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.

Availability: 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.

Figure 1.

Cumulative recall for ATC-recognition relative to rank of retrieval.

Figure 2.

Assembly of the SuperPred server and possible requests for ATC-code prediction. Data: the SuperPred server now contains 2500 compounds of the SuperDrug database. Additionally, 3800 experimental drugs were classified and stored on the server. The drugs are annotated by 7300 links to targets. Methods: the structural properties of the compounds are stored in so-called structural fingerprints, where each bit encodes for an element of the compound structure. The similarity of two compounds is calculated by using the Tanimoto coefficient. Moreover, physicochemical properties are stored for each compound. SuperPred can be used to find new targets for ligands and vice versa to find new ligands for medical biological targets. There are two possibilities to use the SuperPred server. The figure shows two examples for querying the SuperPred server.