Curr Issues Mol Biol. 2025 Jan 20;47(1):67. doi: 10.3390/cimb47010067.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) is a complex and increasingly prevalent malignancy with significant challenges in its treatment and prognosis. This study aims to explore the role of the SLC4A4 transporter as a biomarker in CRC progression and its potential as a therapeutic target, particularly in relation to tumor acidity and immune response.

METHODS: The study utilized computational approaches, including receptor-based virtual screening and high-throughput docking, to identify potential SLC4A4 inhibitors. A model of the human SLC4A4 structure was generated based on CryoEM data (PDB ID 6CAA), and drug candidates from the DrugBank database were evaluated using two computational tools (DrugRep and CB-DOCK2).

RESULTS: The study identified the compound (5R)-N-[(1r)-3-(4-hydroxyphenyl)butanoyl]-2-decanamide (DB07991) as the best ligand, demonstrating favorable binding affinity and stability. Molecular dynamics simulations revealed strong protein-ligand interactions with consistent RMSD (~0.25 nm), RMSF (~0.5 nm), compact Rg (4.0-3.9 nm), and stable SASA profiles, indicating that the SLC4A4 structure remains stable upon ligand binding.

CONCLUSIONS: The findings suggest that DB07991 is a promising drug candidate for further investigation as a therapeutic agent against CRC, particularly for targeting SLC4A4. This study highlights the potential of computational drug repositioning in identifying effective treatments for colorectal cancer.

PMID:39852182 | DOI:10.3390/cimb47010067

Curr Med Chem. 2025 Jan 23. doi: 10.2174/0109298673341391241231054936. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) remains a significant challenge in neurology, marked by progressive cognitive decline and neurodegeneration. Despite extensive research efforts, effective treatments are still lacking. Traditional drug discovery is often slow and costly, frequently resulting in limited success. Drug repurposing, which identifies new therapeutic uses for existing medications, has emerged as a promising approach to expedite AD treatment development. This review examines the potential of drug repurposing to transform AD therapy by utilizing the established safety profiles and known mechanisms of current drugs. We explore various repurposed drugs under investigation for AD, originally intended for cardiovascular, metabolic, and psychiatric conditions. Detailed discussions include how these drugs provide neuroprotective benefits by inhibiting amyloid-beta aggregation, reducing tau phosphorylation, and modulating neuroinflammation. Additionally, we emphasize the benefits of drug repurposing, such as shortened development timelines, lower costs, and increased chances of clinical success. By integrating current research findings, this review offers a thorough overview of the most promising repurposed drug candidates and their potential impact on AD treatment strategies. It stresses the importance of innovative approaches in AD research and calls for greater investment in drug repurposing initiatives. Through these strategies, we aim to accelerate the availability of effective treatments, providing renewed hope and a brighter future for those affected by this devastating disease.

PMID:39851113 | DOI:10.2174/0109298673341391241231054936

Front Pharmacol. 2025 Jan 9;15:1444311. doi: 10.3389/fphar.2024.1444311. eCollection 2024.

ABSTRACT

OBJECTIVE: The expanding field of hematopoietic cell transplantation (HCT) for non-malignant diseases, including those amenable to gene therapy or gene editing, faces challenges due to limited donor availability and the toxicity associated with cell collection methods. Umbilical cord blood (CB) represents a readily accessible source of hematopoietic stem and progenitor cells (HSPCs); however, the cell dose obtainable from a single cord blood unit is frequently insufficient. This limitation can be addressed by enhancing the potency of HSPCs, specifically their capacity to reconstitute hematopoiesis. In our study, we investigated the combined effects of treprostinil, a prostaglandin analog, and cinacalcet, a calcium-sensing receptor modulator, on the reconstitution of hematopoiesis.

METHODS: A Lineage Cell Depletion Kit was employed to isolate lineage-negative (lin-) HSPCs from mouse bone marrow. A Human CB CD34 Positive Selection Kit was utilized to isolate CD34+ cells from the CB of healthy donors. In vitro, the effects of treprostinil, cinacalcet, and their combination on the migration, adhesion, and differentiation of HSPCs were assessed. In vivo, homing and engraftment were examined. Eight-week-old female and male C57BL/6J, BALB/c, or female NSG mice served as recipient models.

RESULTS: When administered concomitantly, treprostinil and cinacalcet exhibited mutual antagonism: the survival of recipient animals was lower when both drugs were administered together compared to either agent alone. Conversely, a sequential regimen involving priming with treprostinil/forskolin followed by cinacalcet treatment in vivo enhanced survival, irrespective of whether hematopoiesis was reconstituted by human or murine HSPCs. In vitro assays demonstrated enhanced migration and adhesion in response to the presence of treprostinil and cinacalcet, suggesting potential synergistic effects. Colony formation confirmed synergism.

CONCLUSION: Augmenting the bone marrow reconstitution potential of HSPCs with treprostinil and cinacalcet shows promise for rescuing patients undergoing HCT. This approach is particularly beneficial for those patients at high risk of transplant failure due to limited numbers of available HSPCs. Furthermore, enhancing the potency of HSPCs has the potential to alleviate the burden and risks associated with HSPC donation, as it would reduce the number of cells needed for collection.

PMID:39850556 | PMC:PMC11755040 | DOI:10.3389/fphar.2024.1444311

J Biomol Struct Dyn. 2025 Jan 24:1-15. doi: 10.1080/07391102.2024.2335282. Online ahead of print.

ABSTRACT

The recent spread of SARS-CoV-2 has led to serious concerns about newly emerging infectious coronaviruses. Drug repurposing is a practical method for rapid development of antiviral agents. The viral spike protein of SARS-CoV-2 binds to its major receptor ACE2 to promote membrane fusion. Following the entry process, the spike protein is further activated by cellular proteases such as TMPRSS2 and Furin to promote viral entry into human cells. A crucial factor in preventing SARS-CoV-2 from entering target cells using HIV-1 fusion inhibitors is the similarity between the fusion mechanisms of SARS-CoV-2 and HIV-1. In this investigation, the HIV-1 fusion inhibitors CMK, Luteolin, and Naphthofluorescein were selected to understand the molecular mode of interactions and binding energy of Furin with these experimental inhibitors. The binding affinity of the three inhibitors with Furin was verified by molecular docking studies. The docking scores of CMK, Luteolin and Naphthofluorescein are -7.4 kcal/mol, -9.3 kcal/mol, and -10.7 kcal/mol, respectively. Therefore, these compounds were subjected to MD, drug-likeness, ADMET, and MM-PBSA analysis. According to the results of a 200 ns MD simulation, all tested compounds show stability with the complex and can be employed as promising inhibitors targeting SARS-CoV-2 Furin protease. In addition, pharmacokinetic analysis revealed that these compounds possess favorable drug-likeness properties. Thus, this study of Furin inhibitors helps in the evaluation of these compounds for use as novel drugs against SARS-CoV-2.

PMID:39849987 | DOI:10.1080/07391102.2024.2335282

Curr Res Transl Med. 2025 Jan 17;73(2):103496. doi: 10.1016/j.retram.2025.103496. Online ahead of print.

ABSTRACT

Drug repurposing is a promising strategy for managing cardiovascular disease (CVD) in geriatric populations, offering efficient and cost-effective solutions. CVDs are prevalent across all age groups, with a significant increase in prevalence among geriatric populations. The middle-age period (40-65 years) is critical due to factors like obesity, sedentary lifestyle, and psychosocial stress. In individuals aged 65 and older, the incidence of CVDs is highest due to age-related physiological changes and prolonged exposure to risk factors. In this review we find that certain drugs, such as non-cardiovascular drugs like anakinra, probenecid, N-acetyl cysteine, quercetin, resveratrol, rapamycin, colchicine, bisphosphonates, hydroxychloroquine, SGLT-2i drugs, GLP-1Ras drugs and sildenafil are recommended for drug repurposing to achieve cardiovascular benefits in geriatric patients. However, agents such as canakinumab, methotrexate, ivermectin, erythromycin, capecitabine, carglumic acid, chloroquine, and furosemide are constrained in their therapeutic use and warrant meticulous consideration, rendering them less favorable for this specific application. This review emphasizes the importance of exploring alternative therapeutic strategies to improve outcomes in geriatric populations and suggests drug repurposing as a promising avenue to enhance treatment efficacy.

PMID:39847829 | DOI:10.1016/j.retram.2025.103496

Front Immunol. 2025 Jan 7;15:1440922. doi: 10.3389/fimmu.2024.1440922. eCollection 2024.

ABSTRACT

BACKGROUND: SLE and ME/CFS both present significant fatigue and share immune dysregulation. The mechanisms underlying fatigue in these disorders remain unclear, and there are no standardized treatments. This study aims to explore shared mechanisms and predict potential therapeutic drugs for fatigue in SLE and ME/CFS.

METHODS: Genes associated with SLE and ME/CFS were collected from disease target and clinical sample databases to identify overlapping genes. Bioinformatics analyses, including GO, KEGG, PPI network construction, and key target identification, were performed. ROC curve and correlation analysis of key targets, along with single-cell clustering, were conducted to validate their expression in different cell types. Additionally, an inflammation model was established using THP-1 cells to simulate monocyte activation in both diseases in vitro, and RT-qPCR was used to validate the expression of the key targets. A TF-mRNA-miRNA co-regulatory network was constructed, followed by drug prediction and molecular docking.

RESULTS: Fifty-eight overlapping genes were identified, mainly involved in innate immunity and inflammation. Five key targets were identified (IL1β, CCL2, TLR2, STAT1, IFIH1). Single-cell sequencing revealed that monocytes are enriched with these targets. RT-qPCR confirmed significant upregulation of these targets in the model group. A co-regulatory network was constructed, and ten potential drugs, including suloctidil, N-Acetyl-L-cysteine, simvastatin, ACMC-20mvek, and camptothecin, were predicted. Simvastatin and camptothecin showed high affinity for the key targets.

CONCLUSION: SLE and ME/CFS share immune and inflammatory pathways. The identified key targets are predominantly enriched in monocytes at the single-cell level, suggesting that classical monocytes may be crucial in linking inflammation and fatigue. RT-qPCR confirmed upregulation in activated monocytes. The TF-mRNA-miRNA network provides a foundation for future research, and drug prediction suggests N-Acetyl-L-cysteine and camptothecin as potential therapies.

PMID:39845969 | PMC:PMC11752880 | DOI:10.3389/fimmu.2024.1440922

EClinicalMedicine. 2024 Dec 31;80:103035. doi: 10.1016/j.eclinm.2024.103035. eCollection 2025 Feb.

ABSTRACT

BACKGROUND: Phosphodiesterase 5 (PDE5) inhibitors, owing to their mechanism of action, have been gaining recognition as a potential case of drug repurposing and combination therapy for diabetes treatment. We aimed to examine the effect of long and short half-life PDE5 inhibitors have on Haemoglobin A1c (HbA1c) levels.

METHODS: A systematic review and meta-analysis was conducted of randomised controlled trials (RCTs) in people with elevated HbA1c (>6%) to assess mean difference in HbA1c levels from baseline versus controls after any PDE5 inhibitor intervention of ≥4 weeks, excluding multiple interventions. Cochrane CENTRAL, PMC Medline, ClinicalTrials.gov, and WHO ICTRP were searched without language restrictions up to September 30, 2024. Summary data from published data were extracted. PRISMA and Cochrane guidelines used to extract and assess data using a random-effects meta-analysis. This study is registered with the Research Registry, reviewregistry1733.

FINDINGS: Among 1096 studies identified, in analysis of 13 studies with 1083 baseline patients, long half-life PDE5 inhibitors (tadalafil, PF-00489791) had decreases in HbA1c while short half-life PDE5 inhibitors (sildenafil, avanafil) had no change. Five (38.5%) studies had a low risk of bias, and eight (61.5%) had some concerns. Long half-life inhibitors had significant mean decrease of -0.40% ([-0.66, -0.14], p = 0.002, I2 = 82%, 7.70% baseline HbA1c). Short half-life inhibitors had insignificant mean difference of +0.08% ([-0.16, 0.33], p = 0.51, I2 = 40%, 7.73% baseline HbA1c). In ≥8-week trials with participants with type 2 diabetes (T2D) and mean HbA1c ≥ 6.5%, long half-life inhibitors had significant mean decrease of -0.50% ([-0.83, -0.17], I2 = 88%, p = 0.003); short half-life inhibitors had significant mean increase of +0.36% ([0.03, 0.68], I2 = 3%, p = 0.03).

INTERPRETATION: At the well-controlled HbA1c of the participants, previous literature shows current diabetes treatments have similar HbA1c decreases, so the HbA1c mean difference of long half-life PDE5 inhibitors may indeed be clinically relevant. This suggests future investigation into PDE5 inhibitors as part of combination therapy or as therapy for high HbA1c individuals is needed, especially because of variable risk of biases, homogeneity, and sample sizes in our study.

FUNDING: None.

PMID:39844934 | PMC:PMC11751502 | DOI:10.1016/j.eclinm.2024.103035

BMC Bioinformatics. 2025 Jan 22;26(1):26. doi: 10.1186/s12859-024-06026-8.

ABSTRACT

BACKGROUND: Interpretability is a topical question in recommender systems, especially in healthcare applications. An interpretable classifier quantifies the importance of each input feature for the predicted item-user association in a non-ambiguous fashion.

RESULTS: We introduce the novel Joint Embedding Learning-classifier for improved Interpretability (JELI). By combining the training of a structured collaborative-filtering classifier and an embedding learning task, JELI predicts new user-item associations based on jointly learned item and user embeddings while providing feature-wise importance scores. Therefore, JELI flexibly allows the introduction of priors on the connections between users, items, and features. In particular, JELI simultaneously (a) learns feature, item, and user embeddings; (b) predicts new item-user associations; (c) provides importance scores for each feature. Moreover, JELI instantiates a generic approach to training recommender systems by encoding generic graph-regularization constraints.

CONCLUSIONS: First, we show that the joint training approach yields a gain in the predictive power of the downstream classifier. Second, JELI can recover feature-association dependencies. Finally, JELI induces a restriction in the number of parameters compared to baselines in synthetic and drug-repurposing data sets.

PMID:39844056 | DOI:10.1186/s12859-024-06026-8

Biomed Pharmacother. 2025 Jan 21;183:117862. doi: 10.1016/j.biopha.2025.117862. Online ahead of print.

ABSTRACT

The strategy of drug repositioning has historically played a significant role in the identification of new treatments for Parkinson's disease. Still today, numerous clinical and preclinical studies are investigating drug classes, already marketed for the treatment of metabolic disorders, for their potential use in Parkinson's disease patients. While drug repurposing offers a promising, fast, and cost-effective path to new treatments, these drugs still require thorough preclinical evaluation to assess their efficacy, addressing the specific neurodegenerative mechanisms of the disease. This review explores the state-of-the-art approaches to drug repurposing for Parkinson's disease, highlighting particularly relevant aspects. Preclinical studies still predominantly rely on traditional neurotoxin-based animal models, which fail to effectively replicate disease progression and are characterized by significant variability in model severity and timing of drug treatment. Importantly, for almost all the drugs analyzed here, there is insufficient data regarding the mechanism of action responsible for the therapeutic effect. Regarding drug efficacy, these factors may obviously render results less reliable or comparable. Accordingly, future preclinical drug repurposing studies in the Parkinson's disease field should be carried out using next-generation animal models like α-synuclein-based models that, unfortunately, have to date been used mostly for studies of disease pathogenesis and only rarely in pharmacological studies.

PMID:39842271 | DOI:10.1016/j.biopha.2025.117862

ANZ J Surg. 2025 Jan 22. doi: 10.1111/ans.19405. Online ahead of print.

ABSTRACT

BACKGROUND: Metformin is a diabetes medication with anti-mitotic properties. A narrative review was performed to investigate people using metformin and the risk of developing pancreatic ductal adenocarcinoma (PDAC) as well as survival outcomes in established PDAC.

METHODS: Relevant studies on metformin use and PDAC were retrieved from PubMed including observational studies on metformin and the risk of developing PDAC and survival outcomes in PDAC, and randomized controlled trials of metformin as a treatment in PDAC.

RESULTS: Of the 367 studies searched, 26 studies fulfilled the criteria for this review. Metformin was not consistently associated with a reduced risk of developing PDAC. However, metformin use, especially higher cumulative doses, in some studies was associated with longer survival in patients with established PDAC, especially in the subgroup with resectable PDAC. Metformin use was not associated with longer survival in more advanced (non-resectable metastatic) PDAC.

CONCLUSION: Metformin was not consistently associated with a reduced risk of developing PDAC. Metformin may be associated with overall survival benefits in patients with PDAC including the resectable PDAC subgroup but not in the metastatic PDAC subgroup. The evidence to date does not support the routine use of metformin as an adjuvant therapy for advanced PDAC.

PMID:39840695 | DOI:10.1111/ans.19405

Sci Prog. 2025 Jan-Mar;108(1):368504241301535. doi: 10.1177/00368504241301535.

ABSTRACT

The recent severe acute respiratory syndrome coronavirus 2 pandemic has clearly exemplified the need for broad-spectrum antiviral (BSA) medications. However, previous outbreaks show that about one year after an outbreak, interest in antiviral research diminishes and the work toward an effective medication is left unfinished. Martin et al. endeavored to support the early stages of focused BSA development by creating the Small Molecule Antiviral Compound Collection (SMACC), which is publicly available online at https://smacc.mml.unc.edu. SMACC is a highly curated database with over 32,500 entries of chemical compounds tested in both phenotypic and target-based assays across 13 viruses from the NIAID's list of emerging infectious diseases/pathogens. The authors advise judicious use of knowledge collections such as SMACC and recommend users critically evaluate retrieved data and resulting hypotheses prior to experimental testing. When used correctly, SMACC-like databases may serve as a reference for medicinal chemists and virologists working to develop novel BSA medications. To summarize, we emphasize the importance of data curation for both novel outbreak prediction and development of BSAs against these outbreaks.

PMID:39840476 | DOI:10.1177/00368504241301535

Alzheimers Dement (N Y). 2025 Jan 21;11(1):e70037. doi: 10.1002/trc2.70037. eCollection 2025 Jan-Mar.

ABSTRACT

ABSTRACT: Recent clinical trials on slowing dementia progression have led to renewed focus on finding safer, more effective treatments. One approach to identify plausible candidates is to assess whether existing medications for other conditions may affect dementia risk. We conducted a systematic review to identify studies adopting a data-driven approach to investigate the association between a wide range of prescribed medications and dementia risk. We included 14 studies using administrative or medical records data for more than 130 million individuals and 1 million dementia cases. Despite inconsistencies in identifying specific drugs that may modify Alzheimer's or dementia risk, some themes emerged for drug classes with biological plausibility. Antimicrobials, vaccinations, and anti-inflammatories were associated with reduced risk, while diabetes drugs, vitamins and supplements, and antipsychotics were associated with increased risk. We found conflicting evidence for antihypertensives and antidepressants. Drug repurposing for use in dementia is an urgent priority. Our findings offer a basis for prioritizing candidates and exploring underlying mechanisms.

HIGHLIGHTS: ·We present a systematic review of studies reporting association between drugs prescribed for other conditions and risk of dementia including 139 million people and 1 million cases of dementia.·Our work supports some previously reported associations, for example, showing decreased risk of dementia with drugs to treat inflammatory disease and increased risk with antipsychotic treatment.·Antimicrobial treatment was perhaps more surprisingly associated with decreased risk, supportive of recent increased interest in this potential therapeutic avenue.·Our work should help prioritize drugs for entry into adaptive platform trials in Alzheimer's disease and will serve as a useful resource for those investigating drugs or classes of drugs and risk of dementia.

PMID:39839078 | PMC:PMC11747987 | DOI:10.1002/trc2.70037

NPJ Parkinsons Dis. 2025 Jan 22;11(1):22. doi: 10.1038/s41531-025-00870-y.

ABSTRACT

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding genome-wide association studies (GWAS) loci effects on five types of brain-specific quantitative trait loci (xQTLs, including expression, protein, splicing, methylation and histone acetylation) under the protein-protein interactome (PPI) network. We then prioritized 175 PD likely risk genes (pdRGs), such as SNCA, CTSB, LRRK2, DGKQ, and CD44, which are enriched in druggable targets and differentially expressed genes across multiple human brain-specific cell types. Integrating network proximity-based drug repurposing and patient electronic health record (EHR) data observations, we identified Simvastatin as being significantly associated with reduced incidence of PD (hazard ratio (HR) = 0.91 for fall outcome, 95% confidence interval (CI): 0.87-0.94; HR = 0.88 for dementia outcome, 95% CI: 0.86-0.89) after adjusting for 267 covariates. In summary, our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.

PMID:39837893 | DOI:10.1038/s41531-025-00870-y

Sci Rep. 2025 Jan 21;15(1):2711. doi: 10.1038/s41598-025-85927-x.

ABSTRACT

Drug development is known to be a costly and time-consuming process, which is prone to high failure rates. Drug repurposing allows drug discovery by reusing already approved compounds. The outcomes of past clinical trials can be used to predict novel drug-disease associations by leveraging drug- and disease-related similarities. To tackle this classification problem, collaborative filtering with implicit feedback (and potentially additional data on drugs and diseases) has become popular. It can handle large imbalances between negative and positive known associations and known and unknown associations. However, properly evaluating the improvement over the state of the art is challenging, as there is no consensus approach to compare models. We propose a reproducible methodology for comparing collaborative filtering-based drug repurposing. We illustrate this method by comparing 11 models from the literature on eight diverse drug repurposing datasets. Based on this benchmark, we derive guidelines to ensure a fair and comprehensive evaluation of the performance of those models. In particular, an uncontrolled bias on unknown associations might lead to severe data leakage and a misestimation of the model's true performance. Moreover, in drug repurposing, the ability of a model to extrapolate beyond its training distribution is crucial and should also be assessed. Finally, we identified a subcategory of collaborative filtering that seems efficient and robust to distribution shifts. Benchmarks constitute an essential step towards increased reproducibility and more accessible development of competitive drug repurposing methods.

PMID:39837888 | DOI:10.1038/s41598-025-85927-x

Mini Rev Med Chem. 2025 Jan 17. doi: 10.2174/0113895575339660250106093738. Online ahead of print.

ABSTRACT

Metabolic reprogramming is a hallmark of cancer. Distinct and unusual metabolic aberrations occur during tumor development that lead to the growth and development of tumors. Oncogenic signaling pathways eventually converge to regulate three major metabolic pathways in tumor cells i.e., glucose, lipid, and amino acid metabolism. Therefore, identifying and targeting the metabolic nodes of cancer cells can be a promising intervention and therapeutic strategy for patients with malignancies. The long road of new drug discovery for cancer therapy has necessitated relooking alternative strategies such as drug repurposing. Advanced genomic and proteomic technologies for the assessment of cancer-specific biological pathways have led to the discovery of new drug targets, which provide excellent opportunities for drug repurposing. The development of effective, safe, cheaper, and readily available anticancer agents is the need of the hour, and drug repurposing has the potential to break the current drug shortage bottleneck. This review will accordingly cover various metabolic pathways that are aberrant in cancer, and strategies for targeting metabolic reprogramming by using repurposed drugs.

PMID:39835565 | DOI:10.2174/0113895575339660250106093738

J Inflamm Res. 2025 Jan 16;18:637-652. doi: 10.2147/JIR.S503118. eCollection 2025.

ABSTRACT

PURPOSE: Immunometabolism is pivotal in rheumatoid arthritis (RA) pathogenesis, yet the intricacies of its pathological regulatory mechanisms remain poorly understood. This study explores the complex immunometabolic landscape of RA to identify potential therapeutic targets.

PATIENTS AND METHODS: We integrated genome-wide association study (GWAS) data involving 1,400 plasma metabolites, 731 immune cell traits, and RA outcomes from over 58,000 participants. Mendelian randomization (MR) and mediation analyses were applied to evaluate causal relationships among plasma metabolites, immune cells, and RA. We further analyzed single-cell and bulk transcriptomes to investigate differential gene expression, immune cell interactions, and relevant biological processes. Machine learning models identified hub genes, which were validated via quantitative real-time PCR (qRT-PCR). Then, potential small-molecule drugs were screened using the Connectivity Map (CMAP) and molecular docking. Finally, a phenome-wide association study (PheWAS) was conducted to evaluate potential side effects of drugs targeting the hub genes.

RESULTS: Causalities were found between six plasma metabolites, five immune cells and RA in genetically determined levels. Notably, DC mediated 18% of the protective effect of PE on RA. Autophagy-related scores were elevated in both RA and DC subsets in PE-associated biological processes. Through observation in the functional differences in cellular interactions between the identified clusters, DCs with high autophagy scores may process such as necroptosis and the activation of the Jak-STAT signaling pathway in contributing the pathogenesis of RA. Explainable machine learning, PPI network analysis, and qPCR jointly identified four hub genes (PFN1, SRP14, S100A11, and SAP18). CMAP, molecular docking, and PheWAS analysis further highlighted vismodegib as a promising therapeutic candidate.

CONCLUSION: This study clarifies the key immunometabolic mechanisms in RA, pinpointing promising paths for better prevention, diagnosis, and treatment.

PMID:39835297 | PMC:PMC11745140 | DOI:10.2147/JIR.S503118

Int J Nanomedicine. 2025 Jan 16;20:605-624. doi: 10.2147/IJN.S500487. eCollection 2025.

ABSTRACT

INTRODUCTION: Androgenetic alopecia (AGA) is a multifactorial and age-related dermatological disease that affects both males and females, usually at older ages. Traditional hair repair drugs exemplified by minoxidil have limitations such as skin irritation and hypertrichosis. Thus, attention has been shifted to the use of repurposing drugs. Metformin is an anti-diabetic drug, that can promote hair follicle regeneration via upregulation of the hair-inductive capability. Hence, the current study aims to fabricate a safe and effective nanoemulsion to improve metformin efficacy in targeting AGA.

METHODS: Rosemary oil was selected as the oily phase due to its ability to increase blood flow and hair growth. Rosemary-based nanoemulsions were statistically optimized by Box-Behnken experimental design, loaded with metformin, and incorporated into a hydrogel to form a nanoemulgel. Metformin-loaded nanoemulsions were assessed for their diametric size, uniformity, zeta potential, and metformin characteristics within the formulated nanosystem. The nanoemulgel was then evaluated in terms of its pH, percentage drug content, and in-vitro release performance. In-vivo study assessed the nanoemulgel's ability to augment hair growth in rats.

RESULTS: The experimental design displayed that using 50%w/w, 20%w/w, and 10%w/w of Cremophor®, Labrafil®, and deionized water, respectively, resulted in nanoemulsion formulation with the smallest globule size (125.01 ± 0.534 nm), unimodal size distribution (PDI=0.103), negative surface charge (-19.9 ± 2.01 mV) with a spherical morphological structure. Rosemary-based nanoemulgel displayed acceptable physicochemical characterizations namely; a neutral pH value of 6.7±0.15, high drug content (92.9± 2.3%), and controlled metformin in-vitro release. Besides, the formulated nanoemulgel significantly increased the number of hair follicles in the animal model compared with other controls and tested groups.

CONCLUSION: The designed nanoemulgel is a promising approach for treating androgenic alopecia.

PMID:39835177 | PMC:PMC11745075 | DOI:10.2147/IJN.S500487

Front Pharmacol. 2025 Jan 6;15:1503490. doi: 10.3389/fphar.2024.1503490. eCollection 2024.

ABSTRACT

Hepatocellular carcinoma (HCC) is a major medical challenge due to its high incidence and poor prognosis. 5-Fluorouracil (5-FU), although extensively studied in the treatment of HCC and other solid tumors, has limited application as a first-line therapy for HCC due to its resistance and significant inter-patient variability. To address these issues, researchers have explored drug repurposing. One of our key findings in this endeavour was the potent anti-HCC effect of the natural product Salidroside (Sal) when co-administered with 5-FU. Sal was found to inhibit mitosis and promote cellular senescence in HCC cells via a mechanism distinct from 5-FU, specifically by inducing excessive mitophagy that led to cellular mitochondrial dysfunction. Importantly, YIPF5 was confirmed as a potential molecular target of Sal. This natural product modulated YIPF5-induced mitophagy and influenced both mitosis and senescence in HCC cells. The combination of Sal and 5-FU demonstrated significant therapeutic effects in a mouse HCC model. In conclusion, our study was not only in line with the innovative strategy of drug repurposing, but also important for drug design and natural product screening targeting the relevant pathways.

PMID:39834805 | PMC:PMC11743563 | DOI:10.3389/fphar.2024.1503490

Nat Neurosci. 2025 Jan 20. doi: 10.1038/s41593-024-01834-w. Online ahead of print.

ABSTRACT

Psychiatric disorders are multifactorial and effective treatments are lacking. Probable contributing factors to the challenges in therapeutic development include the complexity of the human brain and the high polygenicity of psychiatric disorders. Combining well-powered genome-wide and brain-wide genetics and transcriptomics analyses can deepen our understanding of the etiology of psychiatric disorders. Here, we leverage two landmark resources to infer the cell types involved in the etiology of schizophrenia, other psychiatric disorders and informative comparison of brain phenotypes. We found both cortical and subcortical neuronal associations for schizophrenia, bipolar disorder and depression. These cell types included somatostatin interneurons, excitatory neurons from the retrosplenial cortex and eccentric medium spiny-like neurons from the amygdala. In contrast we found T cell and B cell associations with multiple sclerosis and microglial associations with Alzheimer's disease. We provide a framework for a cell-type-based classification system that can lead to drug repurposing or development opportunities and personalized treatments. This work formalizes a data-driven, cellular and molecular model of complex brain disorders.

PMID:39833308 | DOI:10.1038/s41593-024-01834-w

Sci Rep. 2025 Jan 20;15(1):2581. doi: 10.1038/s41598-024-79377-0.

ABSTRACT

Human organic cation transporter 2 (hOCT2/SLC22A2) is a key drug transporter that facilitates the transport of endogenous and exogenous organic cations. Because hOCT2 is responsible for the development of adverse effects caused by platinum-based anti-cancer agents, drugs with OCT2 inhibitory effects may serve as prophylactic agents against the toxicity of platinum-based anti-cancer agents. In the present study, we established a machine learning-based quantitative structure-activity relationship (QSAR) model for hOCT2 inhibitors based on the public ChEMBL database and explored novel hOCT2 inhibitors among the FDA-approved drugs. Using our QSAR model, we identified 162 candidate hOCT2 inhibitors among the FDA-approved drugs registered in the DrugBank database. After manual selection and in vitro assays, we found that dequalinium, a quaternary ammonium cation antimicrobial agent, is a potent hOCT2 inhibitor (IC50 = 88.16 ± 7.14 nM). Moreover, dequalinium inhibited hOCT2-mediated transport of platinum anti-cancer agents (cisplatin and oxaliplatin) in a concentration-dependent manner. Our study is the first to demonstrate the construction of a novel machine learning-based QSAR model for hOCT2 inhibitors and identify a novel hOCT2 inhibitor among FDA-approved drugs using this model.

PMID:39833227 | DOI:10.1038/s41598-024-79377-0