J Clin Med. 2025 May 26;14(11):3733. doi: 10.3390/jcm14113733.

ABSTRACT

Background/Objectives: Peritoneal dialysis (PD) is a renal replacement therapy for patients with kidney failure. Managing PD patients often involves addressing a complex interplay of comorbidities and complications, necessitating the use of multiple medications. This study aimed to systematically characterize commonly co-prescribed drugs in PD and to identify novel drug combinations that may target dysregulated molecular mechanisms associated with PD's pathophysiology. Methods: We analyzed clinical records from 702 PD patients spanning 30 years, encompassing over 5500 prescription points. Using network-based modeling techniques, we assessed drug co-prescription patterns, clinical outcomes, and longitudinal treatment trends. To explore potential drug repurposing opportunities, we constructed a molecular network model of PD based on a consolidated transcriptomics dataset and integrated this with drug-target interaction information. Results: We found commonly prescribed drugs such as furosemide, sucroferric oxyhydroxide, calcitriol, darbepoetin alfa, and aluminum hydroxide to be integral components of PD patient management, prescribed in over 30% of PD patients. The molecular-network-based approach found combinations of drugs like theophylline, fluoxetine, celecoxib, and amitriptyline to possibly have synergistic effects and to target dysregulated molecules of PD-related pathomechanisms. Two further distinct categories of drugs emerged as particularly interesting in our study: selective serotonin reuptake inhibitors (SSRIs), which were found to modulate molecules implicated in peritoneal fibrosis, and vascular endothelial growth factor (VEGF) inhibitors, which exhibit anti-fibrotic properties that are potentially useful for PD. Conclusions: This comprehensive exploration of drug co-prescriptions in the context of PD-related pathomechanisms provides valuable insights for opening future therapeutic strategies and identifying new targets for drug repurposing.

PMID:40507495 | DOI:10.3390/jcm14113733

Inflammopharmacology. 2025 Jun 12. doi: 10.1007/s10787-025-01792-0. Online ahead of print.

ABSTRACT

Raynaud's phenomenon is a peripheral vascular disorder characterized by exaggerated vasoconstrictive response to certain stimuli, most typically cold exposure and emotional stress. Interestingly, Raynaud's phenomenon incidence is significantly higher in premenopausal females compared to age-matched males, highlighting a role of the female hormone, estrogen, in Raynaud's phenomenon pathogenesis. Indeed, estrogen plays a fundamental role in potentiating the expression and function of α2C adrenoceptor (α2C-AR), the sole mediator of local cooling-induced vasoconstriction. Due to the mosaic nature of Raynaud's phenomenon involving vascular, hormonal, and neuronal factors, as well as due to the lack of an appropriate animal model, the pathogenesis of Raynaud's phenomenon is not fully elucidated. Consequently, despite various therapeutic approaches aimed at mitigating symptoms of Raynaud's phenomenon, a definitive treatment for Raynaud's phenomenon is quite challenging and remains an unmet need. Therefore, a better understanding of the underlying pathophysiologic mechanisms of Raynaud's phenomenon is crucial to better delineate pharmacotherapeutic targets to help fight this elusive disease. In this paper, we dissect the molecular and cellular mechanisms underlying Raynaud's phenomenon and its risk factors, and we shed more light on the role of estrogen. We also explore traditional and current therapeutic approaches, including pharmacologic and non-pharmacologic treatments. In addition, we discuss how the advancement in molecular research offered promising avenues of Raynaud's phenomenon treatment, namely drug repurposing and molecular targeting. Nonetheless, enhanced awareness, precaution, and good patient compliance are critically important in preventing the progression of Raynaud's phenomenon and reducing its severity.

PMID:40506673 | DOI:10.1007/s10787-025-01792-0

Med Oncol. 2025 Jun 12;42(7):255. doi: 10.1007/s12032-025-02811-4.

ABSTRACT

Cancer is a medical problem that has been difficult to overcome on a global scale. Owing to the sharing of single or multiple genes or regulatory modules, cancer treatment often faces severe challenges. The core of network pharmacology lies in constructing human disease gene regulation networks and multi-pharmacology network. With the continuous updating and iteration of new technologies, it is helpful for us to systematically understand the occurrence and development mechanism behind complex diseases and elucidate the pharmacological mechanisms from the perspective of biological network balance. This review aims to clarify the application of network pharmacology in exploring the pharmacological treatment mechanism of natural products, drug repositioning, and new technology combinations in the context of complex pathogenesis of cancer, so as to help realize the full potential of network pharmacology. Additionally, we discuss the future development of network pharmacology to guide clinical diagnosis and treatment.

PMID:40506575 | DOI:10.1007/s12032-025-02811-4

Eur J Pharm Sci. 2025 Jun 10:107165. doi: 10.1016/j.ejps.2025.107165. Online ahead of print.

ABSTRACT

BACKGROUND: Cancer remains the second leading cause of mortality worldwide, underscoring the urgent need for novel therapeutic strategies. Drug repurposing is an effective strategy to address current cancer challenges, such as the resistance and toxicity associated with traditional chemotherapy. Among the various psychotropic drugs, antidepressants are emerging as promising candidates due to their demonstrated anticancer activity.

METHODS: We evaluated duloxetine (DUL), a serotonin-norepinephrine reuptake inhibitor, for anticancer and immunomodulatory activity by performing comprehensive in vitro and in vivo experiments. In HCT116 (colon), HeLa (cervical), and MDA-MB-231 (triple-negative breast cancer) human cancer cells, and 4T1 mouse breast cancer cells, we investigated DUL's cytotoxicity, apoptosis, autophagy, cell cycle arrest, and migration inhibition through MTT assay, flow cytometry, and immunofluorescence methods. An orthotopic mouse model of breast cancer was utilized to investigate the in vivo tumor inhibitory effects of DUL, along with its systemic toxicity and immunomodulatory properties. Gene expression (p53, Beclin-1), cytokine profile, and CD3+ T cell activation were examined by mRNA sequencing and ELISA kits to explore underlying mechanisms.

RESULTS: For the first time, our in vitro results indicated that DUL caused dose-dependent cytotoxicity, apoptosis, autophagy, and cell cycle arrest in all cancer lines tested, which was more selective than 5-fluorouracil (5-FU). Mechanistically, DUL modulated apoptotic (Bcl-2, Bax, caspase-3), autophagic (p62), and survival (pAkt) signaling, disrupted mitochondrial membrane potential, and inhibited cell migration. In vivo, DUL inhibited tumor growth without inducing hepatic or renal toxicity. Notably, DUL stimulated the production of pro-inflammatory cytokines (IFN-γ, IL-1β, TNF-α), enhanced the immunity of CD3+ T cells, and increased the expression of pro-apoptotic p53 and autophagic Beclin-1 genes, reflecting its dual antitumor and immunomodulatory actions.

CONCLUSION: Our findings revealed for the first time that DUL is a promising repurposed drug for cancer treatment, as it has demonstrated proven antitumor efficacy and immune-stimulating properties. This novel dual role of DUL warrants further investigation in clinical oncology.

PMID:40505838 | DOI:10.1016/j.ejps.2025.107165

Lett Appl Microbiol. 2025 Jun 12:ovaf086. doi: 10.1093/lambio/ovaf086. Online ahead of print.

ABSTRACT

Drug repurposing, offers promising opportunities to address infections caused by multidrug-resistant bacteria. This study was to evaluate the bactericidal activity, anti-biofilm properties, and potential mechanisms of the antihistamine drug ebastine against S. aureus. The minimum inhibitory concentrations of ebastine against standard and clinical S. aureus isolates were determined using the broth microdilution method. The MIC values ranged from 2 to 8 µg·mL-1, indicating good activity against clinical drug-resistant strains. Time-kill curve analyses revealed a dose-dependent bactericidal effect. Regarding anti-biofilm activity, ebastine significantly inhibited biofilm formation at higher concentrations and demonstrated a moderate ability to eradicate preformed biofilms. Mechanistic studies revealed that ebastine exerted the antimicrobial effects by causing disruption to bacterial membrane integrity and inducing reactive oxygen species generation. Furthermore, safety evaluations showed that ebastine exhibited limited toxicity to mammalian cells, with negligible hemolytic effects and good overall safety profiles. This study provided new insights into the potential applications of ebastine in the field of antimicrobial therapy, highlighting its promise as a non-traditional antibacterial agent.

PMID:40504561 | DOI:10.1093/lambio/ovaf086

Acta Parasitol. 2025 Jun 12;70(3):135. doi: 10.1007/s11686-025-01074-3.

ABSTRACT

OBJECTIVE: Chagas disease is an infectious disease classified under neglected tropical diseases and caused by the protozoan parasite Trypanosoma cruzi. This study aimed to investigate the cytotoxic activity, antitrypanosomal efficacy, and combination effects with benznidazole of hybrid silver nanoparticles (AgNPs) synthesized with miltefosine against T. cruzi epimastigotes.

METHODS: In this study, a hybrid miltefosine (Mil)-silver nanoparticle (OA-MilAg-NP) complex was synthesized. The nanoparticles were characterized using FT-IR spectroscopy, transmission electron microscopy (TEM), and scanning electron microscopy (SEM) analyses. The cytotoxicity of the nanoparticles was assessed in L929 fibroblast cells, while their antitrypanosomal activity was evaluated against a Trypanosoma cruzi ATCC 50828 strain using the broth microdilution method. The interaction between the nanoparticle complex or miltefosine and benznidazole was analyzed using the checkerboard method.

RESULTS: FT-IR analysis demonstrated that the amylose surface was successfully coated with silver and miltefosine, confirming the successful synthesis of the hybrid complex. SEM analysis revealed that the nanoparticles exhibited a spherical morphology with varying sizes, while TEM analysis determined their sizes ranged between 10.14 and 18.42 nm. The OA-MilAg-NP complex exhibited high antitrypanosomal activity and a selectivity index twice as high as that of miltefosine. Synergistic interactions were observed in the combinations of the OA-MilAg-NP complex or miltefosine with benznidazole.

CONCLUSION: The development of novel bioactive compounds with lower toxicity compared to traditional drugs has become essential for the treatment of Chagas disease. Drug repurposing combined with nanotechnology applications holds significant potential for improving therapeutic outcomes. The hybridization of miltefosine with silver nanoparticles, demonstrating strong antitrypanosomal activity and synergistic effects with benznidazole, may fill critical gaps in the literature.

PMID:40504446 | DOI:10.1007/s11686-025-01074-3

In Silico Pharmacol. 2025 Jun 9;13(2):85. doi: 10.1007/s40203-025-00374-w. eCollection 2025.

ABSTRACT

The rise of zoonotic viruses like Monkeypox (mpox) presents significant challenges to public health, the economy, and modern medical practices. These pathogens, which can transfer from animals to humans, have the potential to cause both localized outbreaks and global pandemics. Monkeypox, recently recognized as a zoonotic virus, is particularly concerning due to its severe impact, especially on children and those with weakened immune systems. In light of the pressing need for effective treatments, repurposing existing drugs and utilizing computational modeling have emerged as vital strategies for discovering potential therapeutic agents. Research has demonstrated the promise of Direct Acting Antivirals (DAAs) against various viral infections. By employing computational tools and existing data, we can quickly identify potential treatments to combat the current mpox outbreak. Given that the cysteine protease of mpox bears similarities to proteases found in viruses such as HCV and HIV, it is plausible that DAAs could inhibit mpox protease. We applied machine learning techniques, including Support Vector Machines (SVM), Reinforcement Learning (RL), and K-Nearest Neighbors (KNN), to analyze a set of 86 DAAs. The compounds predicted to be effective inhibitors were then assessed using structural modeling methods. Our docking simulations identified four DAAs-Paritaprevir (DB09297), Ledipasvir (DB09027), Lenacapavir (DB15673), and Bictegravir (DB11799)-as having particularly strong binding affinities for mpox protease. Key interacting residues, such as Cys328, Tyr270, His241, and Gly329, were found to be critical in the binding process. These results indicate that FDA-approved DAAs might provide new treatment avenues for mpox. Nevertheless, additional validation through experimental studies is necessary to confirm the biological effectiveness of these drug candidates. This research provides a foundational basis for exploring DAAs as potential new treatments for mpox, with future investigations required to fully determine their therapeutic value.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-025-00374-w.

PMID:40503562 | PMC:PMC12149071 | DOI:10.1007/s40203-025-00374-w

Mol Ther Nucleic Acids. 2025 May 14;36(2):102562. doi: 10.1016/j.omtn.2025.102562. eCollection 2025 Jun 10.

ABSTRACT

Emerging RNA virus outbreaks, including Zika virus, highlight the urgent need for novel antiviral strategies. Zika virus, a positive-strand RNA virus, causes congenital Zika syndrome, and to date, there are no approved vaccines or antiviral treatments. In this context, microRNAs are small non-coding RNAs that regulate gene expression and show potential as antiviral agents due to their ability to target viral RNA, making them a promising therapeutic approach against Zika syndrome. In this study, we identified endogenous microRNAs that interact with the virus genome using computational algorithms and overexpressed them in VERO cells. Twelve microRNAs reduced viral cytopathic effects by more than 50% in cells infected with a Brazilian Zika virus strain. Additionally, we used a computational platform to select pharmacological compounds capable of modulating endogenous microRNAs in human cells, achieving over 90% inhibition of Zika virus activity. These findings offer a promising path through drug repurposing for antiviral therapy by modulating endogenous microRNAs, with potential applications for other positive-strand RNA viruses.

PMID:40503177 | PMC:PMC12155756 | DOI:10.1016/j.omtn.2025.102562

Front Oncol. 2025 May 28;15:1628842. doi: 10.3389/fonc.2025.1628842. eCollection 2025.

NO ABSTRACT

PMID:40502631 | PMC:PMC12151989 | DOI:10.3389/fonc.2025.1628842

bioRxiv [Preprint]. 2025 May 30:2025.05.28.656743. doi: 10.1101/2025.05.28.656743.

ABSTRACT

INTRODUCTION AND METHODS: Endometriosis has limited treatment options, prompting the search for novel therapeutics. We previously used a transcriptomics-based computational drug repositioning pipeline to analyze public bulk transcriptomic data and identified several drug candidates. Fenoprofen, our top in silico candidate, was validated in a rat model. Building on this, we now evaluate two additional candidates, simvastatin (a cholesterol-lowering drug) and primaquine (an antimalarial), based on strong gene expression reversal scores and favorable safety profiles. Using a validated rat model of endometriosis and pain, we conducted behavioral testing, bulk RNA sequencing, and differential expression analysis to assess their therapeutic potential.

RESULTS: Of 299 drugs identified computationally, simvastatin and primaquine ranked highly for reversing gene expression signatures associated with endometriosis. In vivo validation using a rat model of endometriosis demonstrated that both drugs significantly reduced vaginal hyperalgesia, a surrogate marker of endometriosis-associated pain. RNA-seq of uteri and lesions confirmed reversal of disease-associated gene expression signatures following treatment.

CONCLUSION: Simvastatin and primaquine attenuated pain behaviors and reversed endometriosis-related gene expression changes in an animal model. These findings highlight their potential as repurposed therapeutics for endometriosis-related pain and support the effectiveness of computational drug repositioning strategies in identifying new treatment strategies.

PMID:40502156 | PMC:PMC12154721 | DOI:10.1101/2025.05.28.656743

bioRxiv [Preprint]. 2025 Jun 2:2025.05.30.656746. doi: 10.1101/2025.05.30.656746.

ABSTRACT

Biomedical research underpins progress in our understanding of human health and disease, drug discovery, and clinical care. However, with the growth of complex lab experiments, large datasets, many analytical tools, and expansive literature, biomedical research is increasingly constrained by repetitive and fragmented workflows that slow discovery and limit innovation, underscoring the need for a fundamentally new way to scale scientific expertise. Here, we introduce Biomni, a general-purpose biomedical AI agent designed to autonomously execute a wide spectrum of research tasks across diverse biomedical subfields. To systematically map the biomedical action space, Biomni first employs an action discovery agent to create the first unified agentic environment - mining essential tools, databases, and protocols from tens of thousands of publications across 25 biomedical domains. Built on this foundation, Biomni features a generalist agentic architecture that integrates large language model (LLM) reasoning with retrieval-augmented planning and code-based execution, enabling it to dynamically compose and carry out complex biomedical workflows - entirely without relying on predefined templates or rigid task flows. Systematic benchmarking demonstrates that Biomni achieves strong generalization across heterogeneous biomedical tasks - including causal gene prioritization, drug repurposing, rare disease diagnosis, micro-biome analysis, and molecular cloning - without any task-specific prompt tuning. Real-world case studies further showcase Biomni's ability to interpret complex, multi-modal biomedical datasets and autonomously generate experimentally testable protocols. Biomni envisions a future where virtual AI biologists operate alongside and augment human scientists to dramatically enhance research productivity, clinical insight, and healthcare. Biomni is ready to use at https://biomni.stanford.edu , and we invite scientists to explore its capabilities, stress-test its limits, and co-create the next era of biomedical discoveries.

PMID:40501924 | PMC:PMC12157518 | DOI:10.1101/2025.05.30.656746

bioRxiv [Preprint]. 2025 Jun 2:2025.06.02.657296. doi: 10.1101/2025.06.02.657296.

ABSTRACT

Tuberculosis (TB) remains the second leading cause of infectious disease mortality worldwide, killing over one million people annually. Rising antibiotic resistance has created an urgent need for host-directed therapeutics (HDTs) - preferably by repurposing existing approved drugs - that modulate host immune responses rather than directly targeting the pathogen. Repurposed therapeutics have been successfully identified for cancer and COVID-19 by finding drugs that reverse disease gene expression patterns (an approach called 'connectivity scoring'), but this approach remains largely unexplored for bacterial infections like TB. The application of transcriptome-based methods to TB faces significant challenges, including dataset heterogeneity across transcriptomics platforms and biological conditions, uncertainty about optimal scoring methods, and lack of systematic approaches to identify robust disease signatures. Here, we developed an integrative computational workflow combining multiple connectivity scoring methods with consensus disease signature construction and used it to systematically identify FDA-approved drugs as promising TB host-directed therapeutics. Our framework integrates six complementary connectivity methods and constructs weighted consensus signatures from 21 TB gene expression datasets spanning microarray and RNA-seq platforms, diverse cell types, and infection conditions. Our approach prioritized 140 high-confidence drug candidates that consistently reverse TB-associated gene expression changes, successfully recovering known HDTs, including statins (atorvastatin, lovastatin, fluvastatin) and vitamin D receptor agonists (calcitriol). We identified promising novel candidates such as niclosamide and tamoxifen, both recently validated in experimental TB models, and revealed enrichment for therapeutically relevant mechanisms, e.g., cholesterol metabolism inhibition and immune modulation pathways. Network analysis of disease-drug interactions identified 10 key bridging genes (including MYD88, RELA, and CXCR2) that represent potential novel druggable targets for TB host-directed therapy. This work establishes transcriptome-based connectivity mapping as a viable approach for systematic HDT discovery in bacterial infections and provides a robust computational framework applicable to other infectious diseases. Our findings offer immediate opportunities for experimental validation of prioritized drug candidates and mechanistic investigation of identified druggable targets in TB pathogenesis.

PMID:40501823 | PMC:PMC12157595 | DOI:10.1101/2025.06.02.657296

Front Immunol. 2025 May 27;16:1604154. doi: 10.3389/fimmu.2025.1604154. eCollection 2025.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Despite therapeutic advances, there is a critical need to identify novel, effective, and safe drug targets to improve precision treatment strategies.

METHODS: We developed a multi-layered framework integrating Mendelian randomization (MR), colocalization analysis, genome-wide association study (GWAS) data, and expression quantitative trait loci (eQTLs) to prioritize causal and druggable genes in CRC. Single-cell and bulk RNA sequencing were used to characterize gene expression within the tumor microenvironment. Phenome-wide association studies (PheWAS) assessed off-target effects, and drug repurposing potential was evaluated using OpenTargets, DrugBank, and DGIdb. Validation of key targets was performed through RT-qPCR and immunohistochemistry (IHC) in CRC patient samples.

RESULTS: Out of 4,479 druggable genes, MR analysis identified 47 candidates significantly associated with CRC risk. Six genes (TFRC, TNFSF14, LAMC1, PLK1, TYMS, and TSSK6) demonstrated strong colocalization signals and were further validated across replication datasets and subtype-stratified analyses. PheWAS analysis revealed minimal off-target effects for these genes. Notably, several of these genes have already been targeted by existing or investigational drugs, suggesting potential for repurposing. These genes exhibited distinct expression patterns in tumor and stromal cell types and were differentially expressed in CRC versus normal tissues. Among them, TNFSF14, an immune modulator, is particularly involved in regulating T cell activation within the tumor microenvironment.

CONCLUSION: This study identifies and validates six promising druggable targets for CRC, providing a strong foundation for future preclinical studies. These findings open avenues for advancing precision oncology and drug repurposing strategies in CRC treatment, contributing to the development of more effective and personalized therapeutic approaches.

PMID:40496862 | PMC:PMC12149120 | DOI:10.3389/fimmu.2025.1604154

Cell Death Discov. 2025 Jun 10;11(1):275. doi: 10.1038/s41420-025-02552-3.

ABSTRACT

Using clinically relevant animal models, we have recently demonstrated that the anticonvulsant primidone (Liskantin®), approved by the FDA for the treatment of various forms of epilepsy, can effectively block RIPK1 enzymatic activity, which mediates cell death, and consequently prevent RIPK1 cytotoxicity and associated inflammatory responses. Based on these findings, we now reveal both a preventive and, more importantly, a therapeutic effect of primidone in the imiquimod (IMQ)-induced psoriasis-like inflammation model. Notably, the protective effect of IMQ in this necroinflammatory disease is directly correlated with inhibition of the activated state of RIPK1 (as monitored by auto-phosphorylation on Ser166/T169), a critical marker that had been missing in the highly contradictory studies that have previously been published. This allows us to unequivocally identify RIPK1 as a therapeutic target in the treatment of inflammatory disorders, including psoriasis. Given that newly developed RIPK1 inhibitors have shown very limited success in clinical trials for inflammatory and neurological diseases in recent years, and that none of these inhibitors has yet reached clinical utilization, our data strongly recommend a clinical study to evaluate the already approved drug primidone for the treatment of patients suffering from psoriasis within the context of drug repurposing.

PMID:40494888 | DOI:10.1038/s41420-025-02552-3

Med. 2025 Jun 3:100724. doi: 10.1016/j.medj.2025.100724. Online ahead of print.

ABSTRACT

BACKGROUND: Defining the progression of blood biomarkers in Alzheimer's disease (AD) is essential for targeting treatments in patients most likely to benefit from early intervention. We delineated the temporal ordering of blood biomarkers a decade prior to the onset of AD, explored associations with AD brain pathology, and examined the relationship between reactive astrocytosis in the brain and plasma in a transgenic mouse model.

METHODS: We analyzed plasma blood biomarkers using the Quanterix HD-X instrument in case-control and postmortem cohorts from the Baltimore Longitudinal Study on Aging (BLSA). We assessed plasma and cortical reactive astrocytosis, measured by glial fibrillary acidic protein (GFAP), in 5xFAD transgenic and wild-type mice.

FINDINGS: In AD-converters (N = 158, 377 samples), higher plasma GFAP levels are observed 10 years prior to the onset of cognitive impairment due to AD compared with individuals who remain cognitively unimpaired (N = 160, 379 samples). Plasma GFAP levels are highest in neuropathologically confirmed AD, intermediate in asymptomatic AD, and lowest in cognitively unimpaired and associated with severity of neuritic plaques and neurofibrillary tangles. GFAP-labeled immunoreactive astrocytes in the cortex of 3- and 7-month-old 5xFAD transgenic mice increased relative to wild-type mice and higher blood GFAP concentration was associated with more GFAP-expressing astrocytes.

CONCLUSIONS: Reactive astrocytosis, assessed by elevated GFAP levels, is an early event in the progression of blood biomarker changes in preclinical AD, may be an early marker of AD pathogenesis, and a promising therapeutic target.

FUNDING: Intramural Research Program, NIA.

PMID:40494355 | DOI:10.1016/j.medj.2025.100724

Proc Natl Acad Sci U S A. 2025 Jun 17;122(24):e2423650122. doi: 10.1073/pnas.2423650122. Epub 2025 Jun 10.

ABSTRACT

The OXA β-lactamases in Acinetobacter baumannii represent a primary mechanism for resistance to the carbapenems, a class of antibiotics that represent a last line for treatment. In a screen of an U.S. Food and Drug Administration (FDA)-approved drug library, we identified fendiline, a calcium channel blocker, had significantly more antimicrobial activity against OXA-23 expressing cells. Genetic and proteomic studies revealed that fendiline inhibited the essential lipoprotein trafficking pathway (Lol) in both A. baumannii (LolFD) and Escherichia coli (LolCDE). We demonstrate that OXA-23 is an outer membrane lipoprotein and its overexpression resulted in increased lethality in lolFD-depleted A. baumannii. Our results indicate that overexpression of the OXA-23 β-lactamase in A. baumannii stresses normal lipoprotein trafficking, which makes these cells more susceptible to fendiline. Overall, our data reveal a link between carbapenem resistance and the Lol pathway, which can be leveraged for new drug development.

PMID:40493197 | DOI:10.1073/pnas.2423650122

Front Bioinform. 2025 May 26;5:1536504. doi: 10.3389/fbinf.2025.1536504. eCollection 2025.

ABSTRACT

Molecular docking is among the fastest and most readily available computational tools to explore protein-ligand interactions. However, little effort has been put into assessing the quality of its results. In this paper, we compared eight free license docking programs to screen a drug library against the human target, phosphodiesterase 5A (PDE5A), to evaluate their ability to find its known ligand, sildenafil, and other ligands that became erectile dysfunction drugs because they inhibit this target. GNINA was superior at identifying the known target because it offers a convolutional neural network (CNN) score that ranks the quality of docking results. Using this CNN score improved the ranking of known positives. Receiver operating characteristic (ROC) analysis revealed that all docking suites lack specificity; that is, they often misidentify true negatives. Employing a CNN score cutoff before ranking by docking affinity raised specificity with a small loss in sensitivity. After the cutoff, datasets became smaller but of higher quality. We propose a heuristic to produce relevant docking results, which includes an overall evaluation of the target on docking performance through ROC and an improvement of candidate binder selection using a CNN score cutoff of 0.9.

PMID:40491848 | PMC:PMC12146287 | DOI:10.3389/fbinf.2025.1536504

Bioinform Adv. 2025 Jun 5;5(1):vbaf092. doi: 10.1093/bioadv/vbaf092. eCollection 2025.

ABSTRACT

MOTIVATION: Drug repurposing is gaining interest due to its high cost-effectiveness, low risks, and improved patient outcomes. However, most drug repurposing methods depend on drug-disease-target semantic connections of a single drug rather than insights from drug combination data. In this study, we propose SynDRep, a novel drug repurposing tool based on enriching knowledge graphs (KG) with drug combination effects. It predicts the synergistic drug partner with a commonly prescribed drug for the target disease, leveraging graph embedding and machine learning (ML) techniques. This partner drug is then repurposed as a single agent for this disease by exploring pathways between them in the KG.

RESULTS: HolE was the best-performing embedding model (with 84.58% of true predictions for all relations), and random forest emerged as the best ML model with an area under the receiver operating characteristic curve (ROC-AUC) value of 0.796. Some of our selected candidates, such as miconazole and albendazole for Alzheimer's disease, have been validated through literature, while others lack either a clear pathway or literature evidence for their use for the disease of interest. Therefore, complementing SynDRep with more specialized KGs, and additional training data, would enhance its efficacy and offer cost-effective and timely solutions for patients.

AVAILABILITY AND IMPLEMENTATION: SynDRep is available as an open-source Python package at https://github.com/SynDRep/SynDRep under the Apache 2.0 License.

PMID:40491566 | PMC:PMC12148216 | DOI:10.1093/bioadv/vbaf092

OMICS. 2025 Jun 10. doi: 10.1089/omi.2025.0066. Online ahead of print.

ABSTRACT

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbidity and mortality. Despite their clinical association, the underlying genetic mechanisms and therapeutic targets that might link these two chronic disorders remain poorly understood. The present study used in silico analyses and machine learning to uncover genetic features and potential therapeutic targets shared by IPF and PH. Differentially expressed genes (DEGs) were identified using RNA sequencing data from the Gene Expression Omnibus, which revealed a total of 13 common DEGs between IPF and PH. Importantly, among the identified genes, TFF3 was significantly upregulated in both diseases. TFF3 is targeted by aminoglutethimide as identified through the Drug Gene Interaction Database, and with an interaction score of 3.26. Using the Protein Contact Atlas, PROCHECK, PROSA, and ProtParam tools, the structural model of TFF3 was validated. Finally, molecular docking analysis demonstrated a binding affinity score of -6.1 kcal/mol between TFF3 and aminoglutethimide, indicating a stable and potentially effective interaction between aminoglutethimide and the target protein. Aminoglutethimide displayed favorable ADMET properties as well. In conclusion, this in silico study reports (1) potential overlapping molecular links between IPF and PH, and (2) in silico potential of aminoglutethimide and TFF3 in drug repurposing for therapeutic interventions targeting both IPF and PH. These findings also challenge the traditional paradigm of pharmaceutical innovation that has long relied on the "one drug, one disease" premise, and highlight the potentials of "one drug, polydisease" paradigm of drug discovery and development.

PMID:40491360 | DOI:10.1089/omi.2025.0066

ACS Biomater Sci Eng. 2025 Jun 10. doi: 10.1021/acsbiomaterials.5c00680. Online ahead of print.

ABSTRACT

Drug repurposing has received increasing attention in the field of oncology drug development as an alternative strategy to de novo drug synthesis. Disulfiram (DSF) has a long history of clinical application in alcohol withdrawal, and recent studies have revealed that its metabolite diethyldithiocarbamate (DDTC) can be coordinated with copper ions in vivo to form Cu-DDTC complexes with anticancer activity. However, the insufficient in vivo stability of DSF remains a challenge. In this study, the nanomedicine Cu-BTC@DDTC with DDTC-Cu(I) chemical valence and polycrystalline structure was prepared by incorporation of DDTC into the nanosized metal-organic framework (MOF) Cu-BTC. The in vitro cellular evaluation results showed that Cu-BTC@DDTC exhibited high inhibition of tumor cell growth, migration, and invasion. Animal experiments on the xenograft tumor model further demonstrated the excellent antitumor activity and biosafety of Cu-BTC@DDTC, and the antitumor activity was found to be closely related to the regulation of the SLC7A11/GPX4 signaling pathway to induce ferroptosis. This study provides a feasible option for antitumor drug development based on a drug repurposing strategy.

PMID:40491359 | DOI:10.1021/acsbiomaterials.5c00680