Finding multiple target optimal intervention in disease-related molecular network

Kun Yang, Hongjun Bai, Qi Ouyang, Luhua Lai, Chao Tang

Research output: Contribution to journalArticlepeer-review

Abstract

Drugs against multiple targets may overcome the many limitations of single targets and achieve a more effective and safer control of the disease. Numerous high-throughput experiments have been performed in this emerging field. However, systematic identification of multiple drug targets and their best intervention requires knowledge of the underlying disease network and calls for innovative computational methods that exploit the network structure and dynamics. Here, we develop a robust computational algorithm for finding multiple target optimal intervention (MTOI) solutions in a disease network. MTOI identifies potential drug targets and suggests optimal combinations of the target intervention that best restore the network to a normal state, which can be customer designed. We applied MTOI to an inflammation-related network. The well-known side effects of the traditional non-steriodal anti-inflammatory drugs and the recently recalled Vioxx were correctly accounted for in our network model. A number of promising MTOI solutions were found to be both effective and safer.

Original languageEnglish (US)
Article number228
JournalMolecular systems biology
Volume4
DOIs
StatePublished - 2008
Externally publishedYes

Keywords

  • Anti-inflammatory
  • Arachidonic acid metabolic network
  • Drug efficacy prediction
  • Multiple target drug design
  • Network-based drug design

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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