title: Prediction of drugs having opposite effects on disease genes in a directed network.
abstract: BACKGROUND
  Developing novel uses of approved drugs, called drug repositioning, can reduce costs and times in traditional drug development. Network-based approaches have presented promising results in this field. However, even though various types of interactions such as activation or inhibition exist in drug-target interactions and molecular pathways, most of previous network-based studies disregarded this information.
  
  
  METHODS
  We developed a novel computational method, Prediction of Drugs having Opposite effects on Disease genes (PDOD), for identifying drugs having opposite effects on altered states of disease genes. PDOD utilized drug-drug target interactions with 'effect type', an integrated directed molecular network with 'effect type' and 'effect direction', and disease genes with regulated states in disease patients. With this information, we proposed a scoring function to discover drugs likely to restore altered states of disease genes using the path from a drug to a disease through the drug-drug target interactions, shortest paths from drug targets to disease genes in molecular pathways, and disease gene-disease associations.
  
  
  RESULTS
  We collected drug-drug target interactions, molecular pathways, and disease genes with their regulated states in the diseases. PDOD is applied to 898 drugs with known drug-drug target interactions and nine diseases. We compared performance of PDOD for predicting known therapeutic drug-disease associations with the previous methods. PDOD outperformed other previous approaches which do not exploit directional information in molecular network. In addition, we provide a simple web service that researchers can submit genes of interest with their altered states and will obtain drugs seeming to have opposite effects on altered states of input genes at http://gto.kaist.ac.kr/pdod/index.php/main .
  
  
  CONCLUSIONS
  Our results showed that 'effect type' and 'effect direction' information in the network based approaches can be utilized to identify drugs having opposite effects on diseases. Our study can offer a novel insight into the field of network-based drug repositioning.
authors.affiliation: Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. hasuniii@kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. hasuniii@kaist.ac.kr.
authors.forename: Hasun
authors.initials: H
authors.lastname: Yu
authors.affiliation: Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. sjchu@biosoft.kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. sjchu@biosoft.kaist.ac.kr.
authors.forename: Sungji
authors.initials: S
authors.lastname: Choo
authors.affiliation: Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. junseokpark@biosoft.kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. junseokpark@biosoft.kaist.ac.kr.
authors.forename: Junseok
authors.initials: J
authors.lastname: Park
authors.affiliation: Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. jmjung@biosoft.kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. jmjung@biosoft.kaist.ac.kr.
authors.forename: Jinmyung
authors.initials: J
authors.lastname: Jung
authors.affiliation: Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. yeeok@biosoft.kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. yeeok@biosoft.kaist.ac.kr.
authors.forename: Yeeok
authors.initials: Y
authors.lastname: Kang
authors.affiliation: Department of Bio and Brain Engineering, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. dhlee@biosoft.kaist.ac.kr.|Bio-Synergy Research Center, 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea. dhlee@biosoft.kaist.ac.kr.
authors.forename: Doheon
authors.initials: D
authors.lastname: Lee
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D004347:Drug Interactions; D058492:Drug Repositioning / Q000379:methods*; D004358:Drug Therapy; D006801:Humans
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