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https://doi.org/10.1109/iembs....
Article . 2009 . Peer-reviewed
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Mapping drug-target interaction networks

Authors: Longzhang Tian,; Shuxing Zhang,;

Mapping drug-target interaction networks

Abstract

Molecular polypharmacological studies have gained more and more attention as they are important in predicting drug off-target properties and potential toxicity/side effect. The explosive growth of biomedical data provides us an opportunity to develop novel strategies to conduct such studies by analyzing molecular interaction networks. In this paper, we present an integrated web application that is implemented based on more than 5,000 drugs and 56,000 biological macromolecule structures. With efficient search of drug information (biological targets, pharmacology, side effect, etc.) and chemical similarity, molecular maps can be constructed to demonstrate the relationships among multiple drugs and receptors. In addition, receptor information can also be employed to map the interaction network. The 3D structures of available drug-receptor complexes can be visualized via our web server, and the query results will be used to identify similar structures for any given drugs as well as their cross interactions with other biological targets. Our implementation provides an efficient way to evaluate the safety and polypharmacological properties of chemical compounds.

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Keywords

Internet, Binding Sites, Databases, Factual, Protein Conformation, Chemistry, Pharmaceutical, Computational Biology, User-Computer Interface, Drug Design, Drug Discovery, Protein Interaction Mapping, Computer Graphics, Humans, Computer Simulation, Databases, Protein, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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