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Demonstration Study: A Protocol to Combine Online Tools and Databases for Identifying Potentially Repurposable Drugs

Chattopadhyay, Aditi and Ganapathiraju, Madhavi (2017) Demonstration Study: A Protocol to Combine Online Tools and Databases for Identifying Potentially Repurposable Drugs. Data, 2 (2). ISSN 2306-5729

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Traditional methods for discovery and development of new drugs can be very time-consuming and expensive processes because they include several stages, such as compound identification, pre-clinical and clinical trials before the drug is approved by the U.S. Food and Drug Administration (FDA). Therefore, drug repurposing, namely using currently FDA-approved drugs as therapeutics for other diseases than what they are originally prescribed for, is emerging to be a faster and more cost-effective alternative to current drug discovery methods. In this paper, we have described a three-step in silico protocol for analyzing transcriptomics data using online databases and bioinformatics tools for identifying potentially repurposable drugs. The efficacy of this protocol was evaluated by comparing its predictions with the findings of two case studies of recently reported repurposed drugs: HIV treating drug zidovudine for the treatment of dry age-related macular degeneration and the antidepressant imipramine for small-cell lung carcinoma. The proposed protocol successfully identified the published findings, thus demonstrating the efficacy of this method. In addition, it also yielded several novel predictions that have not yet been published, including the finding that imipramine could potentially treat Severe Acute Respiratory Syndrome (SARS), a disease that currently does not have any treatment or vaccine. Since this in silico protocol is simple to use and does not require advanced computer skills, we believe any motivated participant with access to these databases and tools would be able to apply it to large datasets to identify other potentially repurposable drugs in the future


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Chattopadhyay, Aditi
Ganapathiraju, Madhavimadhavi@pitt.edumadhavi
Date: 4 May 2017
Date Type: Publication
Journal or Publication Title: Data
Volume: 2
Number: 2
Publisher: MDPI AG
DOI or Unique Handle: 10.3390/data2020015
Schools and Programs: School of Medicine > Biomedical Informatics
Refereed: Yes
Uncontrolled Keywords: drug repurposing; translational bioinformatics; transcriptomics; transcriptome analysis; drug discovery; computational protocol; gene expression
ISSN: 2306-5729
Official URL:
Article Type: Research Article
Date Deposited: 19 Jan 2021 16:51
Last Modified: 19 Jan 2021 16:51


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