AI Article Synopsis
- Recent data on small-molecule drugs and protein targets challenges the traditional view of drug-target interactions, highlighting the complexity of these relationships.
- Network theory has emerged as a powerful tool for visualizing and analyzing drug-target connections, gaining popularity in chemical biology and molecular informatics.
- The article surveys recent applications of drug-target networks for identifying cross-pharmacology relationships and new drug targets, while also addressing limitations like incomplete interaction data and information loss in simplifying these networks.
Article Abstract
Far from the traditional view of selective drug-target interactions, the recent accumulation of large amounts of interaction data for small-molecule drugs and protein targets requires innovative visualisation and analysis tools that are able to deal with what has become a truly complex system. In this context, network theory offers both a robust and illustrative framework to investigate drug-target connections and has been swiftly and widely embraced by the chemical biology and molecular informatics communities. A survey of the most recent applications of drug-target networks to detect cross-pharmacology relationships among targets and to identify new targets for known drugs is provided. Finally, some of the current limitations are also discussed, including the actual completeness of interaction data and the information loss intrinsically associated with the one-mode projection of drug-target networks.
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| http://dx.doi.org/10.1002/minf.200900069 | DOI Listing |
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