Large-scale prediction of drug-target relationships

Michael Kuhn; Mónica Campillos; Paula González; Lars Juhl Jensen; Peer Bork

doi:10.1016/j.febslet.2008.02.024

Large-scale prediction of drug-target relationships

Michael Kuhn, Mónica Campillos, Paula González, Lars Juhl Jensen, Peer Bork

75 Citations (Scopus)

Abstract

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.

Original language	English
Journal	F E B S Letters
Volume	582
Issue number	8
Pages (from-to)	1283-90
Number of pages	8
ISSN	0014-5793
DOIs	https://doi.org/10.1016/j.febslet.2008.02.024
Publication status	Published - 2008

Keywords

Pharmaceutical Preparations
Proteins

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10.1016/j.febslet.2008.02.024

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abstract = "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.",

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T1 - Large-scale prediction of drug-target relationships

AU - Kuhn, Michael

AU - Campillos, Mónica

AU - González, Paula

AU - Jensen, Lars Juhl

AU - Bork, Peer

PY - 2008

Y1 - 2008

N2 - 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.

AB - 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.

KW - Pharmaceutical Preparations

KW - Proteins

U2 - 10.1016/j.febslet.2008.02.024

DO - 10.1016/j.febslet.2008.02.024

M3 - Journal article

C2 - 18291108

SN - 0014-5793

VL - 582

SP - 1283

EP - 1290

JO - F E B S Letters

JF - F E B S Letters

IS - 8

ER -

Large-scale prediction of drug-target relationships

Abstract

Keywords

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