Br J Clin Pharmacol. 2025 Jul 24. doi: 10.1002/bcp.70181. Online ahead of print.

NO ABSTRACT

PMID:40704644 | DOI:10.1002/bcp.70181

Br J Pharmacol. 2025 Jul 23. doi: 10.1111/bph.70119. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Pharmacological activation of neuronal M-current mediated by Kv7 (Kv7.2-5) potassium channels is a validated mechanism for epilepsy treatment. However, since the market withdrawal of the prototype Kv7 activator retigabine, no Kv7 activator is clinically available for this condition. The object was to identify, characterise and validate new neuronal Kv7 channel activators for epilepsy treatment.

EXPERIMENTAL APPROACH: A fluorescence-based high-throughput assay was optimised in cells stably expressing Kv7 channels to screen two repurposing libraries including >8000 compounds. Whole-cell patch clamp, in silico docking, mutagenesis and multielectrode array recordings in human induced-pluripotent stem cell (hiPSCs)-derived cortical-like glutamatergic neurons (iNeurons) were used to evaluate compound(s) potency and efficacy, binding site, and effects on neuronal activity, respectively. Finally, anticonvulsant activity was assessed in two acute seizure models in male mice.

KEY RESULTS: JNJ-37822681, a fast-dissociating D2 receptor antagonist in clinical development as antipsychotic, enhanced Kv7.2-5 currents with potency and efficacy largely comparable to retigabine. In Kv7.2 subunits, JNJ-37822681 binding site largely overlapped that for retigabine. In iNeurons, JNJ-37822681 enhanced the M-current, hyperpolarised the resting membrane potential and reduced spontaneous action potential firing. These effects were blocked by the Kv7 antagonist, XE-991, and were not reproduced by the D2 antagonist (-)-sulpiride. Finally, JNJ-37822681 showed anticonvulsant activity in two well-validated mouse models of acute seizures.

CONCLUSIONS AND IMPLICATIONS: Our study reveals that JNJ-37822681, which lacks retigabine's potential safety issues due to chemical liability and is already confirmed as safe for human use, represents a potential treatment of Kv7-related neuronal hyperexcitability disorders.

PMID:40702669 | DOI:10.1111/bph.70119

Med Oncol. 2025 Jul 24;42(9):371. doi: 10.1007/s12032-025-02941-9.

ABSTRACT

Mast cells (MC) play a crucial role in the tumor microenvironment (TME) by promoting tumor progression and immune evasion through the secretion of inflammatory mediators. Here, we investigate the impact of epigenetic reprogramming using a drug repurposing combination-hydralazine, a DNA methylation inhibitor, and valproate, a histone deacetylase inhibitor (HDACi)-on MC-cancer cell interactions. Human cancer cell lines (Ca Ski, MDA-MB-468, and A549) that secrete stem cell factor (SCF) were selected from a panel of tumor lines. The HMC-I MC line and the selected cancer cell lines were treated with hydralazine + valproate (HV) for 72 h, and viability assessed via trypan blue exclusion assay revealed consistent reduction across all lines. Conditioned medium (CM) from HV-treated MCs was applied to cancer cells, with MDA-MB-468 displaying resistance. CM from HV-treated cancer cells was then used to evaluate MC migration and chemotaxis, showing reduced mobility in MCs exposed to supernatants from Ca Ski and MDA-MB-468, but not A549. Flow cytometry analysis revealed that HV epigenetically suppressed the expression of pro-tumoral cytokines and MC chemoattractants, with ITAC being the only consistently upregulated cytokine. These findings demonstrate that pharmacological epigenetic reprogramming via HV modulates MC-driven tumor progression and reshapes the cytokine network, highlighting its potential as a novel immunoepigenetic therapeutic strategy in cancer.

PMID:40702162 | DOI:10.1007/s12032-025-02941-9

Curr Issues Mol Biol. 2025 Apr 15;47(4):277. doi: 10.3390/cimb47040277.

ABSTRACT

Transient receptor potential vanilloid 3 (TRPV3) is a non-selective cation channel prominently present in the skin. It plays a role in diverse physiological and pathological functions like inflammation of the skin, pain sensations in the skin, and persistent itchiness. Overactive TRPV3 channels contribute to numerous inflammatory skin diseases, and this highlights the therapeutic potential of its inhibitors. Using a drug repurposing screening approach, we identified fluoxetine-a clinically established antidepressant agent-as a potent inhibitor of TRPV3 channel activation, demonstrating its therapeutic potential for skin inflammation alleviation. During whole-cell patch-clamp recordings, fluoxetine exhibits a selective inhibitory effect on macroscopic TRPV3 currents in a concentration-dependent fashion. The IC50 value is measured as 10.23 ± 2.34 μM. On the single-channel scale, fluoxetine leads to a reduction in both single-channel conductance and the open probability of the channel. In the course of animal experiments, fluoxetine mitigates carvacrol-induced TRPV3-related skin inflammation. It lessens the severity of dorsal lesions and ear edema in mice. Our study not only identified TRPV3 as a novel target of fluoxetine and provides new ideas for the treatment of TRPV3-mediated skin diseases with fluoxetine, but also provides a valuable tool molecule for further understanding TRPV3 channel pharmacology.

PMID:40699677 | DOI:10.3390/cimb47040277

Front Immunol. 2025 Jul 8;16:1619434. doi: 10.3389/fimmu.2025.1619434. eCollection 2025.

ABSTRACT

BACKGROUND: Molecular events that drive endometriosis (EM) and cause accompanying immune deregulation remain elusive. Our purpose was to identify key pathways involved in lesion formation across diverse populations and to detect transcriptomic changes in eutopic endometrium that accompany EM.

METHODS: We searched Gene Expression Omnibus and ArrayExpress and performed differential gene expression analysis and a network meta-analysis on nine qualifying datasets. Those contained transcriptomic data on 114 ectopic endometrium samples (EL), 138 eutopic endometrium samples from women with endometriosis (EEM), and 79 eutopic endometrium samples from women without endometriosis (EH). Gene ontology and enrichment analysis were performed in DAVID, Metascape, and Cytoscape, and drug repurposing was done in CMap.

RESULTS: EEM compared to EH upregulated CCL21 and downregulated BIRC3, CEL, and LEFTY1 genes (|log2FC| > 0.5, p < 0.05). EL showed increased expression of complement and serpin genes (EL vs. EEM: C7, logFC = 3.38, p < 0.0001; C3, logFC = 2.40, p < 0.0001; SERPINE1, logFC = 1.02, p < 0.05; SERPINE2, logFC = 1.54, p < 0.001) and mast cell markers (EL vs. EEM: CPA3, logFC = 1.54, p < 0.0001; KIT, logFC = 0.74, p < 0.001). Functional enrichment analysis highlighted complement and coagulation, inflammation, angiogenesis, and extracellular matrix remodeling as drivers of endometriosis. Pharmacogenomic analysis indicated Janus kinase (JAK), cyclin-dependent kinase (CDK), and topoisomerase inhibitors as therapy targets.

CONCLUSION: Our results suggest an interplay between complement and coagulation, mast cells, extracellular matrix remodeling, and the JAK/STAT3 pathway in endometriosis. We underscore the significance of complement C3 and propose JAK inhibitors as therapy candidates. Detected expression differences between EEM and EH are important for the development of diagnosis via endometrial biopsy.

PMID:40698088 | PMC:PMC12279843 | DOI:10.3389/fimmu.2025.1619434

World J Gastrointest Oncol. 2025 Jul 15;17(7):107681. doi: 10.4251/wjgo.v17.i7.107681.

ABSTRACT

Colorectal cancer (CRC) ranks as the third most common cancer globally and the second leading cause of cancer-related deaths, representing a significant health burden. Despite advancements in traditional treatments such as surgery, chemotherapy, targeted therapy, and immunotherapy, these approaches still face challenges, including high costs, limited efficacy, and drug resistance. Drug repurposing has emerged as a promising strategy for CRC treatment, offering advantages with reduced development timelines, lower costs, and improved drug accessibility. This review explores drug repurposing strategies for CRC, supported by multidisciplinary technologies, and discusses the current challenges in the field.

PMID:40697217 | PMC:PMC12278253 | DOI:10.4251/wjgo.v17.i7.107681

J Alzheimers Dis. 2025 Jul 22:13872877251360009. doi: 10.1177/13872877251360009. Online ahead of print.

ABSTRACT

BackgroundThe accumulation of particular protein deposits connected to molecular mechanisms is one of the many brain abnormalities associated with Alzheimer's disease (AD), a complex neurodegenerative illness. There are currently no effective disease-modifying treatments for AD.ObjectiveThis study attempts to identify potential AD therapeutics through a biological network-based drug repurposing strategy, focusing on drugs targeting important proteins and biological pathways involved in AD pathology.MethodsA comprehensive biological network of AD-associated molecules and their transcription regulatory interactions is constructed. This computational approach integrates data from genome-wide association studies, multiple AD-related magnetic resonance imaging (MRI) derived phenotypes, biomolecular interactions, and gene expression profiles.ResultsThe constructed AD sub-regulatory network reveals significant correlations between transcription factors showing changed gene expression in AD patients relative to controls. This strategy prioritizes drug candidates based on their mechanisms of action, reducing the risk of clinical trial failures and enhancing patient outcomes related to AD. A total of 43 drug candidates have been identified, including 28 FDA-approved drugs, 15 experimental and investigational drugs that may alter biological processes pertaining to important facets of AD pathology. Baricitinib and Gabapentin emerge as promising candidates for targeting AD-related biological processes in the cerebral cortex and hippocampus regions.ConclusionsBy combining biological network analysis and MRI-driven transcriptome-wide association study, this systematic drug repurposing strategy demonstrates promise for identifying novel therapeutic options for AD and offers potential implications for addressing other complex neurological disorders.

PMID:40696841 | DOI:10.1177/13872877251360009

Sci Rep. 2025 Jul 23;15(1):26716. doi: 10.1038/s41598-025-12788-9.

ABSTRACT

Observational studies found that phosphodiesterase 5 (PDE5) inhibitors use is linked to both increased and decreased risk of cancer; while the causal relationship remains unclear. To clarify whether PDE5 inhibitors medication may affect the risk of cancer, 2-sample cis-Mendelian randomisation (MR) analysis was therefore performed. Uncorrelated (linkage disequilibrium [LD] r2 < 0.001) single-nucleotide polymorphisms (SNPs) in PDE5A gene associated (P < 5.0 × 10-8) with circulating levels of PDE5A protein identified from UKB-PPP were used as genetic instrument to mimic the action of PDE5 inhibition. Summary-level data for 22 types of cancer obtained from site-specific GWAS were analyzed in discovery stage (428,361 cancer cases) and then replicated in the FinnGen study (87,505 cancer cases). Inverse-variance weighted random-effects models were used as primary analysis. After multiple testing correction, genetically predicted, per-standard deviation (SD) decrease in PDE5A protein was associated with decreased risk of colorectal cancer with a pooled odds ratio (OR) of 0.80 (95% confidence interval [CI]: 0.75-0.86; P = 6.15 × 10-11). A significant MR association (OR = 0.48, 95% CI: 0.34-0.68; P = 4.70 × 10-5) with gastric cancer (GC) was also observed in combined analysis. There was little evidence to support associations between genetically proxied PDE5 inhibition and other 20 studied cancers. We found an protective effect of genetically proxied PDE5 inhibition on CRC and GC risk. Our drug target MR analyses provide genetic evidence in predicting long-term safety profiles of PDE5 inhibitors on cancer risk and highlight the potential of drug repurposing in CRC and GC.

PMID:40696067 | DOI:10.1038/s41598-025-12788-9

Cell. 2025 Jul 15:S0092-8674(25)00737-8. doi: 10.1016/j.cell.2025.06.035. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by heterogeneous molecular changes across diverse cell types, posing significant challenges for treatment development. To address this, we introduced a cell-type-specific, multi-target drug discovery strategy grounded in human data and real-world evidence. This approach integrates single-cell transcriptomics, drug perturbation databases, and clinical records. Using this framework, letrozole and irinotecan were identified as a potential combination therapy, each targeting AD-related gene expression changes in neurons and glial cells, respectively. In an AD mouse model with both Aβ and tau deposits, this combination therapy significantly improved memory performance and reduced AD-related pathologies compared with vehicle and single-drug treatments. Single-nucleus transcriptomic analysis confirmed that the therapy reversed disease-associated gene networks in a cell-type-specific manner. These results highlight the promise of cell-type-directed combination therapies in addressing multifactorial diseases like AD and lay the groundwork for precision medicine tailored to patient-specific transcriptomic and clinical profiles.

PMID:40695276 | DOI:10.1016/j.cell.2025.06.035

Biomed Pharmacother. 2025 Jul 21;190:118359. doi: 10.1016/j.biopha.2025.118359. Online ahead of print.

ABSTRACT

Triple-negative breast cancer (TNBC) is an aggressive subtype with limited treatment options, high relapse rates, and poor survival outcomes, largely due to chemoresistance. This study aimed to identify potential therapeutic strategies by repurposing FDA-approved anticancer drugs using patient-derived TNBC organoids from drug-resistant residual tumors post-chemotherapy. A high-throughput screen of 133 FDA-approved drugs, integrating image-based analysis and drug-sensitivity assays, identified the proteasome inhibitors bortezomib and carfilzomib as potent cytotoxic agents. Proteomic analysis, coupled with translation and cell cycle assays, showed that these inhibitors suppress TNBC organoid growth by downregulating ribosomal protein expression, leading to impaired translation and disrupted cell cycle progression. Furthermore, drug response dynamics confirmed their efficacy in overcoming clinical drug resistance. Transcriptomic profiling revealed that proteasome inhibitors counteract doxorubicin-induced, inflammation-driven resistance through dual anti-inflammatory and antiproliferative effects. Collectively, these findings support proteasome inhibition as a promising therapeutic strategy to overcome chemoresistance in TNBC.

PMID:40695045 | DOI:10.1016/j.biopha.2025.118359

Mol Pharm. 2025 Jul 22. doi: 10.1021/acs.molpharmaceut.5c00250. Online ahead of print.

ABSTRACT

Antibody-based biotherapeutics make up an important class of biopharmaceuticals. However, their discovery requires resource- and time-consuming laboratory processes. To ameliorate this situation, several computational methods were used to predict the structures of antibody:antigen complexes (Ab:Ag) and identify potential binders, in-silico. However, there is still a general lack of rapid virtual screening methods capable of screening large antibody libraries against a given antigen or group of antigens. In this work, we explore the application of a successful small-molecule drug discovery strategy and adapt pharmacophore-based virtual screening to the world of antibody discovery. Using a nonredundant data set of 874 Ab:Ag complexes, we have developed an automated method to create pharmacophores from the antibody complementarity determining regions. Our method is 98.6% (862 out of 874) successful at reproducing the ground truth, i.e., it can recapitulate the parental antibody:antigen complexes. In a benchmarking comparison with cognate docking, using 33 Ab:Ag complexes of therapeutic interest, the pharmacophore method was not only much faster than cognate docking but also recovered all the native interfacial contacts. In addition, it can also find additional putative antibody binders to a given antigen within clusters of Ab:Ag complexes with similar interfacial structures. Our method has significant implications toward accelerating biotherapeutic drug discovery as well as drug repurposing research. This method was implemented in MOE 2024 and is available to the scientific community.

PMID:40694045 | DOI:10.1021/acs.molpharmaceut.5c00250

ACS Chem Neurosci. 2025 Jul 21. doi: 10.1021/acschemneuro.5c00044. Online ahead of print.

ABSTRACT

We investigated the effects of cyclic peptides somatostatin, its isomer d-Trp8-somatostatin, and marketed somatostatin derivatives octreotide and lanreotide on Aβ42 aggregation and cytotoxicity in mouse hippocampal HT22 cells. The aggregation kinetic studies show that all the cyclic peptides were able to reduce Aβ42 fibrillogenesis at 1, 5, 10, and 25 μM. The native cyclic peptide somatostatin exhibited superior inhibition compared to other cyclic peptides (91% inhibition at 25 μM) and exhibited greater inhibition compared to the reference agent orange G (86% inhibition at 25 μM), whereas the corresponding isomer d-Trp8-somatostatin exhibited 74% inhibition at 25 μM. The marketed drugs octreotide and lanreotide exhibited a similar inhibition profile (∼54% inhibition at 25 μM). Electron microscopy and immunoblotting experiments also demonstrate their antiaggregation properties. Furthermore, the cyclic peptides were not toxic to mouse hippocampal neuronal HT22 cells and exhibited cell viability ranging from 89 to 98.7% at 10 μM. Strikingly, the cyclic peptides somatostatin, d-Trp8-somatostatin, octreotide, and lanreotide were able to rescue mouse hippocampal neuronal HT22 cells from Aβ42-mediated cytotoxicity (cell viability: 71.7-83.8% at 10 μM). The marketed cyclic peptide drugs octreotide and lanreotide exhibited superior activity (cell viability: 83.8% and 81%, respectively) in preventing Aβ42-induced cytotoxicity compared to somatostatin and d-Trp8-somatostatin. Computational studies were able to identify the potential interaction sites of cyclic peptides in the Aβ42 hexamer assembly. Our studies demonstrate the ability of these cyclic peptides to interact with Aβ42 and reduce Aβ42-induced toxicity, highlighting the potential of marketed drugs octreotide and lanreotide in drug repurposing for Alzheimer's disease.

PMID:40690368 | DOI:10.1021/acschemneuro.5c00044

Cell Biochem Biophys. 2025 Jul 21. doi: 10.1007/s12013-025-01840-0. Online ahead of print.

ABSTRACT

Obesity and type II diabetes are independent risk factors for Endometrial cancer (EC) development. Elevated levels of insulin-like growth factor-1 (IGF-1), insulin resistance, and the increased activity of IGF-1 receptor is linked to EC development through the PI3K/AKT/mTOR pathway. The antidiabetic agent metformin is a promising repurposing drug for cancer treatment, but the mechanisms underlying its effects are not completely known. This study evaluated how metformin could act against the EC cell line Ishikawa cultured in vitro or grafted into female Balb/C nude mice. In vitro experiments demonstrated that treatment with 25 mM of metformin reduced cell viability through promoting cytotoxicity, mitochondrial dysfunction, apoptosis, and cell cycle arrest (G1 phase). Mice treatment with 250 mg/kg of metformin for 28 days did not change serum IGF-1 levels nor decreased the grafted cell-induced tumor weight and cell proliferation, but prevented its volume growth while genes of the IGF1-R and PI3K/AKT/mTOR pathways (AKT2, GAPDH, FOXO3, IGF1R, INSR, MAPK3, MTOR, and SHC1) were downregulated. Metformin treatment was more impacting for the in vitro model, but our molecular results provide valuable insights into the possible action of metformin against EC tumoral cells at physiological level. In-silico analysis using Cytoscape indicated that metformin was not described as interacting with AKT2 and SHC1 proteins. Besides interacting with metformin, mTOR and MAPK3 present the larger number of interactions with the other proteins. These four genes/proteins emerge as potential targets for deepening studies to determine the metformin's role in longer EC treatment using animal models.

PMID:40690138 | DOI:10.1007/s12013-025-01840-0

Oncotarget. 2025 Jul 21;16:562-581. doi: 10.18632/oncotarget.28755.

ABSTRACT

Colorectal cancer remains the second leading cause of cancer-related deaths worldwide, highlighting the urgent need for more effective therapies and a deeper understanding of its molecular basis. Drug repurposing has gained traction as a viable strategy to target dysregulated oncogenic pathways. Statins, commonly prescribed for lowering cholesterol, have recently shown potential anti-cancer effects. In this study, we explore how statin treatment influences lipid metabolism, gene expression, and proteomic profiles in colorectal cancer models. Our findings provide direct evidence that statins selectively modulate key components of the Wnt/β-catenin signaling pathway, a major driver of adenoma formation, including members of the special AT-rich sequence-binding (SATB) protein family. We show that statin treatment downregulates SATB1, a known promoter of tumorigenesis in the context of Wnt activation, while simultaneously upregulating SATB2, which plays an opposing role. This reciprocal regulation shifts cellular phenotypes between epithelial and mesenchymal states in 3D spheroid models. Together, these results highlight the therapeutic potential of statins in colorectal cancer and support their consideration in drug repurposing approaches.

PMID:40689929 | DOI:10.18632/oncotarget.28755

Res Pharm Sci. 2025 Jun 17;20(3):392-407. doi: 10.4103/RPS.RPS_9_25. eCollection 2025 Jun.

ABSTRACT

BACKGROUND AND PURPOSE: The Fat mass and obesity-associated protein (FTO) plays a significant role in esophageal cancer by regulating N6-methyladenosine (m6A) modification. FTO inhibition has shown potential in cancer therapies but remains underexplored. This study aimed to identify a safer, FDA-approved compound for FTO inhibition that can be used in combination with chemotherapy drugs.

EXPERIMENTAL APPROACH: FDA-approved drugs were screened from the Zinc 15 database using AutoDock Vina against the 3D structure of FTO (PDB ID: 3LFM). Discovery Studio software was used to determine binding interactions. The GROMACS package was used for molecular dynamics simulations. A non-toxic concentration was determined through an MTT assay on KYSE-30 esophageal cancer cells. The ELISA assay was used to measure the m6A levels in RNA.

FINDINGS/RESULTS: Four compounds, ergotamine, midazolam, digoxin, and loratadine, were identified. Loratadine (ΔG: -8.9) formed stable interactions with FTO, specifically with residues Ser229, Tyr109, Leu109, Val229, and His231. Molecular dynamic simulations of the FTO-loratadine complex revealed higher RMSD fluctuations (0.4-0.6 nm), but the system remained stable overall. RMSF analysis showed similar fluctuation patterns in all three systems, indicating that loratadine did not affect protein structure stability. MM/PBSA calculations revealed powerful binding energy for the FTO-loratadine complex (-135.73 kJ/mol), driven by favorable van der Waals interactions. KYSE-30 cells treated with loratadine (100 μM), m6A levels in KYSE- 30 cells compared to the control group were significantly elevated at a non-toxic concentration.

CONCLUSION AND IMPLICATIONS: Loratadine is a promising, low-toxic FTO inhibitor that could complement chemotherapy for esophageal cancer.

PMID:40687281 | PMC:PMC12271845 | DOI:10.4103/RPS.RPS_9_25

Arch Pharm (Weinheim). 2025 Jul;358(7):e70029. doi: 10.1002/ardp.70029.

ABSTRACT

Protozoal infections remain a significant global health burden despite significant progress in understanding these infections in recent years due to the continuing emergence of multidrug resistance among protozoal parasites. This review focuses on recent innovations in protozoal disease treatment aimed at combating this growing challenge of drug resistance. The escalating prevalence of multidrug resistance among protozoal parasites, especially those responsible for widespread diseases such as malaria, leishmaniasis, and trypanosomiasis, is rapidly emerging as a grave threat to human health worldwide. This resistance undermines the efficacy of existing treatments, making it imperative to develop and explore novel therapeutic approaches. Diverse strategies, including the concept of hybrid drugs, the development of advanced analogs of existing drugs, and drug repurposing, have been employed to counter drug resistance by outmaneuvering the evolution of resistant parasites and restoring the effectiveness of treatments. In this review, we delve into the significant findings reported between 2020 and 2024, with the aim of providing an overview of the state of protozoal disease treatment, highlighting the progress made, exploring promising avenues for tackling these devastating diseases, and offering insights into future directions for overcoming the persistent challenge of drug resistance. Given that the emergence of drug resistance calls for a multifaceted approach to address protozoal infections, long-term success depends on interdisciplinary research collaborations, equitable access to treatment, and appropriate drug resistance surveillance, in addition to the advancement of research and the development of therapeutic strategies described in this review.

PMID:40685763 | DOI:10.1002/ardp.70029

Neurol Res. 2025 Jul 20:1-15. doi: 10.1080/01616412.2025.2532039. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Cerebral venous thrombosis (CVT) is an uncommon yet potentially life-threatening subtype of stroke that predominantly affects younger individuals. This study aimed to systematically identify and validate druggable genes associated with CVT susceptibility using Mendelian randomization (MR) approaches.

METHODS: We integrated two large-scale expression quantitative trait loci (eQTLs) datasets - eQTLGen (peripheral blood) and PsychENCODE (brain tissue) - as exposures, with CVT genome-wide association study (GWAS) summary statistics from FinnGen serving as the outcome. A two-sample MR (TSMR) framework was employed, supported by sensitivity analyses, summary-data-based MR (SMR), and Bayesian colocalization. Functional enrichment, single-cell analyses, drug prediction, and molecular docking were further performed to explore biological relevance and therapeutic potential.

RESULTS: TSMR identified 19 candidate genes from blood eQTLs after false discovery rate (FDR) correction; two were excluded due to pleiotropy, leaving 17, among which 10 were supported by SMR and colocalization. An additional nominally significant gene (ZP3) was detected from brain tissue. Of these, IL18, BMPR2, and COMT exhibited the strongest evidence. Functional annotation implicated these genes in cytokine signaling, cellular adhesion, and coagulation pathways. Single-cell RNA sequencing localized their expression mainly to monocytes, dendritic cells, and natural killer cells. Drug repurposing and docking analysis suggested potential inhibitory interactions between IL18 and glucocorticoids/pioglitazone, and between BMPR2 and iloprost.

CONCLUSION: This study reveals novel gene networks potentially involved in CVT pathogenesis and prioritizes IL18, BMPR2, and COMT as promising candidates for future therapeutic development. Nonetheless, these findings are based on genetic inference and require further mechanistic and clinical validation.

PMID:40684330 | DOI:10.1080/01616412.2025.2532039

Int J Biol Macromol. 2025 Jul 17:146096. doi: 10.1016/j.ijbiomac.2025.146096. Online ahead of print.

ABSTRACT

Acute kidney injury (AKI) remains a critical condition with limited pharmacological options. Bioactive macromolecules, including cytokines, receptors, and enzymes, play central roles in AKI pathogenesis, but systematic efforts to identify translational targets remain limited. In this study, we implemented a multi-omics integrative framework to nominate and validate candidate macromolecular targets for AKI. Using genetically informed screens anchored on a curated set of potentially actionable genes, we identified five prioritized candidates, CD46, IL6R, KLRC1, LEAP2, and SMOX, with strong biological plausibility and therapeutic potential. Bulk and single-cell RNA sequencing data revealed cell-type-specific enrichment, particularly in proximal tubules, immune subsets, and endothelium under AKI conditions. Pathway enrichment highlighted shared involvement in cytokine signaling, antigen presentation, and metabolic stress responses. In silico drug repurposing revealed several clinically approved compounds (e.g., tacrine, raloxifene hydrochloride, tretinoin) with strong predicted binding to CD46, IL6R, and SMOX. In vivo experiments demonstrated that pharmacological inhibition of SMOX significantly alleviated tubular injury, preserved renal function, and reduced oxidative stress. In vitro studies further confirmed the protective effects of SMOX inhibition by maintaining epithelial cell integrity and viability in renal tubular cells, while suppressing oxidative damage.

PMID:40683494 | DOI:10.1016/j.ijbiomac.2025.146096

Ann Parasitol. 2025 Jul 13;71:49-53. doi: 10.17420/ap71.545.

ABSTRACT

In order to overcome obstacles in diagnosis, surveillance, treatment, and vector control, artificial intelligence (AI) has emerged as a crucial weapon in the fight against malaria. The eradication of malaria has benefited greatly from the exceptional accuracy and efficiency of AI-driven solutions. This review of the literature examines several uses of AI in the fight against malaria, emphasizing new developments. AI-driven solutions have the potential to improve malaria prevention and eradication efforts with sustained innovation and investment, ultimately enhancing global health security. AI is transforming the treatment of malaria by facilitating personalised medicine, speeding up drug discovery, and enhancing diagnostics. AI is improving treatment approaches and tackling the problems caused by drug-resistant malaria parasites through machine learning, deep learning, and in silico drug repurposing. Achieving long-term malaria eradication targets will require sustained investment in AI-driven malaria research. In epidemiological tracking, artificial intelligence (AI) has also become a potent instrument. AI-driven methods offer creative ways to find novel treatment approaches, maximize drug discovery, and forecast the dynamics of malaria transmission, especially in light of the growing resistance of Plasmodium parasites to current medications. Thus, this review paper provides insights into the developments made by AI in combating malaria.

PMID:40682862 | DOI:10.17420/ap71.545

Sci Rep. 2025 Jul 18;15(1):26140. doi: 10.1038/s41598-025-10370-x.

ABSTRACT

Caenorhabditis elegans is a widely used animal model for researching new disease treatments. In recent years, automated methods have been developed to extract mobility phenotypes and analyse, using statistical methods, whether there are differences between control strains and disease model strains. However, these methods present certain limitations in detecting subtle and non-linear patterns. In this study, we propose a high-throughput screening method based on machine learning, using classifiers that provide a recovery percentage as a measure of treatment effect. We evaluate two main approaches: traditional machine learning models based on behavioral features extracted from the worm's skeleton using Tierpsy Tracker, and deep neural networks that directly analyse video sequences. The results indicate that a Random Forest classifier trained with features extracted by Tierpsy Tracker offers higher accuracy and explainability, making it more suitable than deep learning models for drug testing experiments. Finally, to assess the applicability of our method, we processed data from a published drug repurposing study on unc-80 mutants based on statistical methods. The results highlight the potential of machine learning models to enhance automated phenotypic screening in animal models, providing a more robust and quantitative evaluation of treatment effects by considering more complex and subtle patterns.

PMID:40681561 | DOI:10.1038/s41598-025-10370-x