Two-stage flux balance analysis of metabolic networks for drug target identification

doi:10.1186/1752-0509-5-S1-S11

CSpace > 应用数学研究所

	Two-stage flux balance analysis of metabolic networks for drug target identification
	Li, Zhenping 2; Wang, Rui-Sheng 3; Zhang, Xiang-Sun1
	2011-06-20
发表期刊	BMC SYSTEMS BIOLOGY
ISSN	1752-0509
卷号	5 页码:11
摘要	Background: Efficient identification of drug targets is one of major challenges for drug discovery and drug development. Traditional approaches to drug target identification include literature search-based target prioritization and in vitro binding assays which are both time-consuming and labor intensive. Computational integration of different knowledge sources is a more effective alternative. Wealth of omics data generated from genomic, proteomic and metabolomic techniques changes the way researchers view drug targets and provides unprecedent opportunities for drug target identification. Results: In this paper, we develop a method based on flux balance analysis (FBA) of metabolic networks to identify potential drug targets. This method consists of two linear programming (LP) models, which first finds the steady optimal fluxes of reactions and the mass flows of metabolites in the pathologic state and then determines the fluxes and mass flows in the medication state with the minimal side effect caused by the medication. Drug targets are identified by comparing the fluxes of reactions in both states and examining the change of reaction fluxes. We give an illustrative example to show that the drug target identification problem can be solved effectively by our method, then apply it to a hyperuricemia-related purine metabolic pathway. Known drug targets for hyperuricemia are correctly identified by our two-stage FBA method, and the side effects of these targets are also taken into account. A number of other promising drug targets are found to be both effective and safe. Conclusions: Our method is an efficient procedure for drug target identification through flux balance analysis of large-scale metabolic networks. It can generate testable predictions, provide insights into drug action mechanisms and guide experimental design of drug discovery.
DOI	10.1186/1752-0509-5-S1-S11
语种	英语
资助项目	NSFC[10631070] ; NSFC[60873205] ; NSFC[10701080] ; Beijing Natural Science Foundation[1092011] ; Foundation of Beijing Education Commission[SM200910037005] ; Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality[(PHR201006217)] ; Funding Project for Base Construction of Scientific Research of Beijing Municipal Commission of Education[(WYJD200902)]
WOS研究方向	Mathematical & Computational Biology
WOS类目	Mathematical & Computational Biology
WOS记录号	WOS:000297313700010
出版者	BIOMED CENTRAL LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/243
专题	应用数学研究所
通讯作者	Zhang, Xiang-Sun
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China 2.Beijing Wuzi Univ, Sch Informat, Beijing 101149, Peoples R China 3.Penn State Univ, Dept Phys, University Pk, PA 16802 USA
推荐引用方式 GB/T 7714	Li, Zhenping,Wang, Rui-Sheng,Zhang, Xiang-Sun. Two-stage flux balance analysis of metabolic networks for drug target identification[J]. BMC SYSTEMS BIOLOGY,2011,5:11.
APA	Li, Zhenping,Wang, Rui-Sheng,&Zhang, Xiang-Sun.(2011).Two-stage flux balance analysis of metabolic networks for drug target identification.BMC SYSTEMS BIOLOGY,5,11.
MLA	Li, Zhenping,et al."Two-stage flux balance analysis of metabolic networks for drug target identification".BMC SYSTEMS BIOLOGY 5(2011):11.