Similar Datasets
Project description:The identification of new therapies for coronary artery disease (CAD) has been challenging due to its inherent molecular complexity, which involves thousands of genes acting within and across tissues and cells. Gene-regulatory networks (GRNs) address this complexity by providing a mechanistic framework for common disease etiologies. Using system genetics, we previously identified the human arterial wall specific GRN42 as a critical regulator of foam cell formation. In this study, we applied a GRN-driven drug repurposing method by combining transcriptional signatures resulting from the silencing of key drivers of GRN42 to drug-related gene expression profiles from the NIH LINCS Program. This analysis identified candidate compounds predicted to modulate foam cell formation. In vitro screenings of top-selected compounds confirmed the computational predictions and demonstrated the efficacy of auranofin — an FDA-approved gold salt compound for rheumatoid arthritis — in reducing foam cell formation. In vivo, auranofin reduced atherosclerosis progression and inflammation in mice and decreased inflammation and wall thickness in the rabbit atherosclerotic aorta, as measured by 18F-FDG PET/MRI. These findings suggest that a GRN-based drug repurposing approach, combined with in vitro and in vivo validation using translational molecular imaging, can uncover new uses for existing drugs, such as auranofin, for the treatment of CAD.
2026-04-01 | GSE293698 | GEO
Project description:The identification of new therapies for coronary artery disease (CAD) has been challenging due to its inherent molecular complexity, which involves thousands of genes acting within and across tissues and cells. Gene-regulatory networks (GRNs) address this complexity by providing a mechanistic framework for common disease etiologies. Using system genetics, we previously identified the human arterial wall specific GRN42 as a critical regulator of foam cell formation. In this study, we applied a GRN-driven drug repurposing method by combining transcriptional signatures resulting from the silencing of key drivers of GRN42 to drug-related gene expression profiles from the NIH LINCS Program. This analysis identified candidate compounds predicted to modulate foam cell formation. In vitro screenings of top-selected compounds confirmed the computational predictions and demonstrated the efficacy of auranofin — an FDA-approved gold salt compound for rheumatoid arthritis — in reducing foam cell formation. In vivo, auranofin reduced atherosclerosis progression and inflammation in mice and decreased inflammation and wall thickness in the rabbit atherosclerotic aorta, as measured by 18F-FDG PET/MRI. These findings suggest that a GRN-based drug repurposing approach, combined with in vitro and in vivo validation using translational molecular imaging, can uncover new uses for existing drugs, such as auranofin, for the treatment of CAD.
2026-04-01 | GSE293697 | GEO
Project description:Gene Regulatory Network-Driven Drug Repurposing Identifies Anti-Atherosclerotic Properties of Auranofin.
| PRJNA1246056 | ENA
Project description:Gene Regulatory Network-Driven Drug Repurposing Identifies Anti-Atherosclerotic Properties of Auranofin [dataset 2]
| PRJNA1246064 | ENA
Project description:Gene Regulatory Network-Driven Drug Repurposing Identifies Anti-Atherosclerotic Properties of Auranofin [dataset 1]
| PRJNA1246065 | ENA
Project description:Drug discovery, development and registration is an expensive and time-consuming process associated with a high failure rate [Pessetto et al. (Mol Cancer Ther 12:1299-1309, 2013), Woodcock and Woosley (Annu Rev Med 59:1-12, 2008)]. Drug 'repurposing' is the identification of new therapeutic purposes for already approved drugs and is more affordable and achievable than novel drug discovery [Pessetto et al. (Mol Cancer Ther 12:1299-1309, 2013)]. Auranofin is a drug that is approved for the treatment of rheumatoid arthritis but is being investigated for potential therapeutic application in a number of other diseases including cancer, neurodegenerative disorders, HIV/AIDS, parasitic infections and bacterial infections [Tejman-Yarden et al. (Antimicrob Agents Chemother 57:2029-2035, 2013)]. The main mechanism of action of auranofin is through the inhibition of reduction/oxidation (redox) enzymes that are essential for maintaining intracellular levels of reactive oxygen species. Inhibition of these enzymes leads to cellular oxidative stress and intrinsic apoptosis [Pessetto et al. (Mol Cancer Ther 12:1299-1309, 2013), Fan et al. (Cell Death Dis 5:e1191, 2014), Fiskus et al. (Cancer Res 74:2520-2532, 2014), Marzano et al. (Free Radic Biol Med 42:872-881, 2007)]. Drugs such as auranofin that have already been approved for human use [Tejman-Yarden et al. (Antimicrob Agents Chemother 57:2029-2035, 2013)] can be brought into clinical use for other diseases relatively quickly and for a fraction of the cost of new drugs.
| S-EPMC4359176 | biostudies-literature
Project description:While establishing worldwide collective immunity with anti SARS-CoV-2 vaccines, COVID-19 remains a major health issue with dramatic ensuing economic consequences. In the transition, repurposing existing drugs remains the fastest cost-effective approach to alleviate the burden on health services, most particularly by reducing the incidence of the acute respiratory distress syndrome associated with severe COVID-19. We undertook a computational repurposing approach to identify candidate therapeutic drugs to control progression towards severe airways inflammation during COVID-19. Molecular profiling data were obtained from public sources regarding SARS-CoV-2 infected epithelial or endothelial cells, immune dysregulations associated with severe COVID-19 and lung inflammation induced by other respiratory viruses. From these data, we generated a protein-protein interactome modeling the evolution of lung inflammation during COVID-19 from inception to an established cytokine release syndrome. This predictive model assembling severe COVID-19-related proteins supports a role for known contributors to the cytokine storm such as IL1β, IL6, TNFα, JAK2, but also less prominent actors such as IL17, IL23 and C5a. Importantly our analysis points out to alarmins such as TSLP, IL33, members of the S100 family and their receptors (ST2, RAGE) as targets of major therapeutic interest. By evaluating the network-based distances between severe COVID-19-related proteins and known drug targets, network computing identified drugs which could be repurposed to prevent or slow down progression towards severe airways inflammation. This analysis confirmed the interest of dexamethasone, JAK2 inhibitors, estrogens and further identified various drugs either available or in development interacting with the aforementioned targets. We most particularly recommend considering various inhibitors of alarmins or their receptors, currently receiving little attention in this indication, as candidate treatments for severe COVID-19.
| S-EPMC8297899 | biostudies-literature
Project description:Drug repositioning or repurposing, i.e. identifying new indications for existing drugs, has gained increasing attention in the recent years. This approach enables the scientists to discover "new targets" for known drugs in a cost and time efficient manner. Glycation, the non-enzymatic reaction of sugars with proteins or nucleic acids to form early glycation (Amadori or fructosamine) products, is a key molecular basis of diabetic complications. Inhibiting the process of non-enzymatic protein glycation is one of the key strategies to prevent glycation-mediated diabetic complications. The present study focuses on the anti-glycation activity of 18 drugs, commonly used for the treatment of gastrointestinal, central nervous system, inflammatory diseases, bacterial infections, and gout. This study was carried out by using two in-vitro protein anti-glycation assay models. Results revealed that nimesulide (3), a non-steroidal anti-inflammatory drug, possesses a good anti-glycation activity in in-vitro BSA-MG and BSA-glucose glycation models with IC50 values of 330.56 ± 2.90, and 145.46 ± 16.35 μM, respectively. Phloroglucinol dihydrate (11), a drug used for the treatment of gastrointestinal diseases, showed a weak activity in BSA-MG glycation model (IC50 = 654.89 ± 2.50 μM), while it showed a good activity in BSA-glucose assay (IC50 = 148.23 ± 0.15 μM). Trimethylphloroglucinol (9), a drug used for the treatment of pain related to functional disorders of the digestive and biliary tracts, also showed a good antiglycation activity in BSA-MG model (IC50 = 321.15 ± 1.26 μM), while it was found to be inactive in in-vitro BSA-glucose assay (IC50 = 12.95% inhibition). These activities of drugs were compared with the anti-glycation activity of the standard, rutin (IC50 = 294.5 ± 1.50 μM in BSA-MG glycation model, and IC50 = 86.94 ± 0.24 μM in BSA- glucose model). Rest of the drugs exhibited a relatively weak antiglycation activity. This study identifies nimesulide (3), and phloroglucinol dihydrate (11) as new inhibitors of in-vitro protein glycation for further investigations as potential anti-diabetic agents.
| S-EPMC5754062 | biostudies-literature
Project description:Current antifungal therapies have limited effectiveness in treating invasive fungal infections. Furthermore, the development of new antifungal is currently unable to keep pace with the urgent demand for safe and effective new drugs. Auranofin, an FDA-approved drug for the treatment of rheumatoid arthritis, inhibits growth of a diverse array of clinical isolates of fungi and represents a new antifungal agent with a previously unexploited mechanism of action. In addition to auranofin's potent antifungal activity against planktonic fungi, this drug significantly reduces the metabolic activity of Candida cells encased in a biofilm. Unbiased chemogenomic profiling, using heterozygous S. cerevisiae deletion strains, combined with growth assays revealed three probable targets for auranofin's antifungal activity-mia40, acn9, and coa4. Mia40 is of particular interest given its essential role in oxidation of cysteine rich proteins imported into the mitochondria. Biochemical analysis confirmed auranofin targets the Mia40-Erv1 pathway as the drug inhibited Mia40 from interacting with its substrate, Cmc1, in a dose-dependent manner similar to the control, MB-7. Furthermore, yeast mitochondria overexpressing Erv1 were shown to exhibit resistance to auranofin as an increase in Cmc1 import was observed compared to wild-type yeast. Further in vivo antifungal activity of auranofin was examined in a Caenorhabditis elegans animal model of Cryptococcus neoformans infection. Auranofin significantly reduced the fungal load in infected C. elegans. Collectively, the present study provides valuable evidence that auranofin has significant promise to be repurposed as a novel antifungal agent and may offer a safe, effective, and quick supplement to current approaches for treating fungal infections.
| S-EPMC5241286 | biostudies-literature
Project description:Numerous computational drug repurposing methods have emerged as efficient alternatives to costly and time-consuming traditional drug discovery approaches. Some of these methods are based on the assumption that the candidate drug should have a reversal effect on disease-associated genes. However, such methods are not applicable in the case that there is limited overlap between disease-related genes and drug-perturbed genes. In this study, we proposed a novel Drug Repurposing method based on the Inhibition Effect on gene regulatory network (DRIE) to identify potential drugs for cancer treatment. DRIE integrated gene expression profile and gene regulatory network to calculate inhibition score by using the shortest path in the disease-specific network. The results on eleven datasets indicated the superior performance of DRIE when compared to other state-of-the-art methods. Case studies showed that our method effectively discovered novel drug-disease associations. Our findings demonstrated that the top-ranked drug candidates had been already validated by CTD database. Additionally, it clearly identified potential agents for three cancers (colorectal, breast, and lung cancer), which was beneficial when annotating drug-disease relationships in the CTD. This study proposed a novel framework for drug repurposing, which would be helpful for drug discovery and development.
| S-EPMC10507583 | biostudies-literature