personalized treatment strategies for TNBC. This review examines long non-coding RNA (lncRNA)- associated competing endogenous RNA (ceRNA) networks, their therapeutic potential, and their application as predictive biomarkers in triple-negative breast cancer (TNBC).

PMID:40527037 | DOI:10.1016/j.biopha.2025.118241

Mamm Genome. 2025 Jun 16. doi: 10.1007/s00335-025-10146-8. Online ahead of print.

ABSTRACT

Cholestasis, characterized by impaired bile flow, leads to significant hepatic dysfunction and poses a clinical challenge. This study investigated cellular communication networks and molecular mechanisms underlying cholestasis using advanced single-cell and transcriptomic sequencing. Data from the GEO database, including single-cell sequencing (GSE237622) and transcriptome datasets (GSE206364, GSE183754), were analyzed to identify biomarkers and therapeutic targets. Lasso regression highlighted IL32, CRIP2, ANXA2, and VWF as key genes, supported by immune infiltration, functional enrichment, and drug repurposing analysis via the Connectivity Map (CMap) database. Expression of these genes was validated in liver tissue from 13 cholestatic liver disease (CLD) patients and 10 controls. Single-cell sequencing identified 534 cell-type-specific markers, with significant upregulation of IL32, CRIP2, ANXA2, and VWF in CLD patients, particularly in endothelial cells near liver sinusoids and periportal areas. Their expression correlated with serum ALT and AST levels, reflecting disease severity. Drug repurposing analysis identified dexamethasone, fenofibrate, promazine, and SB-590,885 as potential therapies. This study identifies IL32, CRIP2, ANXA2, and VWF as pivotal biomarkers and therapeutic targets for cholestasis, offering new avenues for targeted interventions.

PMID:40523982 | DOI:10.1007/s00335-025-10146-8

Cell Death Dis. 2025 Jun 17;16(1):452. doi: 10.1038/s41419-025-07770-2.

ABSTRACT

Non-small cell lung cancer (NSCLC) is highly malignant with limited treatment options, largely due to the inherent tumoral heterogeneity and acquired resistance towards chemotherapy and immunotherapy. RG7388, a known MDM2 inhibitor, exhibited anticancer activity in TP53-wild-type (TP53WT) NSCLC by triggering the p53/PUMA axis-dependent apoptosis. However, our study uncovered previously unrecognized p53-independent anticancer effects of RG7388 in TP53-mutant (TP53mutant) NSCLC, although the underlying mechanisms remained elusive. Here, we demonstrated that RG7388 specifically induced the NOXA/caspase-3 axis-dependent apoptosis and gasdermin E (GSDME)-mediated secondary pyroptosis in TP53mutant NSCLC, as validated through in silico analyses and multiple biological assays. Mechanically, we identified reactive oxygen species (ROS) as the critical mediator in NOXA upregulation and p38 MAPK pathway activation in RG7388 treated TP53mutant NSCLC. This was further supported by the use of ROS scavengers, N-acetylcysteine (NAC), and Ferrostatin-1 (Fer-1), which attenuated these effects. Pharmacologic inhibition of p38 MAPK signaling by SB203580 rescued RG7388-induced ROS-dependent NOXA accumulation and subsequent apoptosis and pyroptosis, highlighting the central role of the ROS/phosphorylated p38 MAPK (p-p38)/NOXA/caspase-3 axis in RG7388-induced TP53mutant NSCLC cell death. Our findings revealed a novel mechanism for selectively targeting mutant p53-derived cancer through ROS/p-p38-mediated NOXA accumulation, offering potential therapeutic implications given the current lack of direct mutant p53 targeting strategies in cancer. Furthermore, immunohistochemical (IHC) analysis of an NSCLC tissue microarray confirmed a strong positive correlation between p-p38 and NOXA expression. Clinical data analysis further suggested that the p-p38/NOXA axis might be a potential prognostic biomarker for overall survival (OS) in NSCLC patients.

PMID:40523886 | DOI:10.1038/s41419-025-07770-2

PLoS One. 2025 Jun 16;20(6):e0325700. doi: 10.1371/journal.pone.0325700. eCollection 2025.

ABSTRACT

BACKGROUND: Digestive system cancers, including esophageal, gastric, colorectal, pancreatic, hepatocellular, and biliary tract cancers, constitute a major global health challenge. Despite therapeutic advancements, prognosis remains poor, highlighting the urgent need for novel treatment strategies. We hypothesized that drug repositioning, facilitated by pan-cancer analyses, could lead to the identification of effective treatment strategies for these cancers.

RESULTS: We performed a comprehensive gene expression profiling of six major digestive system cancer types using The Cancer Genome Atlas data. Through integrative omics analysis, we identified 9,978 shared differentially expressed genes (DEGs) between colorectal cancer (CRC) and liver hepatocellular carcinoma (LIHC). Functional enrichment analysis revealed nine common Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, with Cell Cycle being a significant shared pathway. Protein-protein interaction (PPI) network analysis identified core genes within these pathways, including CCNE1, CHEK1, NXF1, NCBP2, and RPS27A. A Connectivity Map (CMap) analysis matched 1,147 small molecules, leading to the identification of Amonafide and BX795 as top candidates. These two drugs were validated and shown to inhibit the proliferation and migration of CRC (HT-29) and LIHC (HepG2) cells and induce cell cycle arrest and apoptosis.

CONCLUSION: Our study demonstrates the utility of drug repositioning for identifying potential therapeutics for digestive system cancers. Amonafide and BX795 emerged as promising candidates in targeting both CRC and LIHC. Further in vivo studies and clinical trials are warranted to validate these findings.

PMID:40522954 | DOI:10.1371/journal.pone.0325700

Mol Divers. 2025 Jun 16. doi: 10.1007/s11030-025-11241-3. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge in modern medicine, characterized by its insidious progression, early systemic metastasis, and alarmingly low survival rates. Given its clinical challenges, improving detection strategies for PDAC remains a critical area of research. This study has used advanced computational approaches to predict pancreatic adenocarcinoma-associated target genes using transcriptomics datasets. Predictive machine learning models were trained using the identified gene signatures, highlighting their potential relevance for future research into diagnostic strategies for PDAC. A total of thirteen differentially expressed genes (DEGs) associated with PDAC were identified, of which twelve were upregulated (CEACAM5, CEACAM6, CTSE, GALNT5, LAMB3, LAMC2, SLC6A14, TMPRSS4, TSPAN1, ITGA2, ITGB6, and POSTN) and one was down regulated (IAPP). These DEGs are all linked to cancer-associated pathways and potentially play a role in the growth and development of cancer. Furthermore, virtual screening evaluated the upregulated SLC6A14 gene-encoded protein for therapeutic repurposing, revealing promising candidates for PDAC treatment. This study offers exploratory insights into gene expression patterns and molecular biomarkers that may inform future research to improve PDAC prognosis and therapeutic development and provide the repurposed drug candidate for further exploration.

PMID:40522604 | DOI:10.1007/s11030-025-11241-3

Toxicol Appl Pharmacol. 2025 Jun 13:117441. doi: 10.1016/j.taap.2025.117441. Online ahead of print.

ABSTRACT

UDP-glucuronosyltransferases (UGTs) catalyze a major detoxification route for xenobiotics, yet chemical tools that modulate their activity are virtually absent and the possibility of allosteric regulation is largely unexplored. We combined ligand-based target prediction, structure-based docking, long-timescale molecular dynamics and MM/PBSA free-energy calculations to search the pharmacopeia for hidden UGT modulators. Six FDA-approved allosteric drugs were screened against the catalytic domains of UGT1A1, 1A9, 2B7 and 2B15. Docking and 200-ns simulations revealed a previously unrecognized cryptic pocket ~10 Å from the catalytic histidine that stably accommodated all six ligands; ivacaftor and cinacalcet produced the deepest free-energy basins and the most favorable MM/PBSA binding energies (-35.5 and - 31.2 kcal mol-1, respectively). FEL analysis showed that ligand binding funnels the enzyme's conformational ensemble into a single deep basin, providing a dynamic explanation for the Vmax depression observed in vitro. In recombinant enzymes and pooled human-liver microsomes these two compounds inhibited glucuronidation with low-micromolar potency (IC₅₀ ≈ 3-4 μM) while the remaining drugs were an order of magnitude weaker, mirroring the computational ranking. Lineweaver-Burk and Michaelis-Menten analyses showed pure non-competitive behavior, confirming that pocket occupancy depresses Vmax without altering Km. The strong correlation between calculated ΔGbind and experimental pIC₅₀ (ρ = 0.89) validates the predictive pipeline. Pharmacokinetic modelling suggests that clinically relevant concentrations of ivacaftor and cinacalcet may modulate UGT1A9- and UGT1A1-mediated clearance, revealing a previously unrecognized drug-drug-interaction risk. Altogether, the work delivers the small-molecule allosteric probes for UGTs, establishes a general workflow for mining existing drugs as phase-II enzyme modulators, and provides a structural framework for developing isoform-selective UGT therapeutics.

PMID:40518052 | DOI:10.1016/j.taap.2025.117441

Bioorg Chem. 2025 Jun 11;163:108680. doi: 10.1016/j.bioorg.2025.108680. Online ahead of print.

ABSTRACT

Nerve growth factor receptor Trk-A is essential for neurons' survival, growth, and function. The mutations in its gene can cause a disorder called CIPA, which requires the inhibition of Trk-A for preventing CIPA. Reported inhibitors of Trk-A exhibited challenges related to specificity and selectivity. This study used an integrated deep learning and structure-based drug repurposing approach to identify novel, potent, and non-toxic Trk-A inhibitors. Deep learning-based artificial neural network (ANN) models were trained and tested based on Trk-A targeting compounds' already existing bioactivity data. The trained ANN models were assessed for their performance, and a reliable model was employed to screen highly potent compounds from the FDA-approved drugs library. The screened drugs were further evaluated using molecular docking and identified gonadoliberin, caerulein, anidulafungin, and micafungin as potential Trk-A inhibitors. Molecular simulation analysis, including RMSD, RMSF, Rg, H-bonds, PCA, and MMGBSA/MMPBSA, further confirmed the stability of the selected drugs with Trk-A.

PMID:40517591 | DOI:10.1016/j.bioorg.2025.108680

NPJ Parkinsons Dis. 2025 Jun 13;11(1):167. doi: 10.1038/s41531-025-01027-7.

ABSTRACT

Parkinson's disease (PD) is a devastating neurodegenerative disorder with growing prevalence worldwide and, as yet, no effective treatment. Drug repurposing is invaluable for detecting novel PD therapeutics. Here, we compiled gene expression data from 1231 healthy human brain samples and 357 samples across tissues, ethnicities, brain regions, Braak stages, and disease status. By integrating them with multiple-source genomic data, we found a PD-associated gene co-expression module, and its alignment with the CMAP database successfully identified drug candidates. Among these, meclofenoxate hydrochloride (MH) and sodium phenylbutyrate (SP) are indicated to be able to prevent mitochondrial destruction, reduce lipid peroxidation, and protect dopamine synthesis. MH was validated to prevent neuronal death and synaptic damage, improve motor function, and reduce anhedonic and depressive-like behaviors of PD mice. The interaction of MH with a PD-related protein, sigma1, was confirmed experimentally. Thus, our findings support that MH potentially ameliorates PD by interacting with sigma1.

PMID:40514362 | DOI:10.1038/s41531-025-01027-7

Curr Neuropharmacol. 2025 Jun 10. doi: 10.2174/011570159X368382250527073353. Online ahead of print.

ABSTRACT

BACKGROUND: The growing prevalence of neuropsychiatric disorders is becoming a major health challenge. Traditional pharmacotherapies face limitations, making drug repurposing a valuable strategy. However, high-throughput screening approaches for these conditions are scarce.

METHODS: This study leveraged exposure data from the UK Biobank Neale Lab (N = 361,141) and outcome data from the FinnGen database (N = approximately 410,000) to employ Mendelian Randomization (MR) analyses and identify potential drug repurposing candidates for neuropsychiatric disorders. Sensitivity, Linkage Disequilibrium Score Correlation (LDSC), and Bayesian Colocalization (COLOC) analyses were conducted to ensure the robustness and reliability of our findings.

RESULTS: Using the IVW method, seven medications with negative causal associations with neuropsychiatric disorders were identified. Pregabalin, bumetanide, and prednisolone were associated with reduced anxiety (beta = -7.28, p = 4.00e-03; beta = -2.24, p = 6.00e-03; beta = -1.74, p = 2.84e-03). Vitamin B1 preparations showed an inverse association with dementia (beta = -2.47, p = 1.51e-03), Creon E/C granules with epilepsy (beta = -4.99, p = 3.91e-03), Pentasa SR 250 mg with multiple sclerosis (beta = -3.95, p = 3.83e-03), and zolmitriptan with stroke excluding subarachnoid hemorrhage (beta = -1.61, p = 6.00e-03). Sensitivity analyses confirmed these findings, whereas the LDSC and COLOC analyses provided additional support.

CONCLUSION: MR-based drug repurposing is a promising approach for the treatment of neuropsychiatric disorders. Further validation is necessary to effectively integrate these medications into clinical practice.

PMID:40511653 | DOI:10.2174/011570159X368382250527073353

J Pharm Bioallied Sci. 2025 May;17(Suppl 1):S52-S54. doi: 10.4103/jpbs.jpbs_1770_24. Epub 2025 Feb 15.

ABSTRACT

The most strategic weapon in drug discovery in the recent past has been artificial intelligence (AI)-bringing new approaches to one of the toughest areas of the pharmaceutical industry. Various AI approaches such as DL and ML methods utilized in various stages of drug discovery and development including but not limited to virtual screening and target identification are also discussed here. Employing this approach, this review looks at AI programs and platforms that exist in drug discovery today in a bid to outline what a future with AI in this field has in stock. In addition to this, this review does not only give a momentary state of the state of affairs of the AI in the space, but also briefly discusses what is in store next, along with the drawback and the opportunity more so from this perspective.

PMID:40511146 | PMC:PMC12156605 | DOI:10.4103/jpbs.jpbs_1770_24

Front Pharmacol. 2025 May 29;16:1541987. doi: 10.3389/fphar.2025.1541987. eCollection 2025.

ABSTRACT

BACKGROUND: DNA is generally considered the ultimate target of cisplatin, so DNA repair has become the hallmark for cisplatin chemoresistance that is attributed to the poor overall survival (50%) among patients with head and neck cancer (HNC). As the efficacy of cisplatin is dose-dependent, we conducted the first study in an Asian population to characterize the DNA repair genes ACTL6A and ERCC1 based on the dosing of cisplatin-based chemoradiotherapy (CRT).

METHODS: Locally advanced HNC (LAHNC) patients who were planning to undergo cisplatin-based CRT were enrolled in a prospective study to quantify the dose-dependent expressions of ACTL6A and ERCC1 from peripheral blood mononuclear cells via quantitative polymerase chain reaction; these results were integrated with computational analysis and systematic review/meta-analysis to formulate evidence-based translation decisions. The Friedman test and Wilcoxon's test were used to compare the expressions of the two genes before and after CRT, and Spearman's rank correlation was used to find the correlation between ACTL6A and ERCC1 expressions. All statistical analyses were performed using SPSS version 29.

RESULTS: A total of 77 LAHNC patients were enrolled in this study, of which 96.1% were men and 3.9% were women with a mean age of 52.88 ± 9.68 years. The median expressions of ERCC1 were significantly increased (p < 0.001) after 50% (0.19) and 100% CRT (0.23) compared to the baseline value (0.14), whereas ACTL6A expression decreased from 4.77 to 3.87 after 50% CRT (p < 0.05) and increased to 5.43 after 100% CRT. From the computational analysis, ACTL6A and ERCC1 were found to be overexpressed among HNC patients and observed to regulate 10 repair pathways. Overexpressions of ERCC1 and ACTL6A were predicted to infiltrate the tumors with CD4+ cells, macrophages, dendritic cells, and B cells. The hazard ratios for overall survival were found to be 1.67 among the ACTL6A overexpressed and 1.82 among the ERCC1 overexpressed HNC patients via computational analysis and meta-analysis, respectively. Furthermore, FDA-approved drugs like gemcitabine and panobinostat were found to be the best candidates for downregulating ERCC1 and ACTL6A expressions based on binding affinities of -3.707 and -4.198 kcal/mol, respectively.

CONCLUSION: The increased expressions of ACTL6A and ERCC1 during/after cisplatin-based CRT are expected to mediate DNA repair leading to chemoresistance, which could result in poor overall survival in HNC patients. Thus, FDA-approved drugs like panobinostat and gemcitabine can be repurposed to target the chemoresistance genes ACTL6A and ERCC1, respectively.

PMID:40510426 | PMC:PMC12159016 | DOI:10.3389/fphar.2025.1541987

Front Immunol. 2025 May 29;16:1602189. doi: 10.3389/fimmu.2025.1602189. eCollection 2025.

ABSTRACT

Acute myeloid leukemia (AML), originating from myeloid hematopoietic stem/progenitor cells, is a malignant hematological disorder. Resistance to current treatments, especially in FLT3-ITD AML cases, urgently demands the development of novel therapeutics. In this study, we pinpointed fostamatinib, an orally delivered small molecule SYK inhibitor for chronic immune thrombocytopenia (ITP), as a promising candidate for drug repurposing. It effectively inhibited FLT3-ITD+ AML cell proliferation and induced leukemic cell apoptosis. Network pharmacology analysis further deciphered the associated pharmacological mechanism related to the PI3K-AKT signaling pathway. Moreover, fostamatinib downregulated the expression of immune checkpoints such as PD-L1 and CD47. Overall, this study provided a conceptual foundation for evaluating the advantages of drug repurposing in AML drug development.

PMID:40510356 | PMC:PMC12158979 | DOI:10.3389/fimmu.2025.1602189

Molecules. 2025 May 24;30(11):2303. doi: 10.3390/molecules30112303.

ABSTRACT

Antimicrobial resistance (AMR) is one of the most significant public health threats today. The need for new antimicrobials against multidrug-resistant infections is growing. The development of computational models capable of predicting new drug-target interactions is an interesting strategy to reposition already known drugs into potential antimicrobials. The objective of this review was to compile the latest advances in the development of computational models capable of identifying drugs already registered by the Food and Drug Administration for other indications with potential capacity to be applied as antimicrobials. We present studies that apply in silico methods such as machine learning, molecular docking, molecular dynamics and deep learning. Some of these studies have in vitro/in vivo results that demonstrate the reliability of this computational methodology in terms of the identification of effective molecules and new targets of interest in the treatment of infections. In addition, we present the methods that are under development and their future prospects in terms of the search for new antimicrobials. We highlight the need to implement these strategies in the research of effective drugs in the treatment of infectious diseases and to continue to improve the available models and approaches to gain an advantage against the rapid emergence of AMR.

PMID:40509191 | DOI:10.3390/molecules30112303

Int J Mol Sci. 2025 Jun 5;26(11):5415. doi: 10.3390/ijms26115415.

ABSTRACT

Schistosomiasis is a parasitic disease caused by helminth parasites of the genus Schistosoma, affecting >200 million people worldwide. Current schistosomiasis treatment relies on a single drug, praziquantel, highlighting the urgent need for new therapies. We have identified a non-neuronal tegumental acetylcholinesterase from Schistosoma mansoni (SmTAChE) as a rational and molecularly defined drug target. Molecular modeling reveals significant structural differences between SmTAChE and human AChE, suggesting the potential for identifying parasite-specific inhibitors. Here, we screened recombinant SmTAChE (rSmTAChE) against two chemical libraries: the Broad Institute Drug Repurposing Hub (5440 compounds) and the Diversity-Oriented Synthesis (DOS)-A library (3840 compounds). High-throughput screening identified 116 hits from the Repurposing Hub (2.13% hit rate) and 44 from the DOS-A (1.14% hit rate) library that inhibited rSmTAChE ≥60% at 20 µM. Dose-response assays using both rSmTAChE and recombinant human AChE (rHsAChE) revealed 19 Repurposing Hub compounds (IC50: 0.4-24 µM) and four DOS-A scaffolds (IC50: 13-29 µM), with higher selectivity for rSmTAChE. Selective inhibitors such as cepharanthine, primaquine, mesalazine, and embelin emerged as promising candidates for further evaluation in schistosomiasis treatment. These 23 newly identified selective hits provide a foundation for the further development of novel anti-schistosome therapies.

PMID:40508222 | DOI:10.3390/ijms26115415