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Database information

STITCH (Search Tool for Interacting Chemicals)

General information

Description: STITCH is a resource to explore known and predicted interactions of chemicals and proteins. Chemicals are linked to other chemicals and proteins by evidence derived from experiments, databases and the literature.
Year founded: 2008
Last update: 2016-01-04
Version: v5.0
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: Germany
Data type:
Data object:
NA
Database category:
Major organism:
NA
Keywords:

Contact information

University/Institution: Max Planck Institute for Molecular Cell Biology and Genetics
Address: Pfotenhauerstrasse 108, 01307 Dresden
City: Dresden
Province/State:
Country/Region: Germany
Contact name (PI/Team): Michael Kuhn
Contact email (PI/Helpdesk): mkuhn@mpi-cbg.de

Record metadata

Created on: 2015-06-20
Curated by:
Lina Ma [2018-05-29]
Zhang Zhang [2016-04-26]
Lin Xia [2016-04-15]
Lina Ma [2016-03-31]
Lin Xia [2016-03-28]
Mengwei Li [2016-02-18]
Lin Liu [2016-01-29]
Lin Liu [2016-01-03]
Lin Xia [2015-06-26]

Ranking

All databases:
127/4549 (97.23%)
Interaction:
19/671 (97.317%)
127
Total Rank
728
Citations
60.667
z-index

Community reviews

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Word cloud

Publications

26590256
STITCH 5: augmenting protein-chemical interaction networks with tissue and affinity data. [PMID: 26590256]
Szklarczyk D, Santos A, von Mering C, Jensen LJ, Bork P, Kuhn M.

Interactions between proteins and small molecules are an integral part of biological processes in living organisms. Information on these interactions is dispersed over many databases, texts and prediction methods, which makes it difficult to get a comprehensive overview of the available evidence. To address this, we have developed STITCH ('Search Tool for Interacting Chemicals') that integrates these disparate data sources for 430 000 chemicals into a single, easy-to-use resource. In addition to the increased scope of the database, we have implemented a new network view that gives the user the ability to view binding affinities of chemicals in the interaction network. This enables the user to get a quick overview of the potential effects of the chemical on its interaction partners. For each organism, STITCH provides a global network; however, not all proteins have the same pattern of spatial expression. Therefore, only a certain subset of interactions can occur simultaneously. In the new, fifth release of STITCH, we have implemented functionality to filter out the proteins and chemicals not associated with a given tissue. The STITCH database can be downloaded in full, accessed programmatically via an extensive API, or searched via a redesigned web interface at http://stitch.embl.de. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nucleic Acids Res. 2016:44(D1) | 134 Citations (from Europe PMC, 2020-02-15)
24293645
STITCH 4: integration of protein-chemical interactions with user data. [PMID: 24293645]
Kuhn M, Szklarczyk D, Pletscher-Frankild S, Blicher TH, von Mering C, Jensen LJ, Bork P.

STITCH is a database of protein-chemical interactions that integrates many sources of experimental and manually curated evidence with text-mining information and interaction predictions. Available at http://stitch.embl.de, the resulting interaction network includes 390 000 chemicals and 3.6 million proteins from 1133 organisms. Compared with the previous version, the number of high-confidence protein-chemical interactions in human has increased by 45%, to 367 000. In this version, we added features for users to upload their own data to STITCH in the form of internal identifiers, chemical structures or quantitative data. For example, a user can now upload a spreadsheet with screening hits to easily check which interactions are already known. To increase the coverage of STITCH, we expanded the text mining to include full-text articles and added a prediction method based on chemical structures. We further changed our scheme for transferring interactions between species to rely on orthology rather than protein similarity. This improves the performance within protein families, where scores are now transferred only to orthologous proteins, but not to paralogous proteins. STITCH can be accessed with a web-interface, an API and downloadable files.

Nucleic Acids Res. 2014:42(Database issue) | 151 Citations (from Europe PMC, 2020-02-15)
22075997
STITCH 3: zooming in on protein-chemical interactions. [PMID: 22075997]
Kuhn M, Szklarczyk D, Franceschini A, von Mering C, Jensen LJ, Bork P.

To facilitate the study of interactions between proteins and chemicals, we have created STITCH, an aggregated database of interactions connecting over 300,000 chemicals and 2.6 million proteins from 1133 organisms. Compared to the previous version, the number of chemicals with interactions and the number of high-confidence interactions both increase 4-fold. The database can be accessed interactively through a web interface, displaying interactions in an integrated network view. It is also available for computational studies through downloadable files and an API. As an extension in the current version, we offer the option to switch between two levels of detail, namely whether stereoisomers of a given compound are shown as a merged entity or as separate entities. Separate display of stereoisomers is necessary, for example, for carbohydrates and chiral drugs. Combining the isomers increases the coverage, as interaction databases and publications found through text mining will often refer to compounds without specifying the stereoisomer. The database is accessible at http://stitch.embl.de/.

Nucleic Acids Res. 2012:40(Database issue) | 121 Citations (from Europe PMC, 2020-02-15)
19897548
STITCH 2: an interaction network database for small molecules and proteins. [PMID: 19897548]
Kuhn M, Szklarczyk D, Franceschini A, Campillos M, von Mering C, Jensen LJ, Beyer A, Bork P.

Over the last years, the publicly available knowledge on interactions between small molecules and proteins has been steadily increasing. To create a network of interactions, STITCH aims to integrate the data dispersed over the literature and various databases of biological pathways, drug-target relationships and binding affinities. In STITCH 2, the number of relevant interactions is increased by incorporation of BindingDB, PharmGKB and the Comparative Toxicogenomics Database. The resulting network can be explored interactively or used as the basis for large-scale analyses. To facilitate links to other chemical databases, we adopt InChIKeys that allow identification of chemicals with a short, checksum-like string. STITCH 2.0 connects proteins from 630 organisms to over 74,000 different chemicals, including 2200 drugs. STITCH can be accessed at http://stitch.embl.de/.

Nucleic Acids Res. 2010:38(Database issue) | 110 Citations (from Europe PMC, 2020-02-15)
18084021
STITCH: interaction networks of chemicals and proteins. [PMID: 18084021]
Kuhn M, von Mering C, Campillos M, Jensen LJ, Bork P.

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/.

Nucleic Acids Res. 2008:36(Database issue) | 212 Citations (from Europe PMC, 2020-02-15)