2011年2月
Mining Significant Substructure Pairs for Interpreting Polypharmacology in Drug-Target Network
PLOS ONE
- ,
- ,
- 巻
- 6
- 号
- 2
- 開始ページ
- e16999
- 終了ページ
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1371/journal.pone.0016999
- 出版者・発行元
- PUBLIC LIBRARY SCIENCE
A current key feature in drug-target network is that drugs often bind to multiple targets, known as polypharmacology or drug promiscuity. Recent literature has indicated that relatively small fragments in both drugs and targets are crucial in forming polypharmacology. We hypothesize that principles behind polypharmacology are embedded in paired fragments in molecular graphs and amino acid sequences of drug-target interactions. We developed a fast, scalable algorithm for mining significantly co-occurring subgraph-subsequence pairs from drug-target interactions. A noteworthy feature of our approach is to capture significant paired patterns of subgraph-subsequence, while patterns of either drugs or targets only have been considered in the literature so far. Significant substructure pairs allow the grouping of drug-target interactions into clusters, covering approximately 75% of interactions containing approved drugs. These clusters were highly exclusive to each other, being statistically significant and logically implying that each cluster corresponds to a distinguished type of polypharmacology. These exclusive clusters cannot be easily obtained by using either drug or target information only but are naturally found by highlighting significant substructure pairs in drug-target interactions. These results confirm the effectiveness of our method for interpreting polypharmacology in drug-target network.
- リンク情報
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- DOI
- https://doi.org/10.1371/journal.pone.0016999
- CiNii Articles
- http://ci.nii.ac.jp/naid/120002949745
- PubMed
- https://www.ncbi.nlm.nih.gov/pubmed/21373195
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000287657500026&DestApp=WOS_CPL
- ID情報
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- DOI : 10.1371/journal.pone.0016999
- ISSN : 1932-6203
- CiNii Articles ID : 120002949745
- PubMed ID : 21373195
- Web of Science ID : WOS:000287657500026