A side effect resource to capture phenotypic effects of drugs

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

The molecular understanding of phenotypes caused by drugs in humans is essential for elucidating mechanisms of action and for developing personalized medicines. Side effects of drugs (also known as adverse drug reactions) are an important source of human phenotypic information, but so far research on this topic has been hampered by insufficient accessibility of data. Consequently, we have developed a public, computer-readable side effect resource (SIDER) that connects 888 drugs to 1450 side effect terms. It contains information on frequency in patients for one-third of the drug–side effect pairs. For 199 drugs, the side effect frequency of placebo administration could also be extracted. We illustrate the potential of SIDER with a number of analyses. The resource is freely available for academic research at http://sideeffects.embl.de.

Related collections

Most cited references 8

Record: found
Abstract: not found
Article: not found

Erectile dysfunction.

T F Lue (2000)

0 comments Cited 202 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

Stephen W. Davies, Jacques Hamon, Andreas Bender … (2007)

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments, and molecular studies going back more than forty years. In this work we explore PSP chemical space and its relevance for the prediction of adverse drug reactions. Firstly, in silico (computational) Bayesian models for 70 PSP-related targets were built, which are able to detect 93% of the ligands binding at IC(50) < or = 10 microM at an overall correct classification rate of about 94%. Secondly, employing the World Drug Index (WDI), a model for adverse drug reactions was built directly based on normalized side-effect annotations in the WDI, which does not require any underlying functional knowledge. This is, to our knowledge, the first attempt to predict adverse drug reactions across hundreds of categories from chemical structure alone. On average 90% of the adverse drug reactions observed with known, clinically used compounds were detected, an overall correct classification rate of 92%. Drugs withdrawn from the market (Rapacuronium, Suprofen) were tested in the model and their predicted ADRs align well with known ADRs. The analysis was repeated for acetylsalicylic acid and Benperidol which are still on the market. Importantly, features of the models are interpretable and back-projectable to chemical structure, raising the possibility of rationally engineering out adverse effects. By combining PSP and ADR models new hypotheses linking targets and adverse effects can be proposed and examples for the opioid mu and the muscarinic M2 receptors, as well as for cyclooxygenase-1 are presented. It is hoped that the generation of predictive models for adverse drug reactions is able to help support early SAR to accelerate drug discovery and decrease late stage attrition in drug discovery projects. In addition, models such as the ones presented here can be used for compound profiling in all development stages.

0 comments Cited 74 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

ChemBank: a small-molecule screening and cheminformatics resource database

Kathleen Seiler, Gregory A. George, Mary Happ … (2008)

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector.

0 comments Cited 73 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Mol Syst Biol

Title: Molecular Systems Biology

Publisher: Nature Publishing Group

ISSN (Electronic): 1744-4292

Publication date Collection: 2010

Publication date (Electronic): 19 January 2010

Publication date PMC-release: 19 January 2010

Volume: 6

Page: 343

Affiliations

[1 ]Structural and Computational Biology Unit, European Molecular Biology Laboratory , Heidelberg, Germany

[2 ]Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen , Copenhagen, Denmark

[3 ]Max-Delbrück-Centre for Molecular Medicine , Berlin, Germany

Author notes

[a ]Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg 69117, Germany. Tel.: +49 6221 387 8526; Fax: +49 6221 387 517; bork@ 123456embl.de

[*]

Present address: Biotechnology Center, TU Dresden, 01062 Dresden, Germany

Article

Publisher Item ID: msb200998

DOI: 10.1038/msb.2009.98

PMC ID: 2824526

PubMed ID: 20087340

SO-VID: 66e1ff7d-323d-4e4b-a092-0d893c6fe6c2

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits distribution and reproduction in any medium, provided the original author and source are credited. Creation of derivative works is permitted but the resulting work may be distributed only under the same or similar licence to this one. This licence does not permit commercial exploitation without specific permission.

A side effect resource to capture phenotypic effects of drugs

Read this article at

Abstract

Related collections

Drug Repurposing

Most cited references 8

Erectile dysfunction.

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

ChemBank: a small-molecule screening and cheminformatics resource database

Author and article information

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 480

Cited by 260

Most referenced authors 345