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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.. null, 4.
Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.lukas@ebi.ac.ukEMBL-EBIDrugs 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.Finding multiple target optimal intervention in disease-related molecular network.Yang Kun K, Bai Hongjun H, Ouyang Qi Q, Lai Luhua L, Tang Chao Cpolynuclear neutrophilic leukocyte, neutrocyte, mature neutrophilic leucocyte, neutrophilic leucocyte, mature neutrophil leucocyte, mature neutrophil leukocyte, 2610206D02Rik, polymorphonuclear leukocyte, polynuclear neutrophilic leucocyte, neutrophil leukocyte, neutrophil leucocyte, PMN, C530005D02Rik, pmn, polymorphonuclear leucocyte, mature neutrophilic leukocyte, mature neutrocyte, polymorphonuclear neutrophil., poly, neutrophilic leukocyteother disease, Inflammatory Response, Rofecoxib, dmBest1, Inflammations, Procedures, conformation, InChI=1/C17H14O4S/c1-22(19, Vioxx, number, 4-[4-(methylsulfonyl)phenyl]-3-phenyl-2(5H)-furanone, side effects, anon-WO0118547.380, CS(=O)(=O)c1ccc(cc1)C1=C(C(=O)OC1)c1ccccc1, DmelCG6264, 11H2, antiinflammatory agent, 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This is the arachidonic acid metabolic network model for human polymorphonuclear leukocyte (PMN) described in the article:
Finding multiple target optimal intervention in disease-related molecular network.
Yang K, Bai H, Ouyang Q, Lai L, Tang C. Mol Syst Biol.
2008;4:228. Epub 2008 Nov 4.; PMID: 18985027
,doi: 10.1038/msb.2008.60
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.
In this version of the model the parameter names have been slightly changed from the ones in the supplementary material of the article ( Supplementary Information 1
).
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2011-03-032005-01-012008-12-02MODEL823644188718985027MODEL82364418879606BTO:0000089