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SuperPred: update on drug classification and target prediction

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...

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Autores principales: Nickel, Janette, Gohlke, Bjoern-Oliver, Erehman, Jevgeni, Banerjee, Priyanka, Rong, Wen Wei, Goede, Andrean, Dunkel, Mathias, Preissner, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086135/
https://www.ncbi.nlm.nih.gov/pubmed/24878925
http://dx.doi.org/10.1093/nar/gku477
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author Nickel, Janette
Gohlke, Bjoern-Oliver
Erehman, Jevgeni
Banerjee, Priyanka
Rong, Wen Wei
Goede, Andrean
Dunkel, Mathias
Preissner, Robert
author_facet Nickel, Janette
Gohlke, Bjoern-Oliver
Erehman, Jevgeni
Banerjee, Priyanka
Rong, Wen Wei
Goede, Andrean
Dunkel, Mathias
Preissner, Robert
author_sort Nickel, Janette
collection PubMed
description 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.
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spelling pubmed-40861352014-11-04 SuperPred: update on drug classification and target prediction Nickel, Janette Gohlke, Bjoern-Oliver Erehman, Jevgeni Banerjee, Priyanka Rong, Wen Wei Goede, Andrean Dunkel, Mathias Preissner, Robert Nucleic Acids Res Article 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. Oxford University Press 2014-07-01 2014-05-30 /pmc/articles/PMC4086135/ /pubmed/24878925 http://dx.doi.org/10.1093/nar/gku477 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Nickel, Janette
Gohlke, Bjoern-Oliver
Erehman, Jevgeni
Banerjee, Priyanka
Rong, Wen Wei
Goede, Andrean
Dunkel, Mathias
Preissner, Robert
SuperPred: update on drug classification and target prediction
title SuperPred: update on drug classification and target prediction
title_full SuperPred: update on drug classification and target prediction
title_fullStr SuperPred: update on drug classification and target prediction
title_full_unstemmed SuperPred: update on drug classification and target prediction
title_short SuperPred: update on drug classification and target prediction
title_sort superpred: update on drug classification and target prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086135/
https://www.ncbi.nlm.nih.gov/pubmed/24878925
http://dx.doi.org/10.1093/nar/gku477
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