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Computational Methods for Drug Re-positioning

McGarry, Kenneth, Rashid, Anaum and Smith, Hannah (2016) Computational Methods for Drug Re-positioning. Drug Target Review, 3. pp. 31-33. ISSN 2059-1349

Item Type: Article

Abstract

Bioinformatics and computationally based techniques are now experiencing increased attention as a means of improving the costly and time consuming drug development process. Recently, drug repositioning has been suggested as an interim way of harnessing existing drugs to different diseases or medical conditions than the original target. The numerous online databases of chemical, protein interactions, side-effects, drug mechanisms and drug toxicology information make drug repurposing a suitable application area for computational intelligence. Thus in-silico analysis can be used as a useful first stage to screen potential candidate drugs for possible redeployment. We hypothesize that the side-effects of the current Alzheimer’s drugs can be used to screen the SIDER (side-effects) database for potential drug candidates with similar side-effects, that is to say they are probably affecting the same protein targets. Thus, a previously harmful situation has been turned into a mechanism for drug re-positioning. Our system uses complex graph network techniques to analyze drugs with known side effects and compares the proteins involved in these side-effects with proteins known to be identified with other diseases. Our intention is to find potential candidates for treating Alzheimer's disease.

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More Information

Depositing User: Kenneth McGarry

Identifiers

Item ID: 6107
ISSN: 2059-1349
URI: http://sure.sunderland.ac.uk/id/eprint/6107
Official URL: https://www.drugtargetreview.com/article/33392/com...

Users with ORCIDS

ORCID for Kenneth McGarry: ORCID iD orcid.org/0000-0002-9329-9835

Catalogue record

Date Deposited: 21 Mar 2016 09:55
Last Modified: 02 Jun 2021 11:08

Contributors

Author: Kenneth McGarry ORCID iD
Author: Anaum Rashid
Author: Hannah Smith

University Divisions

Faculty of Technology
Faculty of Technology > School of Computer Science

Subjects

Sciences > Biomedical Sciences
Computing > Databases
Sciences > Health Sciences

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