SuperPred: update on drug classification and target prediction
| Autor: | Andrean Goede, Priyanka Banerjee, Robert Preissner, Bjoern-Oliver Gohlke, Jevgeni Erehman, Mathias Dunkel, Janette Nickel, Wen Wei Rong |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Web server
Internet Drug discovery Property (programming) Proteins Chemical similarity Biology Bioinformatics computer.software_genre Ligands Article Set (abstract data type) Drug class Similarity (network science) Pharmaceutical Preparations Drug Discovery Genetics Code (cryptography) Data mining computer Software |
| Zdroj: | Nucleic Acids Research |
| ISSN: | 1362-4962 0305-1048 |
| Popis: | The SuperPred web server connects chemical similarity of drug-like compounds with molecular targets and the therapeutic approach based on the similar property principle. Since the first release of this server, the number of known compound–target interactions has increased from 7000 to 665 000, which allows not only a better prediction quality but also the estimation of a confidence. Apart from the addition of quantitative binding data and the statistical consideration of the similarity distribution in all drug classes, new approaches were implemented to improve the target prediction. The 3D similarity as well as the occurrence of fragments and the concordance of physico-chemical properties is also taken into account. In addition, the effect of different fingerprints on the prediction was examined. The retrospective prediction of a drug class (ATC code of the WHO) allows the evaluation of methods and descriptors for a well-characterized set of approved drugs. The prediction is improved by 7.5% to a total accuracy of 75.1%. For query compounds with sufficient structural similarity, the web server allows prognoses about the medical indication area of novel compounds and to find new leads for known targets. SuperPred is publicly available without registration at: http://prediction.charite.de. |
| Databáze: | OpenAIRE |
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