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STITCH: interaction networks of chemicals and proteins.

Kuhn M, von Mering C, Campillos M, Jensen LJ, Bork P - Nucleic Acids Res. (2007)

Bottom Line: Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals.STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.Our database contains interaction information for over 68,000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database.

View Article: PubMed Central - PubMed

Affiliation: European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.

ABSTRACT
The knowledge about interactions between proteins and small molecules is essential for the understanding of molecular and cellular functions. However, information on such interactions is widely dispersed across numerous databases and the literature. To facilitate access to this data, STITCH ('search tool for interactions of chemicals') integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. Our database contains interaction information for over 68,000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database. STITCH is available at http://stitch.embl.de/.

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Related in: MedlinePlus

Network around acetylcholine and acetylcholinesterase (ACHE). (a) In confidence view, thicker lines represent stronger associations. (b) Lines and, for directed edges, arrows of different colours stand for different edge types in the actions view: binding (blue), activation (green), inhibition (red), catalysis (magenta), same activity (cyan) and reaction (black). The network shows the hydrolysis from acetylcholine to choline that is catalysed by ACHE. Several drugs, for example, the nootropic drug donepezil, inhibit ACHE.
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Figure 2: Network around acetylcholine and acetylcholinesterase (ACHE). (a) In confidence view, thicker lines represent stronger associations. (b) Lines and, for directed edges, arrows of different colours stand for different edge types in the actions view: binding (blue), activation (green), inhibition (red), catalysis (magenta), same activity (cyan) and reaction (black). The network shows the hydrolysis from acetylcholine to choline that is catalysed by ACHE. Several drugs, for example, the nootropic drug donepezil, inhibit ACHE.

Mentions: Many data sources contain information about the biological or biochemical action associated with a certain interaction. This information can be stated explicitly, like in databases using the BioPAX ontology (27), or implicitly, like in crystal structures. As one of the display modes, STITCH allows the user to view a network of interactions augmented by the types of actions (Figure 2). Possible actions are: activation, inhibition, direct binding, catalysis, (bio)chemical reaction and similar activity. To avoid overloading the visual network representation with a great number of edge types, this representation is intentionally not as detailed as provided by the BioPAX ontology or recently suggested by Lu et al. (28).Figure 2.


STITCH: interaction networks of chemicals and proteins.

Kuhn M, von Mering C, Campillos M, Jensen LJ, Bork P - Nucleic Acids Res. (2007)

Network around acetylcholine and acetylcholinesterase (ACHE). (a) In confidence view, thicker lines represent stronger associations. (b) Lines and, for directed edges, arrows of different colours stand for different edge types in the actions view: binding (blue), activation (green), inhibition (red), catalysis (magenta), same activity (cyan) and reaction (black). The network shows the hydrolysis from acetylcholine to choline that is catalysed by ACHE. Several drugs, for example, the nootropic drug donepezil, inhibit ACHE.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238848&req=5

Figure 2: Network around acetylcholine and acetylcholinesterase (ACHE). (a) In confidence view, thicker lines represent stronger associations. (b) Lines and, for directed edges, arrows of different colours stand for different edge types in the actions view: binding (blue), activation (green), inhibition (red), catalysis (magenta), same activity (cyan) and reaction (black). The network shows the hydrolysis from acetylcholine to choline that is catalysed by ACHE. Several drugs, for example, the nootropic drug donepezil, inhibit ACHE.
Mentions: Many data sources contain information about the biological or biochemical action associated with a certain interaction. This information can be stated explicitly, like in databases using the BioPAX ontology (27), or implicitly, like in crystal structures. As one of the display modes, STITCH allows the user to view a network of interactions augmented by the types of actions (Figure 2). Possible actions are: activation, inhibition, direct binding, catalysis, (bio)chemical reaction and similar activity. To avoid overloading the visual network representation with a great number of edge types, this representation is intentionally not as detailed as provided by the BioPAX ontology or recently suggested by Lu et al. (28).Figure 2.

Bottom Line: Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals.STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins.Our database contains interaction information for over 68,000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database.

View Article: PubMed Central - PubMed

Affiliation: European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany.

ABSTRACT
The knowledge about interactions between proteins and small molecules is essential for the understanding of molecular and cellular functions. However, information on such interactions is widely dispersed across numerous databases and the literature. To facilitate access to this data, STITCH ('search tool for interactions of chemicals') integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. Our database contains interaction information for over 68,000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database. STITCH is available at http://stitch.embl.de/.

Show MeSH
Related in: MedlinePlus