{"title":"Bioinformatics tools for drug repurposing: a tutorial using heart failure as a case study","authors":"Ivo Fonseca , Fábio Trindade , Mário Santos , Adelino Leite-Moreira , Daniel Moreira-Gonçalves , Rui Vitorino , Rita Ferreira , Rita Nogueira-Ferreira","doi":"10.1016/j.jmccpl.2025.100460","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>Drug repurposing is a crucial strategy for researchers worldwide to accelerate drug development and mitigate associated risks and costs. Heart failure (HF) is a major global health problem with high prevalence and mortality rates. There are significant sex differences in HF, including in the risk factors and phenotype, which demand a sex-personalized drug treatment. A convenient approach in that direction is the reuse of drugs already approved for other conditions that are known to interact in sex-biased dysregulated pathways in HF. Numerous bioinformatics tools can help identify those candidates. This tutorial explores the utility of specific bioinformatics tools in identifying drugs to treat HF as a case study.</div></div><div><h3>Methods</h3><div>Herein, we explain how NeDRex helps identify genes associated with disease and drug repurposing and how functional enrichment analysis can be performed with ShinyGO. We also explain how to predict targets of small bioactive molecules with SwissTargetPrediction and how to retrieve known and predicted interactions between chemicals and proteins with STITCH.</div></div><div><h3>Results</h3><div>The tutorial demonstrates the use of these tools in searching for new HF treatments.</div></div><div><h3>Conclusion</h3><div>This tutorial is designed to ease entry into the utilization of the mentioned bioinformatics tools. This approach can also set a precedent for applying such tools to other diseases. The results presented in this tutorial are illustrative and do not constitute definitive evidence. They are intended for demonstration purposes only.</div></div>","PeriodicalId":73835,"journal":{"name":"Journal of molecular and cellular cardiology plus","volume":"13 ","pages":"Article 100460"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of molecular and cellular cardiology plus","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772976125001795","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
Drug repurposing is a crucial strategy for researchers worldwide to accelerate drug development and mitigate associated risks and costs. Heart failure (HF) is a major global health problem with high prevalence and mortality rates. There are significant sex differences in HF, including in the risk factors and phenotype, which demand a sex-personalized drug treatment. A convenient approach in that direction is the reuse of drugs already approved for other conditions that are known to interact in sex-biased dysregulated pathways in HF. Numerous bioinformatics tools can help identify those candidates. This tutorial explores the utility of specific bioinformatics tools in identifying drugs to treat HF as a case study.
Methods
Herein, we explain how NeDRex helps identify genes associated with disease and drug repurposing and how functional enrichment analysis can be performed with ShinyGO. We also explain how to predict targets of small bioactive molecules with SwissTargetPrediction and how to retrieve known and predicted interactions between chemicals and proteins with STITCH.
Results
The tutorial demonstrates the use of these tools in searching for new HF treatments.
Conclusion
This tutorial is designed to ease entry into the utilization of the mentioned bioinformatics tools. This approach can also set a precedent for applying such tools to other diseases. The results presented in this tutorial are illustrative and do not constitute definitive evidence. They are intended for demonstration purposes only.