Systematic identification of proteins that elicit drug side effects

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Systematic identification of proteins that elicit drug side effects. / Kuhn, Michael; Al Banchaabouchi, Mumna; Campillos, Monica; Jensen, Lars Juhl; Gross, Cornelius; Gavin, Anne-Claude; Bork, Peer.

In: Molecular Systems Biology, Vol. 9, 30.04.2013, p. 663.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Kuhn, M, Al Banchaabouchi, M, Campillos, M, Jensen, LJ, Gross, C, Gavin, A-C & Bork, P 2013, 'Systematic identification of proteins that elicit drug side effects', Molecular Systems Biology, vol. 9, pp. 663. https://doi.org/10.1038/msb.2013.10

APA

Kuhn, M., Al Banchaabouchi, M., Campillos, M., Jensen, L. J., Gross, C., Gavin, A-C., & Bork, P. (2013). Systematic identification of proteins that elicit drug side effects. Molecular Systems Biology, 9, 663. https://doi.org/10.1038/msb.2013.10

Vancouver

Kuhn M, Al Banchaabouchi M, Campillos M, Jensen LJ, Gross C, Gavin A-C et al. Systematic identification of proteins that elicit drug side effects. Molecular Systems Biology. 2013 Apr 30;9:663. https://doi.org/10.1038/msb.2013.10

Author

Kuhn, Michael ; Al Banchaabouchi, Mumna ; Campillos, Monica ; Jensen, Lars Juhl ; Gross, Cornelius ; Gavin, Anne-Claude ; Bork, Peer. / Systematic identification of proteins that elicit drug side effects. In: Molecular Systems Biology. 2013 ; Vol. 9. pp. 663.

Bibtex

@article{5f4b24cfb2d2470a88837437825a2b03,
title = "Systematic identification of proteins that elicit drug side effects",
abstract = "Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.",
author = "Michael Kuhn and {Al Banchaabouchi}, Mumna and Monica Campillos and Jensen, {Lars Juhl} and Cornelius Gross and Anne-Claude Gavin and Peer Bork",
year = "2013",
month = apr,
day = "30",
doi = "10.1038/msb.2013.10",
language = "English",
volume = "9",
pages = "663",
journal = "Molecular Systems Biology",
issn = "1744-4292",
publisher = "Wiley-Blackwell",

}

RIS

TY - JOUR

T1 - Systematic identification of proteins that elicit drug side effects

AU - Kuhn, Michael

AU - Al Banchaabouchi, Mumna

AU - Campillos, Monica

AU - Jensen, Lars Juhl

AU - Gross, Cornelius

AU - Gavin, Anne-Claude

AU - Bork, Peer

PY - 2013/4/30

Y1 - 2013/4/30

N2 - Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.

AB - Side effect similarities of drugs have recently been employed to predict new drug targets, and networks of side effects and targets have been used to better understand the mechanism of action of drugs. Here, we report a large-scale analysis to systematically predict and characterize proteins that cause drug side effects. We integrated phenotypic data obtained during clinical trials with known drug-target relations to identify overrepresented protein-side effect combinations. Using independent data, we confirm that most of these overrepresentations point to proteins which, when perturbed, cause side effects. Of 1428 side effects studied, 732 were predicted to be predominantly caused by individual proteins, at least 137 of them backed by existing pharmacological or phenotypic data. We prove this concept in vivo by confirming our prediction that activation of the serotonin 7 receptor (HTR7) is responsible for hyperesthesia in mice, which, in turn, can be prevented by a drug that selectively inhibits HTR7. Taken together, we show that a large fraction of complex drug side effects are mediated by individual proteins and create a reference for such relations.

U2 - 10.1038/msb.2013.10

DO - 10.1038/msb.2013.10

M3 - Journal article

C2 - 23632385

VL - 9

SP - 663

JO - Molecular Systems Biology

JF - Molecular Systems Biology

SN - 1744-4292

ER -

ID: 45697978