What is it about?
The concept behind this was simple - can we describe computational approaches that would be useful for repurposing drugs. The mention of neglected and rare disease brought attention to these areas in this context. We describe pharmacophores, databases searching, machine learning methods that could be used for repositioning alongside in vitro efforts.
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Why is it important?
Using published data to build models that could be used to score libraries of FDA approved drugs represents one approach to finding new users for an endpoint for which there is data to build predictive models. The article also provides a large number of examples of molecules identified with new uses using low throughput or HTS or even computational approaches.
Perspectives
Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations. This article also lead to rare disease groups contacting me and ultimately to a greater involvement in rare disease research.
Dr Sean Ekins
Collaborations in Chemistry
Read the Original
This page is a summary of: In silico repositioning of approved drugs for rare and neglected diseases, Drug Discovery Today, April 2011, Elsevier,
DOI: 10.1016/j.drudis.2011.02.016.
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