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

149 Scopus citations


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
StatePublished - 2008
Externally publishedYes


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

ASJC Scopus subject areas

  • General Agricultural and Biological Sciences
  • Information Systems
  • Applied Mathematics
  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • Computational Theory and Mathematics


Dive into the research topics of 'Finding multiple target optimal intervention in disease-related molecular network'. Together they form a unique fingerprint.

Cite this