TY - GEN
T1 - Mapping drug-target interaction networks
AU - Tian, Longzhang
AU - Zhang, Shuxing
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77950987624&partnerID=8YFLogxK
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U2 - 10.1109/IEMBS.2009.5335053
DO - 10.1109/IEMBS.2009.5335053
M3 - Conference contribution
C2 - 19965180
AN - SCOPUS:77950987624
SN - 9781424432967
T3 - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
SP - 2336
EP - 2339
BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - IEEE Computer Society
T2 - 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Y2 - 2 September 2009 through 6 September 2009
ER -