Computational drug repurposing to predict approved and novel drug-disease associations

Khalid, Zoya and Sezerman, Osman Ugur (2018) Computational drug repurposing to predict approved and novel drug-disease associations. Journal of Molecular Graphics and Modelling, 85 . pp. 91-96. ISSN 1093-3263 (Print) 1873-4243 (Online)

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The Drug often binds to more than one targets defined as polypharmacology, one application of which is drug repurposing also referred as drug repositioning or therapeutic switching. The traditional drug discovery and development is a high-priced and tedious process, thus making drug repurposing a popular alternate strategy. We proposed an integrative method based on similarity scheme that predicts approved and novel Drug targets with new disease associations. We combined PPI, biological pathways, binding site structural similarities and disease-disease similarity measures. The results showed 94% Accuracy with 0.93 Recall and 0.94 Precision measure in predicting the approved and novel targets surpassing the existing methods. All these parameters help in elucidating the unknown associations between drug and diseases for finding the new uses for old drugs.
Item Type: Article
Uncontrolled Keywords: Binding site similarity; Common pathways; Drug promiscuity; Drug repositioning; Drug repurposing; Integrative method; Multiple data sources; Similarity measures
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Zoya Khalid
Date Deposited: 03 Jun 2023 21:53
Last Modified: 03 Jun 2023 21:53

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