title: SuperPred: drug classification and target prediction.
abstract: The drug classification scheme of the World Health Organization (WHO) [Anatomical Therapeutic Chemical (ATC)-code] connects chemical classification and therapeutic approach. It is generally accepted that compounds with similar physicochemical properties exhibit similar biological activity. If this hypothesis holds true for drugs, then the ATC-code, the putative medical indication area and potentially the medical target should be predictable on the basis of structural similarity. We have validated that the prediction of the drug class is reliable for WHO-classified drugs. The reliability of the predicted medical effects of the compounds increases with a rising number of (physico-) chemical properties similar to a drug with known function. The web-server translates a user-defined molecule into a structural fingerprint that is compared to about 6300 drugs, which are enriched by 7300 links to molecular targets of the drugs, derived through text mining followed by manual curation. Links to the affected pathways are provided. The similarity to the medical compounds is expressed by the Tanimoto coefficient that gives the structural similarity of two compounds. A similarity score higher than 0.85 results in correct ATC prediction for 81% of all cases. As the biological effect is well predictable, if the structural similarity is sufficient, the web-server allows prognoses about the medical indication area of novel compounds and to find new leads for known targets.
  
  
  BACKGROUND
  the system is freely accessible at http://bioinformatics.charite.de/superpred. SuperPred can be obtained via a Creative Commons Attribution Noncommercial-Share Alike 3.0 License.
authors.affiliation: Institute of Molecular Biology and Bioinformatics, Charité - University Medicine Berlin, Arnimallee 22, 14195 Berlin, Germany.
authors.forename: Mathias
authors.initials: M
authors.lastname: Dunkel
authors.forename: Stefan
authors.initials: S
authors.lastname: Günther
authors.forename: Jessica
authors.initials: J
authors.lastname: Ahmed
authors.forename: Burghardt
authors.initials: B
authors.lastname: Wittig
authors.forename: Robert
authors.initials: R
authors.lastname: Preissner
mesh_terms: D000806:Angiotensin-Converting Enzyme Inhibitors / Q000737:chemistry; D015195:Drug Design; D004656:Enalapril / Q000737:chemistry; D020407:Internet; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000145:classification*; D015203:Reproducibility of Results; D012984:Software; D013329:Structure-Activity Relationship; D014944:World Health Organization
chemical_list: D000806:Angiotensin-Converting Enzyme Inhibitors; D004364:Pharmaceutical Preparations; D004656:Enalapril