Large-scale prediction of drug-target relationships

被引：66

作者：

Kuhn, Michael ^{[1
]}

Campillos, Monica ^{[1
]}

Gonzalez, Paula ^{[1
]}

Jensen, Lars Juhl ^{[1
,2
]}

Bork, Peer ^{[1
,3
]}

机构：

[1] European Mol Biol Lab, D-69117 Heidelberg, Germany

[2] Univ Copenhagen, Novo Nordisk Fdn Ctr Protein Res, DK-2200 Copenhagen, Denmark

[3] Max Delbruck Ctr Mol Med, D-13092 Berlin, Germany

来源：

FEBS LETTERS | 2008年 / 582卷 / 08期

关键词：

drug-target interaction; small-molecule network; drug discovery; target prediction;

D O I：

10.1016/j.febslet.2008.02.024

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

The rapidly increasing amount of publicly available knowledge in biology and chemistry enables scientists to revisit many open problems by the systematic integration and analysis of heterogeneous novel data. The integration of relevant data does not only allow analyses at the network level, but also provides a more global view on drug-target relations. Here we review recent attempts to apply large-scale computational analyses to predict novel interactions of drugs and targets from molecular and cellular features. In this context, we quantify the family-dependent probability of two proteins to bind the same ligand as function of their sequence similarity. We finally discuss how phenotypic data could help to expand our understanding of the complex mechanisms of drug action. (C) 2008 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

引用

页码：1283 / 1290

页数：8

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