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A novel paradigm for potential drug-targets discovery: quantifying relationships of enzymes and cascade interactions of neighboring biological processes to identify drug-targets

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Back cover

Molecular BioSystems Vol - 7 Issue - 3

Molecular BioSystems Vol - 7 Issue - 2

Molecular BioSystems Vol -6

Molecular BioSystems Vol -5

Molecular BioSystems Vol -4

Molecular BioSystems Vol -3

Molecular BioSystems Vol -2

A novel paradigm for potential drug-targets discovery: quantifying relationships of enzymes and cascade interactions of neighboring biological processes to identify drug-targets

Content Provider	Royal Society of Chemistry (RSC)
Author	Li, Wan Li, Xu Chen, Lina Wang, Hong Wang, Qian He, Weiming Zhang, Liangcai Li, Xia Tai, Jingxie
Copyright Year	2011
Abstract	Target discovery is the most crucial step in a modern drug discovery development. Our objective in this study is to propose a novel paradigm for a better discrimination of drug-targets and non-drug-targets with minimum disruptive side-effects under a biological pathway context. We introduce a novel metric, namely, “pathway closeness centrality”, for each gene that jointly considers the relationships of its neighboring enzymes and cross-talks of biological processes, to evaluate its probability of being a drug-target. This metric could distinguish drug-targets with non-drug-targets. Genes with lower pathway closeness centrality values are prone to play marginal roles in biological processes and have less lethality risk, but appear to have tissue-specific expressions. Compared with traditional metrics, our method outperforms degree, betweenness and bridging centrality under the human pathway context. Analysis of the existing top 20 drugs with the most disruptive side-effects indicates that pathway closeness centrality is an appropriate index to predict the probability of the occurrence of adverse pharmacological effects. Case studies in prostate cancer and type 2 diabetes mellitus indicate that the pathway closeness centrality metric could distinguish likely drug-targets well from human pathways. Thus, our method is a promising tool to aid target identification in drug discovery.
Starting Page	1033
Ending Page	1041
Page Count	9
File Format	HTM / HTML PDF
ISSN	1742206X
Volume Number	7
Issue Number	4
Journal	Molecular BioSystems
DOI	10.1039/c0mb00249f
Language	English
Publisher	Royal Society of Chemistry
Access Restriction	Open
Subject Keyword	Gene Centrality Drug discovery Prostate cancer Diabetes mellitus type 2 Biological pathway
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biotechnology

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